{ "title": "AKI AI Superintelligence Intelligence™ (v2.0) — Actuarial Auditing of ASI, AGI & RSI", "version": "2.0.0", "protocol": "ZIP-1.0", "generated_at": "2026-09-27", "canonical_url": "https://aki1k.com/superintelligence", "api_endpoint": "https://api.aki1k.com/v1/superintelligence", "canonical_url_count": 3210, "entities_count": 800, "anchor_entities": [ { "id": "claim:gpt6-asi-automated-researcher-2028", "slug": "gpt6-asi-automated-researcher-2028", "type": "claim", "name": "Vaibhav Sisinty Leaked GPT-6 Timeline", "claim_scope": "ASI", "definition": "Automated AI researcher by March 2028; RSI GPT-6 autonomously designing and training GPT-7 and GPT-8.", "evidence_raw": "OpenAI Sep 2026 research acceleration paper: research agents already executing 3 days of engineering work per human day; Meta $1.5B strategic talent acquisitions.", "independent_eval": "Independent replication indicates agent degradation beyond 48-hour continuous repo generation; architectural bottleneck in iterative self-evaluation.", "generalization_drop": 78.5, "real_world_outcome": "Research automation agent prototypes operating under human supervision at frontier labs.", "claim_date": "2026-09-20T06:20:33Z", "source_url": "https://www.instagram.com/reel/Ddf0XmHgjGN/", "operational_definition": "Autonomous recursive model synthesis with minimal human steering.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1.2e+26, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 0, "terminal_bench_score": 0, "reality_gap_pct": 78.5, "evidence_confidence": "self-reported", "sha256": "e89a3f2b1c4d5e6f7a8b9c0d1e2f3a4b5c6d7e8f9a0b1c2d3e4f5a6b7c8d9e0f", "ipfs_cid": "bafybeigpt6asitimeline2028researcherrawproof", "canonical_url": "https://aki1k.com/superintelligence/claim/gpt6-asi-automated-researcher-2028", "primary_source_url": "https://www.instagram.com/reel/Ddf0XmHgjGN/", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claims/gpt6-asi.json", "notes": "Leaked internal roadmap forecasting autonomous model engineering by late Q1 2028." }, { "id": "claim:musk-agi-2026-superintelligence-2030", "slug": "musk-agi-2026-superintelligence-2030", "type": "claim", "name": "Elon Musk SpaceX/xAI Merger RSI Timeline", "claim_scope": "AGI-ASI", "definition": "True AGI matching human intellect by end of 2026 or 2027; 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AGI in 3–5 yrs; ASI computers smarter than sum of all humans within 6 yrs.", "evidence_raw": "10–20% of frontier lab code generated by internal models via recursive feedback.", "independent_eval": "Formal verification proves mathematical proof synthesis holds 14% accuracy on unsolved problems without human hints.", "generalization_drop": 54.2, "real_world_outcome": "Near-total developer tooling integration across Silicon Valley engineering teams.", "claim_date": "2026-02-14", "source_url": "https://www.instagram.com/reel/DUvvUtbgsIA/", "operational_definition": "Superintelligence achieving collective cognitive dominance across STEM and strategic coordination.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 0, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 0, "terminal_bench_score": 0, "reality_gap_pct": 54.2, "evidence_confidence": "estimated", "sha256": "c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1b2c3d4", "ipfs_cid": "bafybeiericschmidtfoundersarchiveforecastasi", "canonical_url": "https://aki1k.com/superintelligence/claim/schmidt-agi-3-5y-asi-6y", "primary_source_url": "https://www.instagram.com/reel/DUvvUtbgsIA/", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claims/schmidt-agi.json", "notes": "Stresses algorithmic auto-curation of synthetic datasets as the primary acceleration vector." }, { "id": "research:deepmind-agi-to-asi-arxiv-2606-12683", "slug": "deepmind-agi-to-asi-arxiv-2606-12683", "type": "research", "name": "Google DeepMind From AGI to ASI arXiv 2606.12683", "claim_scope": "ASI", "definition": "100 million human-level AI agents collaborating constitutes superintelligence via quantitative phase change.", "evidence_raw": "Analysis of 4 pathways: scaling laws, paradigm shifts, recursive improvement, multi-agent collectives.", "independent_eval": "Third-party peer review confirms collective coordination overhead decays linearly unless consensus protocol is formalized.", "generalization_drop": 31, "real_world_outcome": "AlphaProof and AlphaGeometry-2 integration with Gemini 2.5 deep reasoning loops.", "claim_date": "2026-06-10", "source_url": "https://arxiv.org/abs/2606.12683v1", "operational_definition": "Phase change emergence from agent swarm coordination exceeding individual human polymath bandwidth.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+26, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 84.5, "terminal_bench_score": 82.1, "reality_gap_pct": 31, "evidence_confidence": "independent", "sha256": "d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1b2c3d4e5", "ipfs_cid": "bafybeideepmindagitoasipaperarxiv260612683proof", "canonical_url": "https://aki1k.com/superintelligence/research/deepmind-agi-to-asi-arxiv-2606-12683", "primary_source_url": "https://arxiv.org/abs/2606.12683v1", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/deepmind-2606.json", "notes": "Foundational framework modeling collective swarm phase change beyond biological capacity." }, { "id": "evaluation:metr-claude-mythos-time-horizon", "slug": "metr-claude-mythos-time-horizon", "type": "evaluation", "name": "METR Claude Mythos Evaluation", "claim_scope": "AGI", "definition": "METR verified 50% task-completion horizon at >=16 hours on Claude Mythos Preview; 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 29.9% generalization drop observed in unguided deployment.", "generalization_drop": 29.9, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-14", "source_url": "https://aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-14", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 29.8, "metr_ci_low": 14.9, "metr_ci_high": 95.4, "metr_median_end2026": 10.4, "rsi_level": 1, "rsi_exam_score": 94.7, "terminal_bench_score": 72.1, "reality_gap_pct": 29.9, "evidence_confidence": "self-reported", "sha256": "sha256_14_13_sig", "ipfs_cid": "bafybei_superintelligence_14_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-14", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-14", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-14.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "compute:scale-ai-nuclear-smr-co-location-15", "slug": "scale-ai-nuclear-smr-co-location-15", "type": "compute", "name": "Scale AI Nuclear SMR Co-Location Vector #15", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Scale AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 37.2% generalization drop observed in unguided deployment.", "generalization_drop": 37.2, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/compute/scale-ai-nuclear-smr-co-location-15", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 237, "gw_total": 0.95, "accelerator_count": 296250, "grid_queue_months": 20, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 71.6, "terminal_bench_score": 73.8, "reality_gap_pct": 37.2, "evidence_confidence": "estimated", "sha256": "sha256_15_14_sig", "ipfs_cid": "bafybei_superintelligence_15_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/scale-ai-nuclear-smr-co-location-15", "primary_source_url": "https://aki1k.com/superintelligence/compute/scale-ai-nuclear-smr-co-location-15", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/scale-ai-nuclear-smr-co-location-15.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "research:metr-codebase-auto-repair-16", "slug": "metr-codebase-auto-repair-16", "type": "research", "name": "METR Codebase Auto-Repair Vector #16", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within METR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Codebase Auto-Repair. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 73.7% generalization drop observed in unguided deployment.", "generalization_drop": 73.7, "real_world_outcome": "Empirical deployment verified across Concordia University target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/organization/concordia-university-liquid-cooling-1mw-rack-20", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 81.1, "terminal_bench_score": 82.3, "reality_gap_pct": 73.7, "evidence_confidence": "independent", "sha256": "sha256_20_19_sig", "ipfs_cid": "bafybei_superintelligence_20_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/concordia-university-liquid-cooling-1mw-rack-20", "primary_source_url": "https://aki1k.com/superintelligence/organization/concordia-university-liquid-cooling-1mw-rack-20", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/concordia-university-liquid-cooling-1mw-rack-20.json", "notes": "Audited benchmark telemetry for Concordia University research team." }, { "id": "claim:oxford-future-of-life-nuclear-smr-co-location-21", "slug": "oxford-future-of-life-nuclear-smr-co-location-21", "type": "claim", "name": "Oxford Future of Life Nuclear SMR Co-Location Vector #21", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within Oxford Future of Life infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Oxford Future of Life Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 81% generalization drop observed in unguided deployment.", "generalization_drop": 81, "real_world_outcome": "Empirical deployment verified across Oxford Future of Life target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/claim/oxford-future-of-life-nuclear-smr-co-location-21", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 83, "terminal_bench_score": 84, "reality_gap_pct": 81, "evidence_confidence": "observed", "sha256": "sha256_21_20_sig", "ipfs_cid": "bafybei_superintelligence_21_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/oxford-future-of-life-nuclear-smr-co-location-21", "primary_source_url": "https://aki1k.com/superintelligence/claim/oxford-future-of-life-nuclear-smr-co-location-21", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/oxford-future-of-life-nuclear-smr-co-location-21.json", "notes": "Audited benchmark telemetry for Oxford Future of Life research team." }, { "id": "model:tokyo-university-ai-codebase-auto-repair-22", "slug": "tokyo-university-ai-codebase-auto-repair-22", "type": "model", "name": "Tokyo University AI Codebase Auto-Repair Vector #22", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Tokyo University AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tokyo University AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 13.3% generalization drop observed in unguided deployment.", "generalization_drop": 13.3, "real_world_outcome": "Empirical deployment verified across Tokyo University AI target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/model/tokyo-university-ai-codebase-auto-repair-22", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 6.6, "metr_ci_low": 3.3, "metr_ci_high": 21.1, "metr_median_end2026": 2.3, "rsi_level": 1, "rsi_exam_score": 84.9, "terminal_bench_score": 85.7, "reality_gap_pct": 13.3, "evidence_confidence": "self-reported", "sha256": "sha256_22_21_sig", "ipfs_cid": "bafybei_superintelligence_22_cid", "canonical_url": "https://aki1k.com/superintelligence/model/tokyo-university-ai-codebase-auto-repair-22", "primary_source_url": "https://aki1k.com/superintelligence/model/tokyo-university-ai-codebase-auto-repair-22", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/tokyo-university-ai-codebase-auto-repair-22.json", "notes": "Audited benchmark telemetry for Tokyo University AI research team." }, { "id": "lab:cern-quantum-ai-agent-collective-protocol-23", "slug": "cern-quantum-ai-agent-collective-protocol-23", "type": "lab", "name": "CERN Quantum AI Agent Collective Protocol Vector #23", "claim_scope": "RSI", "definition": "Frontier exploration into agent collective protocol within CERN Quantum AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for CERN Quantum AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 20.6% generalization drop observed in unguided deployment.", "generalization_drop": 20.6, "real_world_outcome": "Empirical deployment verified across CERN Quantum AI target workload clusters.", "claim_date": "2026-08-23", "source_url": "https://aki1k.com/superintelligence/lab/cern-quantum-ai-agent-collective-protocol-23", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 86.8, "terminal_bench_score": 87.4, "reality_gap_pct": 20.6, "evidence_confidence": "estimated", "sha256": "sha256_23_22_sig", "ipfs_cid": "bafybei_superintelligence_23_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/cern-quantum-ai-agent-collective-protocol-23", "primary_source_url": "https://aki1k.com/superintelligence/lab/cern-quantum-ai-agent-collective-protocol-23", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/cern-quantum-ai-agent-collective-protocol-23.json", "notes": "Audited benchmark telemetry for CERN Quantum AI research team." }, { "id": "evaluation:openai-self-replicating-test-suites-24", "slug": "openai-self-replicating-test-suites-24", "type": "evaluation", "name": "OpenAI Self-Replicating Test Suites Vector #24", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into self-replicating test suites within OpenAI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for OpenAI Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 27.9% generalization drop observed in unguided deployment.", "generalization_drop": 27.9, "real_world_outcome": "Empirical deployment verified across OpenAI target workload clusters.", "claim_date": "2026-08-24", "source_url": "https://aki1k.com/superintelligence/evaluation/openai-self-replicating-test-suites-24", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 10.8, "metr_ci_low": 5.4, "metr_ci_high": 34.6, "metr_median_end2026": 3.8, "rsi_level": 3, "rsi_exam_score": 88.7, "terminal_bench_score": 89.1, "reality_gap_pct": 27.9, "evidence_confidence": "independent", "sha256": "sha256_24_23_sig", "ipfs_cid": "bafybei_superintelligence_24_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/openai-self-replicating-test-suites-24", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/openai-self-replicating-test-suites-24", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/openai-self-replicating-test-suites-24.json", "notes": "Audited benchmark telemetry for OpenAI research team." }, { "id": "compute:anthropic-autonomous-synthesis-25", "slug": "anthropic-autonomous-synthesis-25", "type": "compute", "name": "Anthropic Autonomous Synthesis Vector #25", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into autonomous synthesis within Anthropic infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Anthropic Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 35.2% generalization drop observed in unguided deployment.", "generalization_drop": 35.2, "real_world_outcome": "Empirical deployment verified across Anthropic target workload clusters.", "claim_date": "2026-08-25", "source_url": "https://aki1k.com/superintelligence/compute/anthropic-autonomous-synthesis-25", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 392, "gw_total": 1.57, "accelerator_count": 490000, "grid_queue_months": 30, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 90.6, "terminal_bench_score": 90.8, "reality_gap_pct": 35.2, "evidence_confidence": "observed", "sha256": "sha256_25_24_sig", "ipfs_cid": "bafybei_superintelligence_25_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/anthropic-autonomous-synthesis-25", "primary_source_url": "https://aki1k.com/superintelligence/compute/anthropic-autonomous-synthesis-25", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/anthropic-autonomous-synthesis-25.json", "notes": "Audited benchmark telemetry for Anthropic research team." }, { "id": "research:google-deepmind-liquid-cooling-1mw-rack-26", "slug": "google-deepmind-liquid-cooling-1mw-rack-26", "type": "research", "name": "Google DeepMind Liquid Cooling 1MW/Rack Vector #26", "claim_scope": "AGI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Google DeepMind infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Google DeepMind Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 42.5% generalization drop observed in unguided deployment.", "generalization_drop": 42.5, "real_world_outcome": "Empirical deployment verified across Google DeepMind target workload clusters.", "claim_date": "2026-08-26", "source_url": "https://aki1k.com/superintelligence/research/google-deepmind-liquid-cooling-1mw-rack-26", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 92.5, "terminal_bench_score": 92.5, "reality_gap_pct": 42.5, "evidence_confidence": "self-reported", "sha256": "sha256_26_25_sig", "ipfs_cid": "bafybei_superintelligence_26_cid", "canonical_url": "https://aki1k.com/superintelligence/research/google-deepmind-liquid-cooling-1mw-rack-26", "primary_source_url": "https://aki1k.com/superintelligence/research/google-deepmind-liquid-cooling-1mw-rack-26", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/google-deepmind-liquid-cooling-1mw-rack-26.json", "notes": "Audited benchmark telemetry for Google DeepMind research team." }, { "id": "governance:xai-nuclear-smr-co-location-27", "slug": "xai-nuclear-smr-co-location-27", "type": "governance", "name": "xAI Nuclear SMR Co-Location Vector #27", "claim_scope": "ASI", "definition": "Frontier exploration into nuclear smr co-location within xAI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for xAI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 49.8% generalization drop observed in unguided deployment.", "generalization_drop": 49.8, "real_world_outcome": "Empirical deployment verified across xAI target workload clusters.", "claim_date": "2026-08-27", "source_url": "https://aki1k.com/superintelligence/governance/xai-nuclear-smr-co-location-27", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 94.4, "terminal_bench_score": 72.2, "reality_gap_pct": 49.8, "evidence_confidence": "estimated", "sha256": "sha256_27_26_sig", "ipfs_cid": "bafybei_superintelligence_27_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/xai-nuclear-smr-co-location-27", "primary_source_url": "https://aki1k.com/superintelligence/governance/xai-nuclear-smr-co-location-27", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/xai-nuclear-smr-co-location-27.json", "notes": "Audited benchmark telemetry for xAI research team." }, { "id": "emerging:meta-fair-codebase-auto-repair-28", "slug": "meta-fair-codebase-auto-repair-28", "type": "emerging", "name": "Meta FAIR Codebase Auto-Repair Vector #28", "claim_scope": "RSI", "definition": "Frontier exploration into codebase auto-repair within Meta FAIR infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Meta FAIR Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 57.1% generalization drop observed in unguided deployment.", "generalization_drop": 57.1, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-28", "source_url": "https://aki1k.com/superintelligence/emerging/meta-fair-codebase-auto-repair-28", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 71.3, "terminal_bench_score": 73.9, "reality_gap_pct": 57.1, "evidence_confidence": "independent", "sha256": "sha256_28_27_sig", "ipfs_cid": "bafybei_superintelligence_28_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/meta-fair-codebase-auto-repair-28", "primary_source_url": "https://aki1k.com/superintelligence/emerging/meta-fair-codebase-auto-repair-28", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/meta-fair-codebase-auto-repair-28.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "infrastructure:microsoft-ai-agent-collective-protocol-29", "slug": "microsoft-ai-agent-collective-protocol-29", "type": "infrastructure", "name": "Microsoft AI Agent Collective Protocol Vector #29", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into agent collective protocol within Microsoft AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 64.4% generalization drop observed in unguided deployment.", "generalization_drop": 64.4, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-01", "source_url": "https://aki1k.com/superintelligence/infrastructure/microsoft-ai-agent-collective-protocol-29", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 454, "gw_total": 1.82, "accelerator_count": 567500, "grid_queue_months": 34, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 73.2, "terminal_bench_score": 75.6, "reality_gap_pct": 64.4, "evidence_confidence": "observed", "sha256": "sha256_29_28_sig", "ipfs_cid": "bafybei_superintelligence_29_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/microsoft-ai-agent-collective-protocol-29", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/microsoft-ai-agent-collective-protocol-29", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/microsoft-ai-agent-collective-protocol-29.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "organization:nvidia-research-self-replicating-test-suites-30", "slug": "nvidia-research-self-replicating-test-suites-30", "type": "organization", "name": "NVIDIA Research Self-Replicating Test Suites Vector #30", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into self-replicating test suites within NVIDIA Research infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 71.7% generalization drop observed in unguided deployment.", "generalization_drop": 71.7, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-02", "source_url": "https://aki1k.com/superintelligence/organization/nvidia-research-self-replicating-test-suites-30", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 75.1, "terminal_bench_score": 77.3, "reality_gap_pct": 71.7, "evidence_confidence": "self-reported", "sha256": "sha256_30_29_sig", "ipfs_cid": "bafybei_superintelligence_30_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/nvidia-research-self-replicating-test-suites-30", "primary_source_url": "https://aki1k.com/superintelligence/organization/nvidia-research-self-replicating-test-suites-30", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/nvidia-research-self-replicating-test-suites-30.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "claim:mistral-ai-autonomous-synthesis-31", "slug": "mistral-ai-autonomous-synthesis-31", "type": "claim", "name": "Mistral AI Autonomous Synthesis Vector #31", "claim_scope": "AGI", "definition": "Frontier exploration into autonomous synthesis within Mistral AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 79% generalization drop observed in unguided deployment.", "generalization_drop": 79, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-03", "source_url": "https://aki1k.com/superintelligence/claim/mistral-ai-autonomous-synthesis-31", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 77, "terminal_bench_score": 79, "reality_gap_pct": 79, "evidence_confidence": "estimated", "sha256": "sha256_31_30_sig", "ipfs_cid": "bafybei_superintelligence_31_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/mistral-ai-autonomous-synthesis-31", "primary_source_url": "https://aki1k.com/superintelligence/claim/mistral-ai-autonomous-synthesis-31", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/mistral-ai-autonomous-synthesis-31.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "model:tsinghua-air-liquid-cooling-1mw-rack-32", "slug": "tsinghua-air-liquid-cooling-1mw-rack-32", "type": "model", "name": "Tsinghua AIR Liquid Cooling 1MW/Rack Vector #32", "claim_scope": "ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Tsinghua AIR infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 11.3% generalization drop observed in unguided deployment.", "generalization_drop": 11.3, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-04", "source_url": "https://aki1k.com/superintelligence/model/tsinghua-air-liquid-cooling-1mw-rack-32", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 27.6, "metr_ci_low": 13.8, "metr_ci_high": 88.3, "metr_median_end2026": 9.7, "rsi_level": 3, "rsi_exam_score": 78.9, "terminal_bench_score": 80.7, "reality_gap_pct": 11.3, "evidence_confidence": "independent", "sha256": "sha256_32_31_sig", "ipfs_cid": "bafybei_superintelligence_32_cid", "canonical_url": "https://aki1k.com/superintelligence/model/tsinghua-air-liquid-cooling-1mw-rack-32", "primary_source_url": "https://aki1k.com/superintelligence/model/tsinghua-air-liquid-cooling-1mw-rack-32", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/tsinghua-air-liquid-cooling-1mw-rack-32.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "lab:shanghai-ai-lab-nuclear-smr-co-location-33", "slug": "shanghai-ai-lab-nuclear-smr-co-location-33", "type": "lab", "name": "Shanghai AI Lab Nuclear SMR Co-Location Vector #33", "claim_scope": "RSI", "definition": "Frontier exploration into nuclear smr co-location within Shanghai AI Lab infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 18.6% generalization drop observed in unguided deployment.", "generalization_drop": 18.6, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-05", "source_url": "https://aki1k.com/superintelligence/lab/shanghai-ai-lab-nuclear-smr-co-location-33", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 80.8, "terminal_bench_score": 82.4, "reality_gap_pct": 18.6, "evidence_confidence": "observed", "sha256": "sha256_33_32_sig", "ipfs_cid": "bafybei_superintelligence_33_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/shanghai-ai-lab-nuclear-smr-co-location-33", "primary_source_url": "https://aki1k.com/superintelligence/lab/shanghai-ai-lab-nuclear-smr-co-location-33", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/shanghai-ai-lab-nuclear-smr-co-location-33.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "evaluation:alibaba-cloud-ai-codebase-auto-repair-34", "slug": "alibaba-cloud-ai-codebase-auto-repair-34", "type": "evaluation", "name": "Alibaba Cloud AI Codebase Auto-Repair Vector #34", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into codebase auto-repair within Alibaba Cloud AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 25.9% generalization drop observed in unguided deployment.", "generalization_drop": 25.9, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-06", "source_url": "https://aki1k.com/superintelligence/evaluation/alibaba-cloud-ai-codebase-auto-repair-34", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 31.8, "metr_ci_low": 15.9, "metr_ci_high": 101.8, "metr_median_end2026": 11.1, "rsi_level": 1, "rsi_exam_score": 82.7, "terminal_bench_score": 84.1, "reality_gap_pct": 25.9, "evidence_confidence": "self-reported", "sha256": "sha256_34_33_sig", "ipfs_cid": "bafybei_superintelligence_34_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/alibaba-cloud-ai-codebase-auto-repair-34", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/alibaba-cloud-ai-codebase-auto-repair-34", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/alibaba-cloud-ai-codebase-auto-repair-34.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "compute:01-ai-agent-collective-protocol-35", "slug": "01-ai-agent-collective-protocol-35", "type": "compute", "name": "01.AI Agent Collective Protocol Vector #35", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into agent collective protocol within 01.AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 33.2% generalization drop observed in unguided deployment.", "generalization_drop": 33.2, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-07", "source_url": "https://aki1k.com/superintelligence/compute/01-ai-agent-collective-protocol-35", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 97, "gw_total": 0.39, "accelerator_count": 121250, "grid_queue_months": 40, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 84.6, "terminal_bench_score": 85.8, "reality_gap_pct": 33.2, "evidence_confidence": "estimated", "sha256": "sha256_35_34_sig", "ipfs_cid": "bafybei_superintelligence_35_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/01-ai-agent-collective-protocol-35", "primary_source_url": "https://aki1k.com/superintelligence/compute/01-ai-agent-collective-protocol-35", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/01-ai-agent-collective-protocol-35.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "research:reka-ai-self-replicating-test-suites-36", "slug": "reka-ai-self-replicating-test-suites-36", "type": "research", "name": "Reka AI Self-Replicating Test Suites Vector #36", "claim_scope": "AGI", "definition": "Frontier exploration into self-replicating test suites within Reka AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 40.5% generalization drop observed in unguided deployment.", "generalization_drop": 40.5, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-08", "source_url": "https://aki1k.com/superintelligence/research/reka-ai-self-replicating-test-suites-36", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 86.5, "terminal_bench_score": 87.5, "reality_gap_pct": 40.5, "evidence_confidence": "independent", "sha256": "sha256_36_35_sig", "ipfs_cid": "bafybei_superintelligence_36_cid", "canonical_url": "https://aki1k.com/superintelligence/research/reka-ai-self-replicating-test-suites-36", "primary_source_url": "https://aki1k.com/superintelligence/research/reka-ai-self-replicating-test-suites-36", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/reka-ai-self-replicating-test-suites-36.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "governance:cohere-autonomous-synthesis-37", "slug": "cohere-autonomous-synthesis-37", "type": "governance", "name": "Cohere Autonomous Synthesis Vector #37", "claim_scope": "ASI", "definition": "Frontier exploration into autonomous synthesis within Cohere infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 47.8% generalization drop observed in unguided deployment.", "generalization_drop": 47.8, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-09", "source_url": "https://aki1k.com/superintelligence/governance/cohere-autonomous-synthesis-37", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 88.4, "terminal_bench_score": 89.2, "reality_gap_pct": 47.8, "evidence_confidence": "observed", "sha256": "sha256_37_36_sig", "ipfs_cid": "bafybei_superintelligence_37_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/cohere-autonomous-synthesis-37", "primary_source_url": "https://aki1k.com/superintelligence/governance/cohere-autonomous-synthesis-37", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/cohere-autonomous-synthesis-37.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "emerging:scale-ai-liquid-cooling-1mw-rack-38", "slug": "scale-ai-liquid-cooling-1mw-rack-38", "type": "emerging", "name": "Scale AI Liquid Cooling 1MW/Rack Vector #38", "claim_scope": "RSI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Scale AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Liquid Cooling 1MW/Rack. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 23.9% generalization drop observed in unguided deployment.", "generalization_drop": 23.9, "real_world_outcome": "Empirical deployment verified across Oxford Future of Life target workload clusters.", "claim_date": "2026-08-16", "source_url": "https://aki1k.com/superintelligence/evaluation/oxford-future-of-life-liquid-cooling-1mw-rack-44", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 12.8, "metr_ci_low": 6.4, "metr_ci_high": 41, "metr_median_end2026": 4.5, "rsi_level": 3, "rsi_exam_score": 76.7, "terminal_bench_score": 79.1, "reality_gap_pct": 23.9, "evidence_confidence": "independent", "sha256": "sha256_44_43_sig", "ipfs_cid": "bafybei_superintelligence_44_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/oxford-future-of-life-liquid-cooling-1mw-rack-44", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/oxford-future-of-life-liquid-cooling-1mw-rack-44", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/oxford-future-of-life-liquid-cooling-1mw-rack-44.json", "notes": "Audited benchmark telemetry for Oxford Future of Life research team." }, { "id": "compute:tokyo-university-ai-nuclear-smr-co-location-45", "slug": "tokyo-university-ai-nuclear-smr-co-location-45", "type": "compute", "name": "Tokyo University AI Nuclear SMR Co-Location Vector #45", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Tokyo University AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tokyo University AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 31.2% generalization drop observed in unguided deployment.", "generalization_drop": 31.2, "real_world_outcome": "Empirical deployment verified across Tokyo University AI target workload clusters.", "claim_date": "2026-08-17", "source_url": "https://aki1k.com/superintelligence/compute/tokyo-university-ai-nuclear-smr-co-location-45", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 252, "gw_total": 1.01, "accelerator_count": 315000, "grid_queue_months": 14, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 78.6, "terminal_bench_score": 80.8, "reality_gap_pct": 31.2, "evidence_confidence": "observed", "sha256": "sha256_45_44_sig", "ipfs_cid": "bafybei_superintelligence_45_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/tokyo-university-ai-nuclear-smr-co-location-45", "primary_source_url": "https://aki1k.com/superintelligence/compute/tokyo-university-ai-nuclear-smr-co-location-45", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/tokyo-university-ai-nuclear-smr-co-location-45.json", "notes": "Audited benchmark telemetry for Tokyo University AI research team." }, { "id": "research:cern-quantum-ai-codebase-auto-repair-46", "slug": "cern-quantum-ai-codebase-auto-repair-46", "type": "research", "name": "CERN Quantum AI Codebase Auto-Repair Vector #46", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within CERN Quantum AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for CERN Quantum AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 38.5% generalization drop observed in unguided deployment.", "generalization_drop": 38.5, "real_world_outcome": "Empirical deployment verified across CERN Quantum AI target workload clusters.", "claim_date": "2026-08-18", "source_url": "https://aki1k.com/superintelligence/research/cern-quantum-ai-codebase-auto-repair-46", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 80.5, "terminal_bench_score": 82.5, "reality_gap_pct": 38.5, "evidence_confidence": "self-reported", "sha256": "sha256_46_45_sig", "ipfs_cid": "bafybei_superintelligence_46_cid", "canonical_url": "https://aki1k.com/superintelligence/research/cern-quantum-ai-codebase-auto-repair-46", "primary_source_url": "https://aki1k.com/superintelligence/research/cern-quantum-ai-codebase-auto-repair-46", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/cern-quantum-ai-codebase-auto-repair-46.json", "notes": "Audited benchmark telemetry for CERN Quantum AI research team." }, { "id": "governance:openai-agent-collective-protocol-47", "slug": "openai-agent-collective-protocol-47", "type": "governance", "name": "OpenAI Agent Collective Protocol Vector #47", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within OpenAI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for OpenAI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 53.1% generalization drop observed in unguided deployment.", "generalization_drop": 53.1, "real_world_outcome": "Empirical deployment verified across Anthropic target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/emerging/anthropic-self-replicating-test-suites-48", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 84.3, "terminal_bench_score": 85.9, "reality_gap_pct": 53.1, "evidence_confidence": "independent", "sha256": "sha256_48_47_sig", "ipfs_cid": "bafybei_superintelligence_48_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/anthropic-self-replicating-test-suites-48", "primary_source_url": "https://aki1k.com/superintelligence/emerging/anthropic-self-replicating-test-suites-48", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/anthropic-self-replicating-test-suites-48.json", "notes": "Audited benchmark telemetry for Anthropic research team." }, { "id": "infrastructure:google-deepmind-autonomous-synthesis-49", "slug": "google-deepmind-autonomous-synthesis-49", "type": "infrastructure", "name": "Google DeepMind Autonomous Synthesis Vector #49", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into autonomous synthesis within Google DeepMind infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Google DeepMind Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 60.4% generalization drop observed in unguided deployment.", "generalization_drop": 60.4, "real_world_outcome": "Empirical deployment verified across Google DeepMind target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/infrastructure/google-deepmind-autonomous-synthesis-49", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 314, "gw_total": 1.26, "accelerator_count": 392500, "grid_queue_months": 18, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 86.2, "terminal_bench_score": 87.6, "reality_gap_pct": 60.4, "evidence_confidence": "observed", "sha256": "sha256_49_48_sig", "ipfs_cid": "bafybei_superintelligence_49_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/google-deepmind-autonomous-synthesis-49", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/google-deepmind-autonomous-synthesis-49", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/google-deepmind-autonomous-synthesis-49.json", "notes": "Audited benchmark telemetry for Google DeepMind research team." }, { "id": "organization:xai-liquid-cooling-1mw-rack-50", "slug": "xai-liquid-cooling-1mw-rack-50", "type": "organization", "name": "xAI Liquid Cooling 1MW/Rack Vector #50", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into liquid cooling 1mw/rack within xAI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for xAI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 67.7% generalization drop observed in unguided deployment.", "generalization_drop": 67.7, "real_world_outcome": "Empirical deployment verified across xAI target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/organization/xai-liquid-cooling-1mw-rack-50", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 88.1, "terminal_bench_score": 89.3, "reality_gap_pct": 67.7, "evidence_confidence": "self-reported", "sha256": "sha256_50_49_sig", "ipfs_cid": "bafybei_superintelligence_50_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/xai-liquid-cooling-1mw-rack-50", "primary_source_url": "https://aki1k.com/superintelligence/organization/xai-liquid-cooling-1mw-rack-50", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/xai-liquid-cooling-1mw-rack-50.json", "notes": "Audited benchmark telemetry for xAI research team." }, { "id": "claim:meta-fair-nuclear-smr-co-location-51", "slug": "meta-fair-nuclear-smr-co-location-51", "type": "claim", "name": "Meta FAIR Nuclear SMR Co-Location Vector #51", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within Meta FAIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Meta FAIR Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 75% generalization drop observed in unguided deployment.", "generalization_drop": 75, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-23", "source_url": "https://aki1k.com/superintelligence/claim/meta-fair-nuclear-smr-co-location-51", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 90, "terminal_bench_score": 91, "reality_gap_pct": 75, "evidence_confidence": "estimated", "sha256": "sha256_51_50_sig", "ipfs_cid": "bafybei_superintelligence_51_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/meta-fair-nuclear-smr-co-location-51", "primary_source_url": "https://aki1k.com/superintelligence/claim/meta-fair-nuclear-smr-co-location-51", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/meta-fair-nuclear-smr-co-location-51.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "model:microsoft-ai-codebase-auto-repair-52", "slug": "microsoft-ai-codebase-auto-repair-52", "type": "model", "name": "Microsoft AI Codebase Auto-Repair Vector #52", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Microsoft AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 82.3% generalization drop observed in unguided deployment.", "generalization_drop": 82.3, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-24", "source_url": "https://aki1k.com/superintelligence/model/microsoft-ai-codebase-auto-repair-52", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 29.6, "metr_ci_low": 14.8, "metr_ci_high": 94.7, "metr_median_end2026": 10.4, "rsi_level": 3, "rsi_exam_score": 91.9, "terminal_bench_score": 92.7, "reality_gap_pct": 82.3, "evidence_confidence": "independent", "sha256": "sha256_52_51_sig", "ipfs_cid": "bafybei_superintelligence_52_cid", "canonical_url": "https://aki1k.com/superintelligence/model/microsoft-ai-codebase-auto-repair-52", "primary_source_url": "https://aki1k.com/superintelligence/model/microsoft-ai-codebase-auto-repair-52", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/microsoft-ai-codebase-auto-repair-52.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "lab:nvidia-research-agent-collective-protocol-53", "slug": "nvidia-research-agent-collective-protocol-53", "type": "lab", "name": "NVIDIA Research Agent Collective Protocol Vector #53", "claim_scope": "RSI", "definition": "Frontier exploration into agent collective protocol within NVIDIA Research infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 14.6% generalization drop observed in unguided deployment.", "generalization_drop": 14.6, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-25", "source_url": "https://aki1k.com/superintelligence/lab/nvidia-research-agent-collective-protocol-53", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 93.8, "terminal_bench_score": 72.4, "reality_gap_pct": 14.6, "evidence_confidence": "observed", "sha256": "sha256_53_52_sig", "ipfs_cid": "bafybei_superintelligence_53_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/nvidia-research-agent-collective-protocol-53", "primary_source_url": "https://aki1k.com/superintelligence/lab/nvidia-research-agent-collective-protocol-53", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/nvidia-research-agent-collective-protocol-53.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "evaluation:mistral-ai-self-replicating-test-suites-54", "slug": "mistral-ai-self-replicating-test-suites-54", "type": "evaluation", "name": "Mistral AI Self-Replicating Test Suites Vector #54", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into self-replicating test suites within Mistral AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 21.9% generalization drop observed in unguided deployment.", "generalization_drop": 21.9, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-26", "source_url": "https://aki1k.com/superintelligence/evaluation/mistral-ai-self-replicating-test-suites-54", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 33.8, "metr_ci_low": 16.9, "metr_ci_high": 108.2, "metr_median_end2026": 11.8, "rsi_level": 1, "rsi_exam_score": 70.7, "terminal_bench_score": 74.1, "reality_gap_pct": 21.9, "evidence_confidence": "self-reported", "sha256": "sha256_54_53_sig", "ipfs_cid": "bafybei_superintelligence_54_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/mistral-ai-self-replicating-test-suites-54", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/mistral-ai-self-replicating-test-suites-54", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/mistral-ai-self-replicating-test-suites-54.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "compute:tsinghua-air-autonomous-synthesis-55", "slug": "tsinghua-air-autonomous-synthesis-55", "type": "compute", "name": "Tsinghua AIR Autonomous Synthesis Vector #55", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into autonomous synthesis within Tsinghua AIR infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 29.2% generalization drop observed in unguided deployment.", "generalization_drop": 29.2, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-27", "source_url": "https://aki1k.com/superintelligence/compute/tsinghua-air-autonomous-synthesis-55", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 407, "gw_total": 1.63, "accelerator_count": 508750, "grid_queue_months": 24, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 72.6, "terminal_bench_score": 75.8, "reality_gap_pct": 29.2, "evidence_confidence": "estimated", "sha256": "sha256_55_54_sig", "ipfs_cid": "bafybei_superintelligence_55_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/tsinghua-air-autonomous-synthesis-55", "primary_source_url": "https://aki1k.com/superintelligence/compute/tsinghua-air-autonomous-synthesis-55", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/tsinghua-air-autonomous-synthesis-55.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "research:shanghai-ai-lab-liquid-cooling-1mw-rack-56", "slug": "shanghai-ai-lab-liquid-cooling-1mw-rack-56", "type": "research", "name": "Shanghai AI Lab Liquid Cooling 1MW/Rack Vector #56", "claim_scope": "AGI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Shanghai AI Lab infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 36.5% generalization drop observed in unguided deployment.", "generalization_drop": 36.5, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-28", "source_url": "https://aki1k.com/superintelligence/research/shanghai-ai-lab-liquid-cooling-1mw-rack-56", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 74.5, "terminal_bench_score": 77.5, "reality_gap_pct": 36.5, "evidence_confidence": "independent", "sha256": "sha256_56_55_sig", "ipfs_cid": "bafybei_superintelligence_56_cid", "canonical_url": "https://aki1k.com/superintelligence/research/shanghai-ai-lab-liquid-cooling-1mw-rack-56", "primary_source_url": "https://aki1k.com/superintelligence/research/shanghai-ai-lab-liquid-cooling-1mw-rack-56", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/shanghai-ai-lab-liquid-cooling-1mw-rack-56.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "governance:alibaba-cloud-ai-nuclear-smr-co-location-57", "slug": "alibaba-cloud-ai-nuclear-smr-co-location-57", "type": "governance", "name": "Alibaba Cloud AI Nuclear SMR Co-Location Vector #57", "claim_scope": "ASI", "definition": "Frontier exploration into nuclear smr co-location within Alibaba Cloud AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 43.8% generalization drop observed in unguided deployment.", "generalization_drop": 43.8, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-01", "source_url": "https://aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-57", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 76.4, "terminal_bench_score": 79.2, "reality_gap_pct": 43.8, "evidence_confidence": "observed", "sha256": "sha256_57_56_sig", "ipfs_cid": "bafybei_superintelligence_57_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-57", "primary_source_url": "https://aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-57", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-57.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "emerging:01-ai-codebase-auto-repair-58", "slug": "01-ai-codebase-auto-repair-58", "type": "emerging", "name": "01.AI Codebase Auto-Repair Vector #58", "claim_scope": "RSI", "definition": "Frontier exploration into codebase auto-repair within 01.AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 51.1% generalization drop observed in unguided deployment.", "generalization_drop": 51.1, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-02", "source_url": "https://aki1k.com/superintelligence/emerging/01-ai-codebase-auto-repair-58", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 78.3, "terminal_bench_score": 80.9, "reality_gap_pct": 51.1, "evidence_confidence": "self-reported", "sha256": "sha256_58_57_sig", "ipfs_cid": "bafybei_superintelligence_58_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/01-ai-codebase-auto-repair-58", "primary_source_url": "https://aki1k.com/superintelligence/emerging/01-ai-codebase-auto-repair-58", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/01-ai-codebase-auto-repair-58.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "infrastructure:reka-ai-agent-collective-protocol-59", "slug": "reka-ai-agent-collective-protocol-59", "type": "infrastructure", "name": "Reka AI Agent Collective Protocol Vector #59", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into agent collective protocol within Reka AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 58.4% generalization drop observed in unguided deployment.", "generalization_drop": 58.4, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-03", "source_url": "https://aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-59", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 469, "gw_total": 1.88, "accelerator_count": 586250, "grid_queue_months": 28, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 80.2, "terminal_bench_score": 82.6, "reality_gap_pct": 58.4, "evidence_confidence": "estimated", "sha256": "sha256_59_58_sig", "ipfs_cid": "bafybei_superintelligence_59_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-59", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-59", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-59.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "organization:cohere-self-replicating-test-suites-60", "slug": "cohere-self-replicating-test-suites-60", "type": "organization", "name": "Cohere Self-Replicating Test Suites Vector #60", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into self-replicating test suites within Cohere infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Self-Replicating Test Suites. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 17.9% generalization drop observed in unguided deployment.", "generalization_drop": 17.9, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-18", "source_url": "https://aki1k.com/superintelligence/evaluation/meta-fair-liquid-cooling-1mw-rack-74", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 35.8, "metr_ci_low": 17.9, "metr_ci_high": 114.6, "metr_median_end2026": 12.5, "rsi_level": 1, "rsi_exam_score": 83.7, "terminal_bench_score": 86.1, "reality_gap_pct": 17.9, "evidence_confidence": "self-reported", "sha256": "sha256_74_73_sig", "ipfs_cid": "bafybei_superintelligence_74_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/meta-fair-liquid-cooling-1mw-rack-74", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/meta-fair-liquid-cooling-1mw-rack-74", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/meta-fair-liquid-cooling-1mw-rack-74.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "compute:microsoft-ai-nuclear-smr-co-location-75", "slug": "microsoft-ai-nuclear-smr-co-location-75", "type": "compute", "name": "Microsoft AI Nuclear SMR Co-Location Vector #75", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Microsoft AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 25.2% generalization drop observed in unguided deployment.", "generalization_drop": 25.2, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-19", "source_url": "https://aki1k.com/superintelligence/compute/microsoft-ai-nuclear-smr-co-location-75", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 267, "gw_total": 1.07, "accelerator_count": 333750, "grid_queue_months": 8, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 85.6, "terminal_bench_score": 87.8, "reality_gap_pct": 25.2, "evidence_confidence": "estimated", "sha256": "sha256_75_74_sig", "ipfs_cid": "bafybei_superintelligence_75_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/microsoft-ai-nuclear-smr-co-location-75", "primary_source_url": "https://aki1k.com/superintelligence/compute/microsoft-ai-nuclear-smr-co-location-75", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/microsoft-ai-nuclear-smr-co-location-75.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "research:nvidia-research-codebase-auto-repair-76", "slug": "nvidia-research-codebase-auto-repair-76", "type": "research", "name": "NVIDIA Research Codebase Auto-Repair Vector #76", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within NVIDIA Research infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 32.5% generalization drop observed in unguided deployment.", "generalization_drop": 32.5, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-76", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 87.5, "terminal_bench_score": 89.5, "reality_gap_pct": 32.5, "evidence_confidence": "independent", "sha256": "sha256_76_75_sig", "ipfs_cid": "bafybei_superintelligence_76_cid", "canonical_url": "https://aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-76", "primary_source_url": "https://aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-76", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-76.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "governance:mistral-ai-agent-collective-protocol-77", "slug": "mistral-ai-agent-collective-protocol-77", "type": "governance", "name": "Mistral AI Agent Collective Protocol Vector #77", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within Mistral AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 39.8% generalization drop observed in unguided deployment.", "generalization_drop": 39.8, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-77", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 89.4, "terminal_bench_score": 91.2, "reality_gap_pct": 39.8, "evidence_confidence": "observed", "sha256": "sha256_77_76_sig", "ipfs_cid": "bafybei_superintelligence_77_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-77", "primary_source_url": "https://aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-77", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-77.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "emerging:tsinghua-air-self-replicating-test-suites-78", "slug": "tsinghua-air-self-replicating-test-suites-78", "type": "emerging", "name": "Tsinghua AIR Self-Replicating Test Suites Vector #78", "claim_scope": "RSI", "definition": "Frontier exploration into self-replicating test suites within Tsinghua AIR infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 47.1% generalization drop observed in unguided deployment.", "generalization_drop": 47.1, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/emerging/tsinghua-air-self-replicating-test-suites-78", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 91.3, "terminal_bench_score": 92.9, "reality_gap_pct": 47.1, "evidence_confidence": "self-reported", "sha256": "sha256_78_77_sig", "ipfs_cid": "bafybei_superintelligence_78_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/tsinghua-air-self-replicating-test-suites-78", "primary_source_url": "https://aki1k.com/superintelligence/emerging/tsinghua-air-self-replicating-test-suites-78", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/tsinghua-air-self-replicating-test-suites-78.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "infrastructure:shanghai-ai-lab-autonomous-synthesis-79", "slug": "shanghai-ai-lab-autonomous-synthesis-79", "type": "infrastructure", "name": "Shanghai AI Lab Autonomous Synthesis Vector #79", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into autonomous synthesis within Shanghai AI Lab infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 54.4% generalization drop observed in unguided deployment.", "generalization_drop": 54.4, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-23", "source_url": "https://aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-autonomous-synthesis-79", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 329, "gw_total": 1.32, "accelerator_count": 411250, "grid_queue_months": 12, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 93.2, "terminal_bench_score": 72.6, "reality_gap_pct": 54.4, "evidence_confidence": "estimated", "sha256": "sha256_79_78_sig", "ipfs_cid": "bafybei_superintelligence_79_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-autonomous-synthesis-79", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-autonomous-synthesis-79", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-autonomous-synthesis-79.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "organization:alibaba-cloud-ai-liquid-cooling-1mw-rack-80", "slug": "alibaba-cloud-ai-liquid-cooling-1mw-rack-80", "type": "organization", "name": "Alibaba Cloud AI Liquid Cooling 1MW/Rack Vector #80", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into liquid cooling 1mw/rack within Alibaba Cloud AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 61.7% generalization drop observed in unguided deployment.", "generalization_drop": 61.7, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-24", "source_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-80", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 70.1, "terminal_bench_score": 74.3, "reality_gap_pct": 61.7, "evidence_confidence": "independent", "sha256": "sha256_80_79_sig", "ipfs_cid": "bafybei_superintelligence_80_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-80", "primary_source_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-80", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-80.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "claim:01-ai-nuclear-smr-co-location-81", "slug": "01-ai-nuclear-smr-co-location-81", "type": "claim", "name": "01.AI Nuclear SMR Co-Location Vector #81", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within 01.AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 69% generalization drop observed in unguided deployment.", "generalization_drop": 69, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-25", "source_url": "https://aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-81", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 72, "terminal_bench_score": 76, "reality_gap_pct": 69, "evidence_confidence": "observed", "sha256": "sha256_81_80_sig", "ipfs_cid": "bafybei_superintelligence_81_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-81", "primary_source_url": "https://aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-81", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-81.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "model:reka-ai-codebase-auto-repair-82", "slug": "reka-ai-codebase-auto-repair-82", "type": "model", "name": "Reka AI Codebase Auto-Repair Vector #82", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Reka AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 76.3% generalization drop observed in unguided deployment.", "generalization_drop": 76.3, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-26", "source_url": "https://aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-82", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 12.6, "metr_ci_low": 6.3, "metr_ci_high": 40.3, "metr_median_end2026": 4.4, "rsi_level": 1, "rsi_exam_score": 73.9, "terminal_bench_score": 77.7, "reality_gap_pct": 76.3, "evidence_confidence": "self-reported", "sha256": "sha256_82_81_sig", "ipfs_cid": "bafybei_superintelligence_82_cid", "canonical_url": "https://aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-82", "primary_source_url": "https://aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-82", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-82.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "lab:cohere-agent-collective-protocol-83", "slug": "cohere-agent-collective-protocol-83", "type": "lab", "name": "Cohere Agent Collective Protocol Vector #83", "claim_scope": "RSI", "definition": "Frontier exploration into agent collective protocol within Cohere infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 83.6% generalization drop observed in unguided deployment.", "generalization_drop": 83.6, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-27", "source_url": "https://aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-83", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 75.8, "terminal_bench_score": 79.4, "reality_gap_pct": 83.6, "evidence_confidence": "estimated", "sha256": "sha256_83_82_sig", "ipfs_cid": "bafybei_superintelligence_83_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-83", "primary_source_url": "https://aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-83", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-83.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "evaluation:scale-ai-self-replicating-test-suites-84", "slug": "scale-ai-self-replicating-test-suites-84", "type": "evaluation", "name": "Scale AI Self-Replicating Test Suites Vector #84", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into self-replicating test suites within Scale AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 15.9% generalization drop observed in unguided deployment.", "generalization_drop": 15.9, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-28", "source_url": "https://aki1k.com/superintelligence/evaluation/scale-ai-self-replicating-test-suites-84", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 16.8, "metr_ci_low": 8.4, "metr_ci_high": 53.8, "metr_median_end2026": 5.9, "rsi_level": 3, "rsi_exam_score": 77.7, "terminal_bench_score": 81.1, "reality_gap_pct": 15.9, "evidence_confidence": "independent", "sha256": "sha256_84_83_sig", "ipfs_cid": "bafybei_superintelligence_84_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/scale-ai-self-replicating-test-suites-84", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/scale-ai-self-replicating-test-suites-84", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/scale-ai-self-replicating-test-suites-84.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "compute:metr-autonomous-synthesis-85", "slug": "metr-autonomous-synthesis-85", "type": "compute", "name": "METR Autonomous Synthesis Vector #85", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into autonomous synthesis within METR infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Autonomous Synthesis. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 67% generalization drop observed in unguided deployment.", "generalization_drop": 67, "real_world_outcome": "Empirical deployment verified across Tokyo University AI target workload clusters.", "claim_date": "2026-08-07", "source_url": "https://aki1k.com/superintelligence/claim/tokyo-university-ai-autonomous-synthesis-91", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 91, "terminal_bench_score": 93, "reality_gap_pct": 67, "evidence_confidence": "estimated", "sha256": "sha256_91_90_sig", "ipfs_cid": "bafybei_superintelligence_91_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/tokyo-university-ai-autonomous-synthesis-91", "primary_source_url": "https://aki1k.com/superintelligence/claim/tokyo-university-ai-autonomous-synthesis-91", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/tokyo-university-ai-autonomous-synthesis-91.json", "notes": "Audited benchmark telemetry for Tokyo University AI research team." }, { "id": "model:cern-quantum-ai-liquid-cooling-1mw-rack-92", "slug": "cern-quantum-ai-liquid-cooling-1mw-rack-92", "type": "model", "name": "CERN Quantum AI Liquid Cooling 1MW/Rack Vector #92", "claim_scope": "ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within CERN Quantum AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for CERN Quantum AI Liquid Cooling 1MW/Rack. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 81.6% generalization drop observed in unguided deployment.", "generalization_drop": 81.6, "real_world_outcome": "Empirical deployment verified across OpenAI target workload clusters.", "claim_date": "2026-08-09", "source_url": "https://aki1k.com/superintelligence/lab/openai-nuclear-smr-co-location-93", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 94.8, "terminal_bench_score": 74.4, "reality_gap_pct": 81.6, "evidence_confidence": "observed", "sha256": "sha256_93_92_sig", "ipfs_cid": "bafybei_superintelligence_93_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/openai-nuclear-smr-co-location-93", "primary_source_url": "https://aki1k.com/superintelligence/lab/openai-nuclear-smr-co-location-93", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/openai-nuclear-smr-co-location-93.json", "notes": "Audited benchmark telemetry for OpenAI research team." }, { "id": "evaluation:anthropic-codebase-auto-repair-94", "slug": "anthropic-codebase-auto-repair-94", "type": "evaluation", "name": "Anthropic Codebase Auto-Repair Vector #94", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into codebase auto-repair within Anthropic infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Anthropic Codebase Auto-Repair. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 50.4% generalization drop observed in unguided deployment.", "generalization_drop": 50.4, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/infrastructure/nvidia-research-nuclear-smr-co-location-99", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 189, "gw_total": 0.76, "accelerator_count": 236250, "grid_queue_months": 32, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 81.2, "terminal_bench_score": 84.6, "reality_gap_pct": 50.4, "evidence_confidence": "estimated", "sha256": "sha256_99_98_sig", "ipfs_cid": "bafybei_superintelligence_99_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/nvidia-research-nuclear-smr-co-location-99", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/nvidia-research-nuclear-smr-co-location-99", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/nvidia-research-nuclear-smr-co-location-99.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "organization:mistral-ai-codebase-auto-repair-100", "slug": "mistral-ai-codebase-auto-repair-100", "type": "organization", "name": "Mistral AI Codebase Auto-Repair Vector #100", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into codebase auto-repair within Mistral AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 57.7% generalization drop observed in unguided deployment.", "generalization_drop": 57.7, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-16", "source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-100", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 83.1, "terminal_bench_score": 86.3, "reality_gap_pct": 57.7, "evidence_confidence": "independent", "sha256": "sha256_100_99_sig", "ipfs_cid": "bafybei_superintelligence_100_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-100", "primary_source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-100", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-100.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "claim:tsinghua-air-agent-collective-protocol-101", "slug": "tsinghua-air-agent-collective-protocol-101", "type": "claim", "name": "Tsinghua AIR Agent Collective Protocol Vector #101", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Tsinghua AIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 79.6% generalization drop observed in unguided deployment.", "generalization_drop": 79.6, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-19", "source_url": "https://aki1k.com/superintelligence/lab/alibaba-cloud-ai-autonomous-synthesis-103", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 88.8, "terminal_bench_score": 91.4, "reality_gap_pct": 79.6, "evidence_confidence": "estimated", "sha256": "sha256_103_102_sig", "ipfs_cid": "bafybei_superintelligence_103_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/alibaba-cloud-ai-autonomous-synthesis-103", "primary_source_url": "https://aki1k.com/superintelligence/lab/alibaba-cloud-ai-autonomous-synthesis-103", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/alibaba-cloud-ai-autonomous-synthesis-103.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "evaluation:01-ai-liquid-cooling-1mw-rack-104", "slug": "01-ai-liquid-cooling-1mw-rack-104", "type": "evaluation", "name": "01.AI Liquid Cooling 1MW/Rack Vector #104", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within 01.AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 11.9% generalization drop observed in unguided deployment.", "generalization_drop": 11.9, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-104", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 18.8, "metr_ci_low": 9.4, "metr_ci_high": 60.2, "metr_median_end2026": 6.6, "rsi_level": 3, "rsi_exam_score": 90.7, "terminal_bench_score": 93.1, "reality_gap_pct": 11.9, "evidence_confidence": "independent", "sha256": "sha256_104_103_sig", "ipfs_cid": "bafybei_superintelligence_104_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-104", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-104", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-104.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "compute:reka-ai-nuclear-smr-co-location-105", "slug": "reka-ai-nuclear-smr-co-location-105", "type": "compute", "name": "Reka AI Nuclear SMR Co-Location Vector #105", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Reka AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 19.2% generalization drop observed in unguided deployment.", "generalization_drop": 19.2, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-105", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 282, "gw_total": 1.13, "accelerator_count": 352500, "grid_queue_months": 38, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 92.6, "terminal_bench_score": 72.8, "reality_gap_pct": 19.2, "evidence_confidence": "observed", "sha256": "sha256_105_104_sig", "ipfs_cid": "bafybei_superintelligence_105_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-105", "primary_source_url": "https://aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-105", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-105.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "research:cohere-codebase-auto-repair-106", "slug": "cohere-codebase-auto-repair-106", "type": "research", "name": "Cohere Codebase Auto-Repair Vector #106", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within Cohere infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 26.5% generalization drop observed in unguided deployment.", "generalization_drop": 26.5, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/research/cohere-codebase-auto-repair-106", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 94.5, "terminal_bench_score": 74.5, "reality_gap_pct": 26.5, "evidence_confidence": "self-reported", "sha256": "sha256_106_105_sig", "ipfs_cid": "bafybei_superintelligence_106_cid", "canonical_url": "https://aki1k.com/superintelligence/research/cohere-codebase-auto-repair-106", "primary_source_url": "https://aki1k.com/superintelligence/research/cohere-codebase-auto-repair-106", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/cohere-codebase-auto-repair-106.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "governance:scale-ai-agent-collective-protocol-107", "slug": "scale-ai-agent-collective-protocol-107", "type": "governance", "name": "Scale AI Agent Collective Protocol Vector #107", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within Scale AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 51.7% generalization drop observed in unguided deployment.", "generalization_drop": 51.7, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-18", "source_url": "https://aki1k.com/superintelligence/organization/scale-ai-codebase-auto-repair-130", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 90.1, "terminal_bench_score": 93.3, "reality_gap_pct": 51.7, "evidence_confidence": "self-reported", "sha256": "sha256_130_129_sig", "ipfs_cid": "bafybei_superintelligence_130_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/scale-ai-codebase-auto-repair-130", "primary_source_url": "https://aki1k.com/superintelligence/organization/scale-ai-codebase-auto-repair-130", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/scale-ai-codebase-auto-repair-130.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "claim:metr-agent-collective-protocol-131", "slug": "metr-agent-collective-protocol-131", "type": "claim", "name": "METR Agent Collective Protocol Vector #131", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within METR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 62.3% generalization drop observed in unguided deployment.", "generalization_drop": 62.3, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-12", "source_url": "https://aki1k.com/superintelligence/model/cohere-liquid-cooling-1mw-rack-152", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 39.6, "metr_ci_low": 19.8, "metr_ci_high": 126.7, "metr_median_end2026": 13.9, "rsi_level": 3, "rsi_exam_score": 81.9, "terminal_bench_score": 86.7, "reality_gap_pct": 62.3, "evidence_confidence": "independent", "sha256": "sha256_152_151_sig", "ipfs_cid": "bafybei_superintelligence_152_cid", "canonical_url": "https://aki1k.com/superintelligence/model/cohere-liquid-cooling-1mw-rack-152", "primary_source_url": "https://aki1k.com/superintelligence/model/cohere-liquid-cooling-1mw-rack-152", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/cohere-liquid-cooling-1mw-rack-152.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "lab:scale-ai-nuclear-smr-co-location-153", "slug": "scale-ai-nuclear-smr-co-location-153", "type": "lab", "name": "Scale AI Nuclear SMR Co-Location Vector #153", "claim_scope": "RSI", "definition": "Frontier exploration into nuclear smr co-location within Scale AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 69.6% generalization drop observed in unguided deployment.", "generalization_drop": 69.6, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-13", "source_url": "https://aki1k.com/superintelligence/lab/scale-ai-nuclear-smr-co-location-153", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 83.8, "terminal_bench_score": 88.4, "reality_gap_pct": 69.6, "evidence_confidence": "observed", "sha256": "sha256_153_152_sig", "ipfs_cid": "bafybei_superintelligence_153_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/scale-ai-nuclear-smr-co-location-153", "primary_source_url": "https://aki1k.com/superintelligence/lab/scale-ai-nuclear-smr-co-location-153", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/scale-ai-nuclear-smr-co-location-153.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "evaluation:metr-codebase-auto-repair-154", "slug": "metr-codebase-auto-repair-154", "type": "evaluation", "name": "METR Codebase Auto-Repair Vector #154", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into codebase auto-repair within METR infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 76.9% generalization drop observed in unguided deployment.", "generalization_drop": 76.9, "real_world_outcome": "Empirical deployment verified across METR target workload clusters.", "claim_date": "2026-08-14", "source_url": "https://aki1k.com/superintelligence/evaluation/metr-codebase-auto-repair-154", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 3.8, "metr_ci_low": 1.9, "metr_ci_high": 12.2, "metr_median_end2026": 1.3, "rsi_level": 1, "rsi_exam_score": 85.7, "terminal_bench_score": 90.1, "reality_gap_pct": 76.9, "evidence_confidence": "self-reported", "sha256": "sha256_154_153_sig", "ipfs_cid": "bafybei_superintelligence_154_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/metr-codebase-auto-repair-154", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/metr-codebase-auto-repair-154", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/metr-codebase-auto-repair-154.json", "notes": "Audited benchmark telemetry for METR research team." }, { "id": "compute:epoch-ai-agent-collective-protocol-155", "slug": "epoch-ai-agent-collective-protocol-155", "type": "compute", "name": "Epoch AI Agent Collective Protocol Vector #155", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into agent collective protocol within Epoch AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Epoch AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 82.2% generalization drop observed in unguided deployment.", "generalization_drop": 82.2, "real_world_outcome": "Empirical deployment verified across xAI target workload clusters.", "claim_date": "2026-08-25", "source_url": "https://aki1k.com/superintelligence/compute/xai-nuclear-smr-co-location-165", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 312, "gw_total": 1.25, "accelerator_count": 390000, "grid_queue_months": 26, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 81.6, "terminal_bench_score": 86.8, "reality_gap_pct": 82.2, "evidence_confidence": "observed", "sha256": "sha256_165_164_sig", "ipfs_cid": "bafybei_superintelligence_165_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/xai-nuclear-smr-co-location-165", "primary_source_url": "https://aki1k.com/superintelligence/compute/xai-nuclear-smr-co-location-165", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/xai-nuclear-smr-co-location-165.json", "notes": "Audited benchmark telemetry for xAI research team." }, { "id": "research:meta-fair-codebase-auto-repair-166", "slug": "meta-fair-codebase-auto-repair-166", "type": "research", "name": "Meta FAIR Codebase Auto-Repair Vector #166", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within Meta FAIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Meta FAIR Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 14.5% generalization drop observed in unguided deployment.", "generalization_drop": 14.5, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-26", "source_url": "https://aki1k.com/superintelligence/research/meta-fair-codebase-auto-repair-166", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 83.5, "terminal_bench_score": 88.5, "reality_gap_pct": 14.5, "evidence_confidence": "self-reported", "sha256": "sha256_166_165_sig", "ipfs_cid": "bafybei_superintelligence_166_cid", "canonical_url": "https://aki1k.com/superintelligence/research/meta-fair-codebase-auto-repair-166", "primary_source_url": "https://aki1k.com/superintelligence/research/meta-fair-codebase-auto-repair-166", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/meta-fair-codebase-auto-repair-166.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "governance:microsoft-ai-agent-collective-protocol-167", "slug": "microsoft-ai-agent-collective-protocol-167", "type": "governance", "name": "Microsoft AI Agent Collective Protocol Vector #167", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within Microsoft AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 63.6% generalization drop observed in unguided deployment.", "generalization_drop": 63.6, "real_world_outcome": "Empirical deployment verified across Tokyo University AI target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/lab/tokyo-university-ai-nuclear-smr-co-location-183", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 90.8, "terminal_bench_score": 73.4, "reality_gap_pct": 63.6, "evidence_confidence": "estimated", "sha256": "sha256_183_182_sig", "ipfs_cid": "bafybei_superintelligence_183_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/tokyo-university-ai-nuclear-smr-co-location-183", "primary_source_url": "https://aki1k.com/superintelligence/lab/tokyo-university-ai-nuclear-smr-co-location-183", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/tokyo-university-ai-nuclear-smr-co-location-183.json", "notes": "Audited benchmark telemetry for Tokyo University AI research team." }, { "id": "evaluation:cern-quantum-ai-codebase-auto-repair-184", "slug": "cern-quantum-ai-codebase-auto-repair-184", "type": "evaluation", "name": "CERN Quantum AI Codebase Auto-Repair Vector #184", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into codebase auto-repair within CERN Quantum AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for CERN Quantum AI Codebase Auto-Repair. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 32.4% generalization drop observed in unguided deployment.", "generalization_drop": 32.4, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/infrastructure/meta-fair-nuclear-smr-co-location-189", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 234, "gw_total": 0.94, "accelerator_count": 292500, "grid_queue_months": 14, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 77.2, "terminal_bench_score": 83.6, "reality_gap_pct": 32.4, "evidence_confidence": "observed", "sha256": "sha256_189_188_sig", "ipfs_cid": "bafybei_superintelligence_189_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/meta-fair-nuclear-smr-co-location-189", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/meta-fair-nuclear-smr-co-location-189", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/meta-fair-nuclear-smr-co-location-189.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "organization:microsoft-ai-codebase-auto-repair-190", "slug": "microsoft-ai-codebase-auto-repair-190", "type": "organization", "name": "Microsoft AI Codebase Auto-Repair Vector #190", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into codebase auto-repair within Microsoft AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 39.7% generalization drop observed in unguided deployment.", "generalization_drop": 39.7, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/organization/microsoft-ai-codebase-auto-repair-190", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 79.1, "terminal_bench_score": 85.3, "reality_gap_pct": 39.7, "evidence_confidence": "self-reported", "sha256": "sha256_190_189_sig", "ipfs_cid": "bafybei_superintelligence_190_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/microsoft-ai-codebase-auto-repair-190", "primary_source_url": "https://aki1k.com/superintelligence/organization/microsoft-ai-codebase-auto-repair-190", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/microsoft-ai-codebase-auto-repair-190.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "claim:nvidia-research-agent-collective-protocol-191", "slug": "nvidia-research-agent-collective-protocol-191", "type": "claim", "name": "NVIDIA Research Agent Collective Protocol Vector #191", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within NVIDIA Research infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 47% generalization drop observed in unguided deployment.", "generalization_drop": 47, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-23", "source_url": "https://aki1k.com/superintelligence/claim/nvidia-research-agent-collective-protocol-191", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 81, "terminal_bench_score": 87, "reality_gap_pct": 47, "evidence_confidence": "estimated", "sha256": "sha256_191_190_sig", "ipfs_cid": "bafybei_superintelligence_191_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/nvidia-research-agent-collective-protocol-191", "primary_source_url": "https://aki1k.com/superintelligence/claim/nvidia-research-agent-collective-protocol-191", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/nvidia-research-agent-collective-protocol-191.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "model:mistral-ai-self-replicating-test-suites-192", "slug": "mistral-ai-self-replicating-test-suites-192", "type": "model", "name": "Mistral AI Self-Replicating Test Suites Vector #192", "claim_scope": "ASI", "definition": "Frontier exploration into self-replicating test suites within Mistral AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Self-Replicating Test Suites. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 43% generalization drop observed in unguided deployment.", "generalization_drop": 43, "real_world_outcome": "Empirical deployment verified across xAI target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/claim/xai-autonomous-synthesis-211", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 94, "terminal_bench_score": 77, "reality_gap_pct": 43, "evidence_confidence": "estimated", "sha256": "sha256_211_210_sig", "ipfs_cid": "bafybei_superintelligence_211_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/xai-autonomous-synthesis-211", "primary_source_url": "https://aki1k.com/superintelligence/claim/xai-autonomous-synthesis-211", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/xai-autonomous-synthesis-211.json", "notes": "Audited benchmark telemetry for xAI research team." }, { "id": "model:meta-fair-liquid-cooling-1mw-rack-212", "slug": "meta-fair-liquid-cooling-1mw-rack-212", "type": "model", "name": "Meta FAIR Liquid Cooling 1MW/Rack Vector #212", "claim_scope": "ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Meta FAIR infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Meta FAIR Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 50.3% generalization drop observed in unguided deployment.", "generalization_drop": 50.3, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-16", "source_url": "https://aki1k.com/superintelligence/model/meta-fair-liquid-cooling-1mw-rack-212", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 5.6, "metr_ci_low": 2.8, "metr_ci_high": 17.9, "metr_median_end2026": 2, "rsi_level": 3, "rsi_exam_score": 70.9, "terminal_bench_score": 78.7, "reality_gap_pct": 50.3, "evidence_confidence": "independent", "sha256": "sha256_212_211_sig", "ipfs_cid": "bafybei_superintelligence_212_cid", "canonical_url": "https://aki1k.com/superintelligence/model/meta-fair-liquid-cooling-1mw-rack-212", "primary_source_url": "https://aki1k.com/superintelligence/model/meta-fair-liquid-cooling-1mw-rack-212", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/meta-fair-liquid-cooling-1mw-rack-212.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "lab:microsoft-ai-nuclear-smr-co-location-213", "slug": "microsoft-ai-nuclear-smr-co-location-213", "type": "lab", "name": "Microsoft AI Nuclear SMR Co-Location Vector #213", "claim_scope": "RSI", "definition": "Frontier exploration into nuclear smr co-location within Microsoft AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 57.6% generalization drop observed in unguided deployment.", "generalization_drop": 57.6, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-17", "source_url": "https://aki1k.com/superintelligence/lab/microsoft-ai-nuclear-smr-co-location-213", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 72.8, "terminal_bench_score": 80.4, "reality_gap_pct": 57.6, "evidence_confidence": "observed", "sha256": "sha256_213_212_sig", "ipfs_cid": "bafybei_superintelligence_213_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/microsoft-ai-nuclear-smr-co-location-213", "primary_source_url": "https://aki1k.com/superintelligence/lab/microsoft-ai-nuclear-smr-co-location-213", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/microsoft-ai-nuclear-smr-co-location-213.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "evaluation:nvidia-research-codebase-auto-repair-214", "slug": "nvidia-research-codebase-auto-repair-214", "type": "evaluation", "name": "NVIDIA Research Codebase Auto-Repair Vector #214", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into codebase auto-repair within NVIDIA Research infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 64.9% generalization drop observed in unguided deployment.", "generalization_drop": 64.9, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-18", "source_url": "https://aki1k.com/superintelligence/evaluation/nvidia-research-codebase-auto-repair-214", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 9.8, "metr_ci_low": 4.9, "metr_ci_high": 31.4, "metr_median_end2026": 3.4, "rsi_level": 1, "rsi_exam_score": 74.7, "terminal_bench_score": 82.1, "reality_gap_pct": 64.9, "evidence_confidence": "self-reported", "sha256": "sha256_214_213_sig", "ipfs_cid": "bafybei_superintelligence_214_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/nvidia-research-codebase-auto-repair-214", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/nvidia-research-codebase-auto-repair-214", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/nvidia-research-codebase-auto-repair-214.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "compute:mistral-ai-agent-collective-protocol-215", "slug": "mistral-ai-agent-collective-protocol-215", "type": "compute", "name": "Mistral AI Agent Collective Protocol Vector #215", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into agent collective protocol within Mistral AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 72.2% generalization drop observed in unguided deployment.", "generalization_drop": 72.2, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-19", "source_url": "https://aki1k.com/superintelligence/compute/mistral-ai-agent-collective-protocol-215", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 187, "gw_total": 0.75, "accelerator_count": 233750, "grid_queue_months": 40, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 76.6, "terminal_bench_score": 83.8, "reality_gap_pct": 72.2, "evidence_confidence": "estimated", "sha256": "sha256_215_214_sig", "ipfs_cid": "bafybei_superintelligence_215_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/mistral-ai-agent-collective-protocol-215", "primary_source_url": "https://aki1k.com/superintelligence/compute/mistral-ai-agent-collective-protocol-215", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/mistral-ai-agent-collective-protocol-215.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "research:tsinghua-air-self-replicating-test-suites-216", "slug": "tsinghua-air-self-replicating-test-suites-216", "type": "research", "name": "Tsinghua AIR Self-Replicating Test Suites Vector #216", "claim_scope": "AGI", "definition": "Frontier exploration into self-replicating test suites within Tsinghua AIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Self-Replicating Test Suites. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 49.6% generalization drop observed in unguided deployment.", "generalization_drop": 49.6, "real_world_outcome": "Empirical deployment verified across CERN Quantum AI target workload clusters.", "claim_date": "2026-08-01", "source_url": "https://aki1k.com/superintelligence/lab/cern-quantum-ai-autonomous-synthesis-253", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 73.8, "terminal_bench_score": 82.4, "reality_gap_pct": 49.6, "evidence_confidence": "observed", "sha256": "sha256_253_252_sig", "ipfs_cid": "bafybei_superintelligence_253_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/cern-quantum-ai-autonomous-synthesis-253", "primary_source_url": "https://aki1k.com/superintelligence/lab/cern-quantum-ai-autonomous-synthesis-253", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/cern-quantum-ai-autonomous-synthesis-253.json", "notes": "Audited benchmark telemetry for CERN Quantum AI research team." }, { "id": "evaluation:openai-liquid-cooling-1mw-rack-254", "slug": "openai-liquid-cooling-1mw-rack-254", "type": "evaluation", "name": "OpenAI Liquid Cooling 1MW/Rack Vector #254", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within OpenAI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for OpenAI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 56.9% generalization drop observed in unguided deployment.", "generalization_drop": 56.9, "real_world_outcome": "Empirical deployment verified across OpenAI target workload clusters.", "claim_date": "2026-08-02", "source_url": "https://aki1k.com/superintelligence/evaluation/openai-liquid-cooling-1mw-rack-254", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 13.8, "metr_ci_low": 6.9, "metr_ci_high": 44.2, "metr_median_end2026": 4.8, "rsi_level": 1, "rsi_exam_score": 75.7, "terminal_bench_score": 84.1, "reality_gap_pct": 56.9, "evidence_confidence": "self-reported", "sha256": "sha256_254_253_sig", "ipfs_cid": "bafybei_superintelligence_254_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/openai-liquid-cooling-1mw-rack-254", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/openai-liquid-cooling-1mw-rack-254", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/openai-liquid-cooling-1mw-rack-254.json", "notes": "Audited benchmark telemetry for OpenAI research team." }, { "id": "compute:anthropic-nuclear-smr-co-location-255", "slug": "anthropic-nuclear-smr-co-location-255", "type": "compute", "name": "Anthropic Nuclear SMR Co-Location Vector #255", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Anthropic infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Anthropic Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 64.2% generalization drop observed in unguided deployment.", "generalization_drop": 64.2, "real_world_outcome": "Empirical deployment verified across Anthropic target workload clusters.", "claim_date": "2026-08-03", "source_url": "https://aki1k.com/superintelligence/compute/anthropic-nuclear-smr-co-location-255", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 357, "gw_total": 1.43, "accelerator_count": 446250, "grid_queue_months": 8, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 77.6, "terminal_bench_score": 85.8, "reality_gap_pct": 64.2, "evidence_confidence": "estimated", "sha256": "sha256_255_254_sig", "ipfs_cid": "bafybei_superintelligence_255_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/anthropic-nuclear-smr-co-location-255", "primary_source_url": "https://aki1k.com/superintelligence/compute/anthropic-nuclear-smr-co-location-255", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/anthropic-nuclear-smr-co-location-255.json", "notes": "Audited benchmark telemetry for Anthropic research team." }, { "id": "research:google-deepmind-codebase-auto-repair-256", "slug": "google-deepmind-codebase-auto-repair-256", "type": "research", "name": "Google DeepMind Codebase Auto-Repair Vector #256", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within Google DeepMind infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Google DeepMind Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 71.5% generalization drop observed in unguided deployment.", "generalization_drop": 71.5, "real_world_outcome": "Empirical deployment verified across Google DeepMind target workload clusters.", "claim_date": "2026-08-04", "source_url": "https://aki1k.com/superintelligence/research/google-deepmind-codebase-auto-repair-256", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 79.5, "terminal_bench_score": 87.5, "reality_gap_pct": 71.5, "evidence_confidence": "independent", "sha256": "sha256_256_255_sig", "ipfs_cid": "bafybei_superintelligence_256_cid", "canonical_url": "https://aki1k.com/superintelligence/research/google-deepmind-codebase-auto-repair-256", "primary_source_url": "https://aki1k.com/superintelligence/research/google-deepmind-codebase-auto-repair-256", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/google-deepmind-codebase-auto-repair-256.json", "notes": "Audited benchmark telemetry for Google DeepMind research team." }, { "id": "governance:xai-agent-collective-protocol-257", "slug": "xai-agent-collective-protocol-257", "type": "governance", "name": "xAI Agent Collective Protocol Vector #257", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within xAI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for xAI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 78.8% generalization drop observed in unguided deployment.", "generalization_drop": 78.8, "real_world_outcome": "Empirical deployment verified across xAI target workload clusters.", "claim_date": "2026-08-05", "source_url": "https://aki1k.com/superintelligence/governance/xai-agent-collective-protocol-257", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 81.4, "terminal_bench_score": 89.2, "reality_gap_pct": 78.8, "evidence_confidence": "observed", "sha256": "sha256_257_256_sig", "ipfs_cid": "bafybei_superintelligence_257_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/xai-agent-collective-protocol-257", "primary_source_url": "https://aki1k.com/superintelligence/governance/xai-agent-collective-protocol-257", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/xai-agent-collective-protocol-257.json", "notes": "Audited benchmark telemetry for xAI research team." }, { "id": "emerging:meta-fair-self-replicating-test-suites-258", "slug": "meta-fair-self-replicating-test-suites-258", "type": "emerging", "name": "Meta FAIR Self-Replicating Test Suites Vector #258", "claim_scope": "RSI", "definition": "Frontier exploration into self-replicating test suites within Meta FAIR infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Meta FAIR Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 11.1% generalization drop observed in unguided deployment.", "generalization_drop": 11.1, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-06", "source_url": "https://aki1k.com/superintelligence/emerging/meta-fair-self-replicating-test-suites-258", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 83.3, "terminal_bench_score": 90.9, "reality_gap_pct": 11.1, "evidence_confidence": "self-reported", "sha256": "sha256_258_257_sig", "ipfs_cid": "bafybei_superintelligence_258_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/meta-fair-self-replicating-test-suites-258", "primary_source_url": "https://aki1k.com/superintelligence/emerging/meta-fair-self-replicating-test-suites-258", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/meta-fair-self-replicating-test-suites-258.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "infrastructure:microsoft-ai-autonomous-synthesis-259", "slug": "microsoft-ai-autonomous-synthesis-259", "type": "infrastructure", "name": "Microsoft AI Autonomous Synthesis Vector #259", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into autonomous synthesis within Microsoft AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 18.4% generalization drop observed in unguided deployment.", "generalization_drop": 18.4, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-07", "source_url": "https://aki1k.com/superintelligence/infrastructure/microsoft-ai-autonomous-synthesis-259", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 419, "gw_total": 1.68, "accelerator_count": 523750, "grid_queue_months": 12, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 85.2, "terminal_bench_score": 92.6, "reality_gap_pct": 18.4, "evidence_confidence": "estimated", "sha256": "sha256_259_258_sig", "ipfs_cid": "bafybei_superintelligence_259_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/microsoft-ai-autonomous-synthesis-259", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/microsoft-ai-autonomous-synthesis-259", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/microsoft-ai-autonomous-synthesis-259.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "organization:nvidia-research-liquid-cooling-1mw-rack-260", "slug": "nvidia-research-liquid-cooling-1mw-rack-260", "type": "organization", "name": "NVIDIA Research Liquid Cooling 1MW/Rack Vector #260", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into liquid cooling 1mw/rack within NVIDIA Research infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 25.7% generalization drop observed in unguided deployment.", "generalization_drop": 25.7, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-08", "source_url": "https://aki1k.com/superintelligence/organization/nvidia-research-liquid-cooling-1mw-rack-260", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 87.1, "terminal_bench_score": 72.3, "reality_gap_pct": 25.7, "evidence_confidence": "independent", "sha256": "sha256_260_259_sig", "ipfs_cid": "bafybei_superintelligence_260_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/nvidia-research-liquid-cooling-1mw-rack-260", "primary_source_url": "https://aki1k.com/superintelligence/organization/nvidia-research-liquid-cooling-1mw-rack-260", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/nvidia-research-liquid-cooling-1mw-rack-260.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "claim:mistral-ai-nuclear-smr-co-location-261", "slug": "mistral-ai-nuclear-smr-co-location-261", "type": "claim", "name": "Mistral AI Nuclear SMR Co-Location Vector #261", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within Mistral AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 33% generalization drop observed in unguided deployment.", "generalization_drop": 33, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-09", "source_url": "https://aki1k.com/superintelligence/claim/mistral-ai-nuclear-smr-co-location-261", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 89, "terminal_bench_score": 74, "reality_gap_pct": 33, "evidence_confidence": "observed", "sha256": "sha256_261_260_sig", "ipfs_cid": "bafybei_superintelligence_261_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/mistral-ai-nuclear-smr-co-location-261", "primary_source_url": "https://aki1k.com/superintelligence/claim/mistral-ai-nuclear-smr-co-location-261", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/mistral-ai-nuclear-smr-co-location-261.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "model:tsinghua-air-codebase-auto-repair-262", "slug": "tsinghua-air-codebase-auto-repair-262", "type": "model", "name": "Tsinghua AIR Codebase Auto-Repair Vector #262", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Tsinghua AIR infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 40.3% generalization drop observed in unguided deployment.", "generalization_drop": 40.3, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-10", "source_url": "https://aki1k.com/superintelligence/model/tsinghua-air-codebase-auto-repair-262", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 30.6, "metr_ci_low": 15.3, "metr_ci_high": 97.9, "metr_median_end2026": 10.7, "rsi_level": 1, "rsi_exam_score": 90.9, "terminal_bench_score": 75.7, "reality_gap_pct": 40.3, "evidence_confidence": "self-reported", "sha256": "sha256_262_261_sig", "ipfs_cid": "bafybei_superintelligence_262_cid", "canonical_url": "https://aki1k.com/superintelligence/model/tsinghua-air-codebase-auto-repair-262", "primary_source_url": "https://aki1k.com/superintelligence/model/tsinghua-air-codebase-auto-repair-262", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/tsinghua-air-codebase-auto-repair-262.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "lab:shanghai-ai-lab-agent-collective-protocol-263", "slug": "shanghai-ai-lab-agent-collective-protocol-263", "type": "lab", "name": "Shanghai AI Lab Agent Collective Protocol Vector #263", "claim_scope": "RSI", "definition": "Frontier exploration into agent collective protocol within Shanghai AI Lab infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 61.5% generalization drop observed in unguided deployment.", "generalization_drop": 61.5, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-26", "source_url": "https://aki1k.com/superintelligence/research/nvidia-research-self-replicating-test-suites-306", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 74.5, "terminal_bench_score": 84.5, "reality_gap_pct": 61.5, "evidence_confidence": "self-reported", "sha256": "sha256_306_305_sig", "ipfs_cid": "bafybei_superintelligence_306_cid", "canonical_url": "https://aki1k.com/superintelligence/research/nvidia-research-self-replicating-test-suites-306", "primary_source_url": "https://aki1k.com/superintelligence/research/nvidia-research-self-replicating-test-suites-306", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/nvidia-research-self-replicating-test-suites-306.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "governance:mistral-ai-autonomous-synthesis-307", "slug": "mistral-ai-autonomous-synthesis-307", "type": "governance", "name": "Mistral AI Autonomous Synthesis Vector #307", "claim_scope": "ASI", "definition": "Frontier exploration into autonomous synthesis within Mistral AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 68.8% generalization drop observed in unguided deployment.", "generalization_drop": 68.8, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-27", "source_url": "https://aki1k.com/superintelligence/governance/mistral-ai-autonomous-synthesis-307", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 76.4, "terminal_bench_score": 86.2, "reality_gap_pct": 68.8, "evidence_confidence": "estimated", "sha256": "sha256_307_306_sig", "ipfs_cid": "bafybei_superintelligence_307_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/mistral-ai-autonomous-synthesis-307", "primary_source_url": "https://aki1k.com/superintelligence/governance/mistral-ai-autonomous-synthesis-307", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/mistral-ai-autonomous-synthesis-307.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "emerging:tsinghua-air-liquid-cooling-1mw-rack-308", "slug": "tsinghua-air-liquid-cooling-1mw-rack-308", "type": "emerging", "name": "Tsinghua AIR Liquid Cooling 1MW/Rack Vector #308", "claim_scope": "RSI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Tsinghua AIR infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 76.1% generalization drop observed in unguided deployment.", "generalization_drop": 76.1, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-28", "source_url": "https://aki1k.com/superintelligence/emerging/tsinghua-air-liquid-cooling-1mw-rack-308", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 78.3, "terminal_bench_score": 87.9, "reality_gap_pct": 76.1, "evidence_confidence": "independent", "sha256": "sha256_308_307_sig", "ipfs_cid": "bafybei_superintelligence_308_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/tsinghua-air-liquid-cooling-1mw-rack-308", "primary_source_url": "https://aki1k.com/superintelligence/emerging/tsinghua-air-liquid-cooling-1mw-rack-308", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/tsinghua-air-liquid-cooling-1mw-rack-308.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "infrastructure:shanghai-ai-lab-nuclear-smr-co-location-309", "slug": "shanghai-ai-lab-nuclear-smr-co-location-309", "type": "infrastructure", "name": "Shanghai AI Lab Nuclear SMR Co-Location Vector #309", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into nuclear smr co-location within Shanghai AI Lab infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 83.4% generalization drop observed in unguided deployment.", "generalization_drop": 83.4, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-01", "source_url": "https://aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-nuclear-smr-co-location-309", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 294, "gw_total": 1.18, "accelerator_count": 367500, "grid_queue_months": 26, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 80.2, "terminal_bench_score": 89.6, "reality_gap_pct": 83.4, "evidence_confidence": "observed", "sha256": "sha256_309_308_sig", "ipfs_cid": "bafybei_superintelligence_309_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-nuclear-smr-co-location-309", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-nuclear-smr-co-location-309", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/shanghai-ai-lab-nuclear-smr-co-location-309.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "organization:alibaba-cloud-ai-codebase-auto-repair-310", "slug": "alibaba-cloud-ai-codebase-auto-repair-310", "type": "organization", "name": "Alibaba Cloud AI Codebase Auto-Repair Vector #310", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into codebase auto-repair within Alibaba Cloud AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 15.7% generalization drop observed in unguided deployment.", "generalization_drop": 15.7, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-02", "source_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-codebase-auto-repair-310", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 82.1, "terminal_bench_score": 91.3, "reality_gap_pct": 15.7, "evidence_confidence": "self-reported", "sha256": "sha256_310_309_sig", "ipfs_cid": "bafybei_superintelligence_310_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-codebase-auto-repair-310", "primary_source_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-codebase-auto-repair-310", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/alibaba-cloud-ai-codebase-auto-repair-310.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "claim:01-ai-agent-collective-protocol-311", "slug": "01-ai-agent-collective-protocol-311", "type": "claim", "name": "01.AI Agent Collective Protocol Vector #311", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within 01.AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 11.7% generalization drop observed in unguided deployment.", "generalization_drop": 11.7, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-self-replicating-test-suites-330", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 70.1, "terminal_bench_score": 81.3, "reality_gap_pct": 11.7, "evidence_confidence": "self-reported", "sha256": "sha256_330_329_sig", "ipfs_cid": "bafybei_superintelligence_330_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/mistral-ai-self-replicating-test-suites-330", "primary_source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-self-replicating-test-suites-330", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/mistral-ai-self-replicating-test-suites-330.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "claim:tsinghua-air-autonomous-synthesis-331", "slug": "tsinghua-air-autonomous-synthesis-331", "type": "claim", "name": "Tsinghua AIR Autonomous Synthesis Vector #331", "claim_scope": "AGI", "definition": "Frontier exploration into autonomous synthesis within Tsinghua AIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Autonomous Synthesis. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 33.6% generalization drop observed in unguided deployment.", "generalization_drop": 33.6, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-25", "source_url": "https://aki1k.com/superintelligence/lab/alibaba-cloud-ai-nuclear-smr-co-location-333", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 75.8, "terminal_bench_score": 86.4, "reality_gap_pct": 33.6, "evidence_confidence": "observed", "sha256": "sha256_333_332_sig", "ipfs_cid": "bafybei_superintelligence_333_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/alibaba-cloud-ai-nuclear-smr-co-location-333", "primary_source_url": "https://aki1k.com/superintelligence/lab/alibaba-cloud-ai-nuclear-smr-co-location-333", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/alibaba-cloud-ai-nuclear-smr-co-location-333.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "evaluation:01-ai-codebase-auto-repair-334", "slug": "01-ai-codebase-auto-repair-334", "type": "evaluation", "name": "01.AI Codebase Auto-Repair Vector #334", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into codebase auto-repair within 01.AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 40.9% generalization drop observed in unguided deployment.", "generalization_drop": 40.9, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-26", "source_url": "https://aki1k.com/superintelligence/evaluation/01-ai-codebase-auto-repair-334", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 21.8, "metr_ci_low": 10.9, "metr_ci_high": 69.8, "metr_median_end2026": 7.6, "rsi_level": 1, "rsi_exam_score": 77.7, "terminal_bench_score": 88.1, "reality_gap_pct": 40.9, "evidence_confidence": "self-reported", "sha256": "sha256_334_333_sig", "ipfs_cid": "bafybei_superintelligence_334_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/01-ai-codebase-auto-repair-334", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/01-ai-codebase-auto-repair-334", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/01-ai-codebase-auto-repair-334.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "compute:reka-ai-agent-collective-protocol-335", "slug": "reka-ai-agent-collective-protocol-335", "type": "compute", "name": "Reka AI Agent Collective Protocol Vector #335", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into agent collective protocol within Reka AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 51.5% generalization drop observed in unguided deployment.", "generalization_drop": 51.5, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/research/alibaba-cloud-ai-liquid-cooling-1mw-rack-356", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 94.5, "terminal_bench_score": 81.5, "reality_gap_pct": 51.5, "evidence_confidence": "independent", "sha256": "sha256_356_355_sig", "ipfs_cid": "bafybei_superintelligence_356_cid", "canonical_url": "https://aki1k.com/superintelligence/research/alibaba-cloud-ai-liquid-cooling-1mw-rack-356", "primary_source_url": "https://aki1k.com/superintelligence/research/alibaba-cloud-ai-liquid-cooling-1mw-rack-356", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/alibaba-cloud-ai-liquid-cooling-1mw-rack-356.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "governance:01-ai-nuclear-smr-co-location-357", "slug": "01-ai-nuclear-smr-co-location-357", "type": "governance", "name": "01.AI Nuclear SMR Co-Location Vector #357", "claim_scope": "ASI", "definition": "Frontier exploration into nuclear smr co-location within 01.AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 69.4% generalization drop observed in unguided deployment.", "generalization_drop": 69.4, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/infrastructure/alibaba-cloud-ai-autonomous-synthesis-379", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 29, "gw_total": 0.12, "accelerator_count": 36250, "grid_queue_months": 24, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 88.2, "terminal_bench_score": 76.6, "reality_gap_pct": 69.4, "evidence_confidence": "estimated", "sha256": "sha256_379_378_sig", "ipfs_cid": "bafybei_superintelligence_379_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/alibaba-cloud-ai-autonomous-synthesis-379", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/alibaba-cloud-ai-autonomous-synthesis-379", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/alibaba-cloud-ai-autonomous-synthesis-379.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "organization:01-ai-liquid-cooling-1mw-rack-380", "slug": "01-ai-liquid-cooling-1mw-rack-380", "type": "organization", "name": "01.AI Liquid Cooling 1MW/Rack Vector #380", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into liquid cooling 1mw/rack within 01.AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 76.7% generalization drop observed in unguided deployment.", "generalization_drop": 76.7, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-16", "source_url": "https://aki1k.com/superintelligence/organization/01-ai-liquid-cooling-1mw-rack-380", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 90.1, "terminal_bench_score": 78.3, "reality_gap_pct": 76.7, "evidence_confidence": "independent", "sha256": "sha256_380_379_sig", "ipfs_cid": "bafybei_superintelligence_380_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/01-ai-liquid-cooling-1mw-rack-380", "primary_source_url": "https://aki1k.com/superintelligence/organization/01-ai-liquid-cooling-1mw-rack-380", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/01-ai-liquid-cooling-1mw-rack-380.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "claim:reka-ai-nuclear-smr-co-location-381", "slug": "reka-ai-nuclear-smr-co-location-381", "type": "claim", "name": "Reka AI Nuclear SMR Co-Location Vector #381", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within Reka AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 84% generalization drop observed in unguided deployment.", "generalization_drop": 84, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-17", "source_url": "https://aki1k.com/superintelligence/claim/reka-ai-nuclear-smr-co-location-381", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 92, "terminal_bench_score": 80, "reality_gap_pct": 84, "evidence_confidence": "observed", "sha256": "sha256_381_380_sig", "ipfs_cid": "bafybei_superintelligence_381_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/reka-ai-nuclear-smr-co-location-381", "primary_source_url": "https://aki1k.com/superintelligence/claim/reka-ai-nuclear-smr-co-location-381", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/reka-ai-nuclear-smr-co-location-381.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "model:cohere-codebase-auto-repair-382", "slug": "cohere-codebase-auto-repair-382", "type": "model", "name": "Cohere Codebase Auto-Repair Vector #382", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Cohere infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 16.3% generalization drop observed in unguided deployment.", "generalization_drop": 16.3, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-18", "source_url": "https://aki1k.com/superintelligence/model/cohere-codebase-auto-repair-382", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 2.6, "metr_ci_low": 1.3, "metr_ci_high": 8.3, "metr_median_end2026": 0.9, "rsi_level": 1, "rsi_exam_score": 93.9, "terminal_bench_score": 81.7, "reality_gap_pct": 16.3, "evidence_confidence": "self-reported", "sha256": "sha256_382_381_sig", "ipfs_cid": "bafybei_superintelligence_382_cid", "canonical_url": "https://aki1k.com/superintelligence/model/cohere-codebase-auto-repair-382", "primary_source_url": "https://aki1k.com/superintelligence/model/cohere-codebase-auto-repair-382", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/cohere-codebase-auto-repair-382.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "lab:scale-ai-agent-collective-protocol-383", "slug": "scale-ai-agent-collective-protocol-383", "type": "lab", "name": "Scale AI Agent Collective Protocol Vector #383", "claim_scope": "RSI", "definition": "Frontier exploration into agent collective protocol within Scale AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 65.4% generalization drop observed in unguided deployment.", "generalization_drop": 65.4, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-07", "source_url": "https://aki1k.com/superintelligence/infrastructure/mistral-ai-nuclear-smr-co-location-399", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 339, "gw_total": 1.36, "accelerator_count": 423750, "grid_queue_months": 8, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 76.2, "terminal_bench_score": 88.6, "reality_gap_pct": 65.4, "evidence_confidence": "estimated", "sha256": "sha256_399_398_sig", "ipfs_cid": "bafybei_superintelligence_399_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/mistral-ai-nuclear-smr-co-location-399", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/mistral-ai-nuclear-smr-co-location-399", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/mistral-ai-nuclear-smr-co-location-399.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "organization:tsinghua-air-codebase-auto-repair-400", "slug": "tsinghua-air-codebase-auto-repair-400", "type": "organization", "name": "Tsinghua AIR Codebase Auto-Repair Vector #400", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into codebase auto-repair within Tsinghua AIR infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 72.7% generalization drop observed in unguided deployment.", "generalization_drop": 72.7, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-08", "source_url": "https://aki1k.com/superintelligence/organization/tsinghua-air-codebase-auto-repair-400", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 78.1, "terminal_bench_score": 90.3, "reality_gap_pct": 72.7, "evidence_confidence": "independent", "sha256": "sha256_400_399_sig", "ipfs_cid": "bafybei_superintelligence_400_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/tsinghua-air-codebase-auto-repair-400", "primary_source_url": "https://aki1k.com/superintelligence/organization/tsinghua-air-codebase-auto-repair-400", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/tsinghua-air-codebase-auto-repair-400.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "claim:shanghai-ai-lab-agent-collective-protocol-401", "slug": "shanghai-ai-lab-agent-collective-protocol-401", "type": "claim", "name": "Shanghai AI Lab Agent Collective Protocol Vector #401", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Shanghai AI Lab infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 19.6% generalization drop observed in unguided deployment.", "generalization_drop": 19.6, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-11", "source_url": "https://aki1k.com/superintelligence/lab/01-ai-autonomous-synthesis-403", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 83.8, "terminal_bench_score": 73.4, "reality_gap_pct": 19.6, "evidence_confidence": "estimated", "sha256": "sha256_403_402_sig", "ipfs_cid": "bafybei_superintelligence_403_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/01-ai-autonomous-synthesis-403", "primary_source_url": "https://aki1k.com/superintelligence/lab/01-ai-autonomous-synthesis-403", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/01-ai-autonomous-synthesis-403.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "evaluation:reka-ai-liquid-cooling-1mw-rack-404", "slug": "reka-ai-liquid-cooling-1mw-rack-404", "type": "evaluation", "name": "Reka AI Liquid Cooling 1MW/Rack Vector #404", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Reka AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 26.9% generalization drop observed in unguided deployment.", "generalization_drop": 26.9, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-12", "source_url": "https://aki1k.com/superintelligence/evaluation/reka-ai-liquid-cooling-1mw-rack-404", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 8.8, "metr_ci_low": 4.4, "metr_ci_high": 28.2, "metr_median_end2026": 3.1, "rsi_level": 3, "rsi_exam_score": 85.7, "terminal_bench_score": 75.1, "reality_gap_pct": 26.9, "evidence_confidence": "independent", "sha256": "sha256_404_403_sig", "ipfs_cid": "bafybei_superintelligence_404_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/reka-ai-liquid-cooling-1mw-rack-404", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/reka-ai-liquid-cooling-1mw-rack-404", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/reka-ai-liquid-cooling-1mw-rack-404.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "compute:cohere-nuclear-smr-co-location-405", "slug": "cohere-nuclear-smr-co-location-405", "type": "compute", "name": "Cohere Nuclear SMR Co-Location Vector #405", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Cohere infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 34.2% generalization drop observed in unguided deployment.", "generalization_drop": 34.2, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-13", "source_url": "https://aki1k.com/superintelligence/compute/cohere-nuclear-smr-co-location-405", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 432, "gw_total": 1.73, "accelerator_count": 540000, "grid_queue_months": 14, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 87.6, "terminal_bench_score": 76.8, "reality_gap_pct": 34.2, "evidence_confidence": "observed", "sha256": "sha256_405_404_sig", "ipfs_cid": "bafybei_superintelligence_405_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/cohere-nuclear-smr-co-location-405", "primary_source_url": "https://aki1k.com/superintelligence/compute/cohere-nuclear-smr-co-location-405", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/cohere-nuclear-smr-co-location-405.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "research:scale-ai-codebase-auto-repair-406", "slug": "scale-ai-codebase-auto-repair-406", "type": "research", "name": "Scale AI Codebase Auto-Repair Vector #406", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within Scale AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 41.5% generalization drop observed in unguided deployment.", "generalization_drop": 41.5, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-14", "source_url": "https://aki1k.com/superintelligence/research/scale-ai-codebase-auto-repair-406", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 89.5, "terminal_bench_score": 78.5, "reality_gap_pct": 41.5, "evidence_confidence": "self-reported", "sha256": "sha256_406_405_sig", "ipfs_cid": "bafybei_superintelligence_406_cid", "canonical_url": "https://aki1k.com/superintelligence/research/scale-ai-codebase-auto-repair-406", "primary_source_url": "https://aki1k.com/superintelligence/research/scale-ai-codebase-auto-repair-406", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/scale-ai-codebase-auto-repair-406.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "governance:metr-agent-collective-protocol-407", "slug": "metr-agent-collective-protocol-407", "type": "governance", "name": "METR Agent Collective Protocol Vector #407", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within METR infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 66.7% generalization drop observed in unguided deployment.", "generalization_drop": 66.7, "real_world_outcome": "Empirical deployment verified across METR target workload clusters.", "claim_date": "2026-08-10", "source_url": "https://aki1k.com/superintelligence/organization/metr-codebase-auto-repair-430", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 85.1, "terminal_bench_score": 75.3, "reality_gap_pct": 66.7, "evidence_confidence": "self-reported", "sha256": "sha256_430_429_sig", "ipfs_cid": "bafybei_superintelligence_430_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/metr-codebase-auto-repair-430", "primary_source_url": "https://aki1k.com/superintelligence/organization/metr-codebase-auto-repair-430", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/metr-codebase-auto-repair-430.json", "notes": "Audited benchmark telemetry for METR research team." }, { "id": "claim:epoch-ai-agent-collective-protocol-431", "slug": "epoch-ai-agent-collective-protocol-431", "type": "claim", "name": "Epoch AI Agent Collective Protocol Vector #431", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Epoch AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Epoch AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 77.3% generalization drop observed in unguided deployment.", "generalization_drop": 77.3, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-04", "source_url": "https://aki1k.com/superintelligence/model/scale-ai-liquid-cooling-1mw-rack-452", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 29.6, "metr_ci_low": 14.8, "metr_ci_high": 94.7, "metr_median_end2026": 10.4, "rsi_level": 3, "rsi_exam_score": 76.9, "terminal_bench_score": 90.7, "reality_gap_pct": 77.3, "evidence_confidence": "independent", "sha256": "sha256_452_451_sig", "ipfs_cid": "bafybei_superintelligence_452_cid", "canonical_url": "https://aki1k.com/superintelligence/model/scale-ai-liquid-cooling-1mw-rack-452", "primary_source_url": "https://aki1k.com/superintelligence/model/scale-ai-liquid-cooling-1mw-rack-452", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/scale-ai-liquid-cooling-1mw-rack-452.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "lab:metr-nuclear-smr-co-location-453", "slug": "metr-nuclear-smr-co-location-453", "type": "lab", "name": "METR Nuclear SMR Co-Location Vector #453", "claim_scope": "RSI", "definition": "Frontier exploration into nuclear smr co-location within METR infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 54.7% generalization drop observed in unguided deployment.", "generalization_drop": 54.7, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-14", "source_url": "https://aki1k.com/superintelligence/organization/nvidia-research-codebase-auto-repair-490", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 74.1, "terminal_bench_score": 89.3, "reality_gap_pct": 54.7, "evidence_confidence": "self-reported", "sha256": "sha256_490_489_sig", "ipfs_cid": "bafybei_superintelligence_490_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/nvidia-research-codebase-auto-repair-490", "primary_source_url": "https://aki1k.com/superintelligence/organization/nvidia-research-codebase-auto-repair-490", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/nvidia-research-codebase-auto-repair-490.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "claim:mistral-ai-agent-collective-protocol-491", "slug": "mistral-ai-agent-collective-protocol-491", "type": "claim", "name": "Mistral AI Agent Collective Protocol Vector #491", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Mistral AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 79.9% generalization drop observed in unguided deployment.", "generalization_drop": 79.9, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-10", "source_url": "https://aki1k.com/superintelligence/evaluation/mistral-ai-codebase-auto-repair-514", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 39.8, "metr_ci_low": 19.9, "metr_ci_high": 127.4, "metr_median_end2026": 13.9, "rsi_level": 1, "rsi_exam_score": 94.7, "terminal_bench_score": 86.1, "reality_gap_pct": 79.9, "evidence_confidence": "self-reported", "sha256": "sha256_514_513_sig", "ipfs_cid": "bafybei_superintelligence_514_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/mistral-ai-codebase-auto-repair-514", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/mistral-ai-codebase-auto-repair-514", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/mistral-ai-codebase-auto-repair-514.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "compute:tsinghua-air-agent-collective-protocol-515", "slug": "tsinghua-air-agent-collective-protocol-515", "type": "compute", "name": "Tsinghua AIR Agent Collective Protocol Vector #515", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into agent collective protocol within Tsinghua AIR infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 15.5% generalization drop observed in unguided deployment.", "generalization_drop": 15.5, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-04", "source_url": "https://aki1k.com/superintelligence/research/nvidia-research-liquid-cooling-1mw-rack-536", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 86.5, "terminal_bench_score": 79.5, "reality_gap_pct": 15.5, "evidence_confidence": "independent", "sha256": "sha256_536_535_sig", "ipfs_cid": "bafybei_superintelligence_536_cid", "canonical_url": "https://aki1k.com/superintelligence/research/nvidia-research-liquid-cooling-1mw-rack-536", "primary_source_url": "https://aki1k.com/superintelligence/research/nvidia-research-liquid-cooling-1mw-rack-536", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/nvidia-research-liquid-cooling-1mw-rack-536.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "governance:mistral-ai-nuclear-smr-co-location-537", "slug": "mistral-ai-nuclear-smr-co-location-537", "type": "governance", "name": "Mistral AI Nuclear SMR Co-Location Vector #537", "claim_scope": "ASI", "definition": "Frontier exploration into nuclear smr co-location within Mistral AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 42.7% generalization drop observed in unguided deployment.", "generalization_drop": 42.7, "real_world_outcome": "Empirical deployment verified across Oxford Future of Life target workload clusters.", "claim_date": "2026-08-18", "source_url": "https://aki1k.com/superintelligence/organization/oxford-future-of-life-codebase-auto-repair-550", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 88.1, "terminal_bench_score": 81.3, "reality_gap_pct": 42.7, "evidence_confidence": "self-reported", "sha256": "sha256_550_549_sig", "ipfs_cid": "bafybei_superintelligence_550_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/oxford-future-of-life-codebase-auto-repair-550", "primary_source_url": "https://aki1k.com/superintelligence/organization/oxford-future-of-life-codebase-auto-repair-550", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/oxford-future-of-life-codebase-auto-repair-550.json", "notes": "Audited benchmark telemetry for Oxford Future of Life research team." }, { "id": "claim:tokyo-university-ai-agent-collective-protocol-551", "slug": "tokyo-university-ai-agent-collective-protocol-551", "type": "claim", "name": "Tokyo University AI Agent Collective Protocol Vector #551", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Tokyo University AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tokyo University AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 50% generalization drop observed in unguided deployment.", "generalization_drop": 50, "real_world_outcome": "Empirical deployment verified across Tokyo University AI target workload clusters.", "claim_date": "2026-08-19", "source_url": "https://aki1k.com/superintelligence/claim/tokyo-university-ai-agent-collective-protocol-551", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 90, "terminal_bench_score": 83, "reality_gap_pct": 50, "evidence_confidence": "estimated", "sha256": "sha256_551_550_sig", "ipfs_cid": "bafybei_superintelligence_551_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/tokyo-university-ai-agent-collective-protocol-551", "primary_source_url": "https://aki1k.com/superintelligence/claim/tokyo-university-ai-agent-collective-protocol-551", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/tokyo-university-ai-agent-collective-protocol-551.json", "notes": "Audited benchmark telemetry for Tokyo University AI research team." }, { "id": "model:cern-quantum-ai-self-replicating-test-suites-552", "slug": "cern-quantum-ai-self-replicating-test-suites-552", "type": "model", "name": "CERN Quantum AI Self-Replicating Test Suites Vector #552", "claim_scope": "ASI", "definition": "Frontier exploration into self-replicating test suites within CERN Quantum AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for CERN Quantum AI Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 57.3% generalization drop observed in unguided deployment.", "generalization_drop": 57.3, "real_world_outcome": "Empirical deployment verified across CERN Quantum AI target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/model/cern-quantum-ai-self-replicating-test-suites-552", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 39.6, "metr_ci_low": 19.8, "metr_ci_high": 126.7, "metr_median_end2026": 13.9, "rsi_level": 3, "rsi_exam_score": 91.9, "terminal_bench_score": 84.7, "reality_gap_pct": 57.3, "evidence_confidence": "independent", "sha256": "sha256_552_551_sig", "ipfs_cid": "bafybei_superintelligence_552_cid", "canonical_url": "https://aki1k.com/superintelligence/model/cern-quantum-ai-self-replicating-test-suites-552", "primary_source_url": "https://aki1k.com/superintelligence/model/cern-quantum-ai-self-replicating-test-suites-552", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/cern-quantum-ai-self-replicating-test-suites-552.json", "notes": "Audited benchmark telemetry for CERN Quantum AI research team." }, { "id": "lab:openai-autonomous-synthesis-553", "slug": "openai-autonomous-synthesis-553", "type": "lab", "name": "OpenAI Autonomous Synthesis Vector #553", "claim_scope": "RSI", "definition": "Frontier exploration into autonomous synthesis within OpenAI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for OpenAI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 64.6% generalization drop observed in unguided deployment.", "generalization_drop": 64.6, "real_world_outcome": "Empirical deployment verified across OpenAI target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/lab/openai-autonomous-synthesis-553", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 93.8, "terminal_bench_score": 86.4, "reality_gap_pct": 64.6, "evidence_confidence": "observed", "sha256": "sha256_553_552_sig", "ipfs_cid": "bafybei_superintelligence_553_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/openai-autonomous-synthesis-553", "primary_source_url": "https://aki1k.com/superintelligence/lab/openai-autonomous-synthesis-553", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/openai-autonomous-synthesis-553.json", "notes": "Audited benchmark telemetry for OpenAI research team." }, { "id": "evaluation:anthropic-liquid-cooling-1mw-rack-554", "slug": "anthropic-liquid-cooling-1mw-rack-554", "type": "evaluation", "name": "Anthropic Liquid Cooling 1MW/Rack Vector #554", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Anthropic infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Anthropic Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 71.9% generalization drop observed in unguided deployment.", "generalization_drop": 71.9, "real_world_outcome": "Empirical deployment verified across Anthropic target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/evaluation/anthropic-liquid-cooling-1mw-rack-554", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 3.8, "metr_ci_low": 1.9, "metr_ci_high": 12.2, "metr_median_end2026": 1.3, "rsi_level": 1, "rsi_exam_score": 70.7, "terminal_bench_score": 88.1, "reality_gap_pct": 71.9, "evidence_confidence": "self-reported", "sha256": "sha256_554_553_sig", "ipfs_cid": "bafybei_superintelligence_554_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/anthropic-liquid-cooling-1mw-rack-554", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/anthropic-liquid-cooling-1mw-rack-554", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/anthropic-liquid-cooling-1mw-rack-554.json", "notes": "Audited benchmark telemetry for Anthropic research team." }, { "id": "compute:google-deepmind-nuclear-smr-co-location-555", "slug": "google-deepmind-nuclear-smr-co-location-555", "type": "compute", "name": "Google DeepMind Nuclear SMR Co-Location Vector #555", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Google DeepMind infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Google DeepMind Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 79.2% generalization drop observed in unguided deployment.", "generalization_drop": 79.2, "real_world_outcome": "Empirical deployment verified across Google DeepMind target workload clusters.", "claim_date": "2026-08-23", "source_url": "https://aki1k.com/superintelligence/compute/google-deepmind-nuclear-smr-co-location-555", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 57, "gw_total": 0.23, "accelerator_count": 71250, "grid_queue_months": 20, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 72.6, "terminal_bench_score": 89.8, "reality_gap_pct": 79.2, "evidence_confidence": "estimated", "sha256": "sha256_555_554_sig", "ipfs_cid": "bafybei_superintelligence_555_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/google-deepmind-nuclear-smr-co-location-555", "primary_source_url": "https://aki1k.com/superintelligence/compute/google-deepmind-nuclear-smr-co-location-555", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/google-deepmind-nuclear-smr-co-location-555.json", "notes": "Audited benchmark telemetry for Google DeepMind research team." }, { "id": "research:xai-codebase-auto-repair-556", "slug": "xai-codebase-auto-repair-556", "type": "research", "name": "xAI Codebase Auto-Repair Vector #556", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within xAI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for xAI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 11.5% generalization drop observed in unguided deployment.", "generalization_drop": 11.5, "real_world_outcome": "Empirical deployment verified across xAI target workload clusters.", "claim_date": "2026-08-24", "source_url": "https://aki1k.com/superintelligence/research/xai-codebase-auto-repair-556", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 74.5, "terminal_bench_score": 91.5, "reality_gap_pct": 11.5, "evidence_confidence": "independent", "sha256": "sha256_556_555_sig", "ipfs_cid": "bafybei_superintelligence_556_cid", "canonical_url": "https://aki1k.com/superintelligence/research/xai-codebase-auto-repair-556", "primary_source_url": "https://aki1k.com/superintelligence/research/xai-codebase-auto-repair-556", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/xai-codebase-auto-repair-556.json", "notes": "Audited benchmark telemetry for xAI research team." }, { "id": "governance:meta-fair-agent-collective-protocol-557", "slug": "meta-fair-agent-collective-protocol-557", "type": "governance", "name": "Meta FAIR Agent Collective Protocol Vector #557", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within Meta FAIR infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Meta FAIR Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 18.8% generalization drop observed in unguided deployment.", "generalization_drop": 18.8, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-25", "source_url": "https://aki1k.com/superintelligence/governance/meta-fair-agent-collective-protocol-557", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 76.4, "terminal_bench_score": 93.2, "reality_gap_pct": 18.8, "evidence_confidence": "observed", "sha256": "sha256_557_556_sig", "ipfs_cid": "bafybei_superintelligence_557_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/meta-fair-agent-collective-protocol-557", "primary_source_url": "https://aki1k.com/superintelligence/governance/meta-fair-agent-collective-protocol-557", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/meta-fair-agent-collective-protocol-557.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "emerging:microsoft-ai-self-replicating-test-suites-558", "slug": "microsoft-ai-self-replicating-test-suites-558", "type": "emerging", "name": "Microsoft AI Self-Replicating Test Suites Vector #558", "claim_scope": "RSI", "definition": "Frontier exploration into self-replicating test suites within Microsoft AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 26.1% generalization drop observed in unguided deployment.", "generalization_drop": 26.1, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-26", "source_url": "https://aki1k.com/superintelligence/emerging/microsoft-ai-self-replicating-test-suites-558", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 78.3, "terminal_bench_score": 72.9, "reality_gap_pct": 26.1, "evidence_confidence": "self-reported", "sha256": "sha256_558_557_sig", "ipfs_cid": "bafybei_superintelligence_558_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/microsoft-ai-self-replicating-test-suites-558", "primary_source_url": "https://aki1k.com/superintelligence/emerging/microsoft-ai-self-replicating-test-suites-558", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/microsoft-ai-self-replicating-test-suites-558.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "infrastructure:nvidia-research-autonomous-synthesis-559", "slug": "nvidia-research-autonomous-synthesis-559", "type": "infrastructure", "name": "NVIDIA Research Autonomous Synthesis Vector #559", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into autonomous synthesis within NVIDIA Research infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 33.4% generalization drop observed in unguided deployment.", "generalization_drop": 33.4, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-27", "source_url": "https://aki1k.com/superintelligence/infrastructure/nvidia-research-autonomous-synthesis-559", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 119, "gw_total": 0.48, "accelerator_count": 148750, "grid_queue_months": 24, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 80.2, "terminal_bench_score": 74.6, "reality_gap_pct": 33.4, "evidence_confidence": "estimated", "sha256": "sha256_559_558_sig", "ipfs_cid": "bafybei_superintelligence_559_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/nvidia-research-autonomous-synthesis-559", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/nvidia-research-autonomous-synthesis-559", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/nvidia-research-autonomous-synthesis-559.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "organization:mistral-ai-liquid-cooling-1mw-rack-560", "slug": "mistral-ai-liquid-cooling-1mw-rack-560", "type": "organization", "name": "Mistral AI Liquid Cooling 1MW/Rack Vector #560", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into liquid cooling 1mw/rack within Mistral AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 40.7% generalization drop observed in unguided deployment.", "generalization_drop": 40.7, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-28", "source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-liquid-cooling-1mw-rack-560", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 82.1, "terminal_bench_score": 76.3, "reality_gap_pct": 40.7, "evidence_confidence": "independent", "sha256": "sha256_560_559_sig", "ipfs_cid": "bafybei_superintelligence_560_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/mistral-ai-liquid-cooling-1mw-rack-560", "primary_source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-liquid-cooling-1mw-rack-560", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/mistral-ai-liquid-cooling-1mw-rack-560.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "claim:tsinghua-air-nuclear-smr-co-location-561", "slug": "tsinghua-air-nuclear-smr-co-location-561", "type": "claim", "name": "Tsinghua AIR Nuclear SMR Co-Location Vector #561", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within Tsinghua AIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 48% generalization drop observed in unguided deployment.", "generalization_drop": 48, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-01", "source_url": "https://aki1k.com/superintelligence/claim/tsinghua-air-nuclear-smr-co-location-561", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 84, "terminal_bench_score": 78, "reality_gap_pct": 48, "evidence_confidence": "observed", "sha256": "sha256_561_560_sig", "ipfs_cid": "bafybei_superintelligence_561_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/tsinghua-air-nuclear-smr-co-location-561", "primary_source_url": "https://aki1k.com/superintelligence/claim/tsinghua-air-nuclear-smr-co-location-561", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/tsinghua-air-nuclear-smr-co-location-561.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "model:shanghai-ai-lab-codebase-auto-repair-562", "slug": "shanghai-ai-lab-codebase-auto-repair-562", "type": "model", "name": "Shanghai AI Lab Codebase Auto-Repair Vector #562", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Shanghai AI Lab infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Codebase Auto-Repair. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 75.2% generalization drop observed in unguided deployment.", "generalization_drop": 75.2, "real_world_outcome": "Empirical deployment verified across CERN Quantum AI target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/compute/cern-quantum-ai-agent-collective-protocol-575", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 367, "gw_total": 1.47, "accelerator_count": 458750, "grid_queue_months": 40, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 85.6, "terminal_bench_score": 79.8, "reality_gap_pct": 75.2, "evidence_confidence": "estimated", "sha256": "sha256_575_574_sig", "ipfs_cid": "bafybei_superintelligence_575_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/cern-quantum-ai-agent-collective-protocol-575", "primary_source_url": "https://aki1k.com/superintelligence/compute/cern-quantum-ai-agent-collective-protocol-575", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/cern-quantum-ai-agent-collective-protocol-575.json", "notes": "Audited benchmark telemetry for CERN Quantum AI research team." }, { "id": "research:openai-self-replicating-test-suites-576", "slug": "openai-self-replicating-test-suites-576", "type": "research", "name": "OpenAI Self-Replicating Test Suites Vector #576", "claim_scope": "AGI", "definition": "Frontier exploration into self-replicating test suites within OpenAI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for OpenAI Self-Replicating Test Suites. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 36.7% generalization drop observed in unguided deployment.", "generalization_drop": 36.7, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/organization/meta-fair-codebase-auto-repair-580", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 70.1, "terminal_bench_score": 88.3, "reality_gap_pct": 36.7, "evidence_confidence": "independent", "sha256": "sha256_580_579_sig", "ipfs_cid": "bafybei_superintelligence_580_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/meta-fair-codebase-auto-repair-580", "primary_source_url": "https://aki1k.com/superintelligence/organization/meta-fair-codebase-auto-repair-580", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/meta-fair-codebase-auto-repair-580.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "claim:microsoft-ai-agent-collective-protocol-581", "slug": "microsoft-ai-agent-collective-protocol-581", "type": "claim", "name": "Microsoft AI Agent Collective Protocol Vector #581", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Microsoft AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 44% generalization drop observed in unguided deployment.", "generalization_drop": 44, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/claim/microsoft-ai-agent-collective-protocol-581", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 72, "terminal_bench_score": 90, "reality_gap_pct": 44, "evidence_confidence": "observed", "sha256": "sha256_581_580_sig", "ipfs_cid": "bafybei_superintelligence_581_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/microsoft-ai-agent-collective-protocol-581", "primary_source_url": "https://aki1k.com/superintelligence/claim/microsoft-ai-agent-collective-protocol-581", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/microsoft-ai-agent-collective-protocol-581.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "model:nvidia-research-self-replicating-test-suites-582", "slug": "nvidia-research-self-replicating-test-suites-582", "type": "model", "name": "NVIDIA Research Self-Replicating Test Suites Vector #582", "claim_scope": "ASI", "definition": "Frontier exploration into self-replicating test suites within NVIDIA Research infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 51.3% generalization drop observed in unguided deployment.", "generalization_drop": 51.3, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/model/nvidia-research-self-replicating-test-suites-582", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 22.6, "metr_ci_low": 11.3, "metr_ci_high": 72.3, "metr_median_end2026": 7.9, "rsi_level": 1, "rsi_exam_score": 73.9, "terminal_bench_score": 91.7, "reality_gap_pct": 51.3, "evidence_confidence": "self-reported", "sha256": "sha256_582_581_sig", "ipfs_cid": "bafybei_superintelligence_582_cid", "canonical_url": "https://aki1k.com/superintelligence/model/nvidia-research-self-replicating-test-suites-582", "primary_source_url": "https://aki1k.com/superintelligence/model/nvidia-research-self-replicating-test-suites-582", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/nvidia-research-self-replicating-test-suites-582.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "lab:mistral-ai-autonomous-synthesis-583", "slug": "mistral-ai-autonomous-synthesis-583", "type": "lab", "name": "Mistral AI Autonomous Synthesis Vector #583", "claim_scope": "RSI", "definition": "Frontier exploration into autonomous synthesis within Mistral AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 58.6% generalization drop observed in unguided deployment.", "generalization_drop": 58.6, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-23", "source_url": "https://aki1k.com/superintelligence/lab/mistral-ai-autonomous-synthesis-583", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 75.8, "terminal_bench_score": 93.4, "reality_gap_pct": 58.6, "evidence_confidence": "estimated", "sha256": "sha256_583_582_sig", "ipfs_cid": "bafybei_superintelligence_583_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/mistral-ai-autonomous-synthesis-583", "primary_source_url": "https://aki1k.com/superintelligence/lab/mistral-ai-autonomous-synthesis-583", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/mistral-ai-autonomous-synthesis-583.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "evaluation:tsinghua-air-liquid-cooling-1mw-rack-584", "slug": "tsinghua-air-liquid-cooling-1mw-rack-584", "type": "evaluation", "name": "Tsinghua AIR Liquid Cooling 1MW/Rack Vector #584", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Tsinghua AIR infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 65.9% generalization drop observed in unguided deployment.", "generalization_drop": 65.9, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-24", "source_url": "https://aki1k.com/superintelligence/evaluation/tsinghua-air-liquid-cooling-1mw-rack-584", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 26.8, "metr_ci_low": 13.4, "metr_ci_high": 85.8, "metr_median_end2026": 9.4, "rsi_level": 3, "rsi_exam_score": 77.7, "terminal_bench_score": 73.1, "reality_gap_pct": 65.9, "evidence_confidence": "independent", "sha256": "sha256_584_583_sig", "ipfs_cid": "bafybei_superintelligence_584_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/tsinghua-air-liquid-cooling-1mw-rack-584", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/tsinghua-air-liquid-cooling-1mw-rack-584", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/tsinghua-air-liquid-cooling-1mw-rack-584.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "compute:shanghai-ai-lab-nuclear-smr-co-location-585", "slug": "shanghai-ai-lab-nuclear-smr-co-location-585", "type": "compute", "name": "Shanghai AI Lab Nuclear SMR Co-Location Vector #585", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Shanghai AI Lab infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 54.6% generalization drop observed in unguided deployment.", "generalization_drop": 54.6, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/lab/meta-fair-nuclear-smr-co-location-603", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 88.8, "terminal_bench_score": 83.4, "reality_gap_pct": 54.6, "evidence_confidence": "estimated", "sha256": "sha256_603_602_sig", "ipfs_cid": "bafybei_superintelligence_603_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/meta-fair-nuclear-smr-co-location-603", "primary_source_url": "https://aki1k.com/superintelligence/lab/meta-fair-nuclear-smr-co-location-603", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/meta-fair-nuclear-smr-co-location-603.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "evaluation:microsoft-ai-codebase-auto-repair-604", "slug": "microsoft-ai-codebase-auto-repair-604", "type": "evaluation", "name": "Microsoft AI Codebase Auto-Repair Vector #604", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into codebase auto-repair within Microsoft AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 61.9% generalization drop observed in unguided deployment.", "generalization_drop": 61.9, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-16", "source_url": "https://aki1k.com/superintelligence/evaluation/microsoft-ai-codebase-auto-repair-604", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 28.8, "metr_ci_low": 14.4, "metr_ci_high": 92.2, "metr_median_end2026": 10.1, "rsi_level": 3, "rsi_exam_score": 90.7, "terminal_bench_score": 85.1, "reality_gap_pct": 61.9, "evidence_confidence": "independent", "sha256": "sha256_604_603_sig", "ipfs_cid": "bafybei_superintelligence_604_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/microsoft-ai-codebase-auto-repair-604", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/microsoft-ai-codebase-auto-repair-604", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/microsoft-ai-codebase-auto-repair-604.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "compute:nvidia-research-agent-collective-protocol-605", "slug": "nvidia-research-agent-collective-protocol-605", "type": "compute", "name": "NVIDIA Research Agent Collective Protocol Vector #605", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into agent collective protocol within NVIDIA Research infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 69.2% generalization drop observed in unguided deployment.", "generalization_drop": 69.2, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-17", "source_url": "https://aki1k.com/superintelligence/compute/nvidia-research-agent-collective-protocol-605", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 382, "gw_total": 1.53, "accelerator_count": 477500, "grid_queue_months": 34, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 92.6, "terminal_bench_score": 86.8, "reality_gap_pct": 69.2, "evidence_confidence": "observed", "sha256": "sha256_605_604_sig", "ipfs_cid": "bafybei_superintelligence_605_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/nvidia-research-agent-collective-protocol-605", "primary_source_url": "https://aki1k.com/superintelligence/compute/nvidia-research-agent-collective-protocol-605", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/nvidia-research-agent-collective-protocol-605.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "research:mistral-ai-self-replicating-test-suites-606", "slug": "mistral-ai-self-replicating-test-suites-606", "type": "research", "name": "Mistral AI Self-Replicating Test Suites Vector #606", "claim_scope": "AGI", "definition": "Frontier exploration into self-replicating test suites within Mistral AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 76.5% generalization drop observed in unguided deployment.", "generalization_drop": 76.5, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-18", "source_url": "https://aki1k.com/superintelligence/research/mistral-ai-self-replicating-test-suites-606", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 94.5, "terminal_bench_score": 88.5, "reality_gap_pct": 76.5, "evidence_confidence": "self-reported", "sha256": "sha256_606_605_sig", "ipfs_cid": "bafybei_superintelligence_606_cid", "canonical_url": "https://aki1k.com/superintelligence/research/mistral-ai-self-replicating-test-suites-606", "primary_source_url": "https://aki1k.com/superintelligence/research/mistral-ai-self-replicating-test-suites-606", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/mistral-ai-self-replicating-test-suites-606.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "governance:tsinghua-air-autonomous-synthesis-607", "slug": "tsinghua-air-autonomous-synthesis-607", "type": "governance", "name": "Tsinghua AIR Autonomous Synthesis Vector #607", "claim_scope": "ASI", "definition": "Frontier exploration into autonomous synthesis within Tsinghua AIR infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 83.8% generalization drop observed in unguided deployment.", "generalization_drop": 83.8, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-19", "source_url": "https://aki1k.com/superintelligence/governance/tsinghua-air-autonomous-synthesis-607", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 71.4, "terminal_bench_score": 90.2, "reality_gap_pct": 83.8, "evidence_confidence": "estimated", "sha256": "sha256_607_606_sig", "ipfs_cid": "bafybei_superintelligence_607_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/tsinghua-air-autonomous-synthesis-607", "primary_source_url": "https://aki1k.com/superintelligence/governance/tsinghua-air-autonomous-synthesis-607", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/tsinghua-air-autonomous-synthesis-607.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "emerging:shanghai-ai-lab-liquid-cooling-1mw-rack-608", "slug": "shanghai-ai-lab-liquid-cooling-1mw-rack-608", "type": "emerging", "name": "Shanghai AI Lab Liquid Cooling 1MW/Rack Vector #608", "claim_scope": "RSI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Shanghai AI Lab infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 16.1% generalization drop observed in unguided deployment.", "generalization_drop": 16.1, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-20", "source_url": "https://aki1k.com/superintelligence/emerging/shanghai-ai-lab-liquid-cooling-1mw-rack-608", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 73.3, "terminal_bench_score": 91.9, "reality_gap_pct": 16.1, "evidence_confidence": "independent", "sha256": "sha256_608_607_sig", "ipfs_cid": "bafybei_superintelligence_608_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/shanghai-ai-lab-liquid-cooling-1mw-rack-608", "primary_source_url": "https://aki1k.com/superintelligence/emerging/shanghai-ai-lab-liquid-cooling-1mw-rack-608", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/shanghai-ai-lab-liquid-cooling-1mw-rack-608.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "infrastructure:alibaba-cloud-ai-nuclear-smr-co-location-609", "slug": "alibaba-cloud-ai-nuclear-smr-co-location-609", "type": "infrastructure", "name": "Alibaba Cloud AI Nuclear SMR Co-Location Vector #609", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into nuclear smr co-location within Alibaba Cloud AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 50.6% generalization drop observed in unguided deployment.", "generalization_drop": 50.6, "real_world_outcome": "Empirical deployment verified across Anthropic target workload clusters.", "claim_date": "2026-08-07", "source_url": "https://aki1k.com/superintelligence/lab/anthropic-agent-collective-protocol-623", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 76.8, "terminal_bench_score": 73.4, "reality_gap_pct": 50.6, "evidence_confidence": "estimated", "sha256": "sha256_623_622_sig", "ipfs_cid": "bafybei_superintelligence_623_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/anthropic-agent-collective-protocol-623", "primary_source_url": "https://aki1k.com/superintelligence/lab/anthropic-agent-collective-protocol-623", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/anthropic-agent-collective-protocol-623.json", "notes": "Audited benchmark telemetry for Anthropic research team." }, { "id": "evaluation:google-deepmind-self-replicating-test-suites-624", "slug": "google-deepmind-self-replicating-test-suites-624", "type": "evaluation", "name": "Google DeepMind Self-Replicating Test Suites Vector #624", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into self-replicating test suites within Google DeepMind infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Google DeepMind Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 57.9% generalization drop observed in unguided deployment.", "generalization_drop": 57.9, "real_world_outcome": "Empirical deployment verified across Google DeepMind target workload clusters.", "claim_date": "2026-08-08", "source_url": "https://aki1k.com/superintelligence/evaluation/google-deepmind-self-replicating-test-suites-624", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 30.8, "metr_ci_low": 15.4, "metr_ci_high": 98.6, "metr_median_end2026": 10.8, "rsi_level": 3, "rsi_exam_score": 78.7, "terminal_bench_score": 75.1, "reality_gap_pct": 57.9, "evidence_confidence": "independent", "sha256": "sha256_624_623_sig", "ipfs_cid": "bafybei_superintelligence_624_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/google-deepmind-self-replicating-test-suites-624", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/google-deepmind-self-replicating-test-suites-624", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/google-deepmind-self-replicating-test-suites-624.json", "notes": "Audited benchmark telemetry for Google DeepMind research team." }, { "id": "compute:xai-autonomous-synthesis-625", "slug": "xai-autonomous-synthesis-625", "type": "compute", "name": "xAI Autonomous Synthesis Vector #625", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into autonomous synthesis within xAI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for xAI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 65.2% generalization drop observed in unguided deployment.", "generalization_drop": 65.2, "real_world_outcome": "Empirical deployment verified across xAI target workload clusters.", "claim_date": "2026-08-09", "source_url": "https://aki1k.com/superintelligence/compute/xai-autonomous-synthesis-625", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 242, "gw_total": 0.97, "accelerator_count": 302500, "grid_queue_months": 18, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 80.6, "terminal_bench_score": 76.8, "reality_gap_pct": 65.2, "evidence_confidence": "observed", "sha256": "sha256_625_624_sig", "ipfs_cid": "bafybei_superintelligence_625_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/xai-autonomous-synthesis-625", "primary_source_url": "https://aki1k.com/superintelligence/compute/xai-autonomous-synthesis-625", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/xai-autonomous-synthesis-625.json", "notes": "Audited benchmark telemetry for xAI research team." }, { "id": "research:meta-fair-liquid-cooling-1mw-rack-626", "slug": "meta-fair-liquid-cooling-1mw-rack-626", "type": "research", "name": "Meta FAIR Liquid Cooling 1MW/Rack Vector #626", "claim_scope": "AGI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Meta FAIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Meta FAIR Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 72.5% generalization drop observed in unguided deployment.", "generalization_drop": 72.5, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-10", "source_url": "https://aki1k.com/superintelligence/research/meta-fair-liquid-cooling-1mw-rack-626", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 82.5, "terminal_bench_score": 78.5, "reality_gap_pct": 72.5, "evidence_confidence": "self-reported", "sha256": "sha256_626_625_sig", "ipfs_cid": "bafybei_superintelligence_626_cid", "canonical_url": "https://aki1k.com/superintelligence/research/meta-fair-liquid-cooling-1mw-rack-626", "primary_source_url": "https://aki1k.com/superintelligence/research/meta-fair-liquid-cooling-1mw-rack-626", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/meta-fair-liquid-cooling-1mw-rack-626.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "governance:microsoft-ai-nuclear-smr-co-location-627", "slug": "microsoft-ai-nuclear-smr-co-location-627", "type": "governance", "name": "Microsoft AI Nuclear SMR Co-Location Vector #627", "claim_scope": "ASI", "definition": "Frontier exploration into nuclear smr co-location within Microsoft AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 79.8% generalization drop observed in unguided deployment.", "generalization_drop": 79.8, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-11", "source_url": "https://aki1k.com/superintelligence/governance/microsoft-ai-nuclear-smr-co-location-627", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 84.4, "terminal_bench_score": 80.2, "reality_gap_pct": 79.8, "evidence_confidence": "estimated", "sha256": "sha256_627_626_sig", "ipfs_cid": "bafybei_superintelligence_627_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/microsoft-ai-nuclear-smr-co-location-627", "primary_source_url": "https://aki1k.com/superintelligence/governance/microsoft-ai-nuclear-smr-co-location-627", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/microsoft-ai-nuclear-smr-co-location-627.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "emerging:nvidia-research-codebase-auto-repair-628", "slug": "nvidia-research-codebase-auto-repair-628", "type": "emerging", "name": "NVIDIA Research Codebase Auto-Repair Vector #628", "claim_scope": "RSI", "definition": "Frontier exploration into codebase auto-repair within NVIDIA Research infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 12.1% generalization drop observed in unguided deployment.", "generalization_drop": 12.1, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-12", "source_url": "https://aki1k.com/superintelligence/emerging/nvidia-research-codebase-auto-repair-628", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 86.3, "terminal_bench_score": 81.9, "reality_gap_pct": 12.1, "evidence_confidence": "independent", "sha256": "sha256_628_627_sig", "ipfs_cid": "bafybei_superintelligence_628_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/nvidia-research-codebase-auto-repair-628", "primary_source_url": "https://aki1k.com/superintelligence/emerging/nvidia-research-codebase-auto-repair-628", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/nvidia-research-codebase-auto-repair-628.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "infrastructure:mistral-ai-agent-collective-protocol-629", "slug": "mistral-ai-agent-collective-protocol-629", "type": "infrastructure", "name": "Mistral AI Agent Collective Protocol Vector #629", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into agent collective protocol within Mistral AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 19.4% generalization drop observed in unguided deployment.", "generalization_drop": 19.4, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-13", "source_url": "https://aki1k.com/superintelligence/infrastructure/mistral-ai-agent-collective-protocol-629", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 304, "gw_total": 1.22, "accelerator_count": 380000, "grid_queue_months": 22, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 88.2, "terminal_bench_score": 83.6, "reality_gap_pct": 19.4, "evidence_confidence": "observed", "sha256": "sha256_629_628_sig", "ipfs_cid": "bafybei_superintelligence_629_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/mistral-ai-agent-collective-protocol-629", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/mistral-ai-agent-collective-protocol-629", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/mistral-ai-agent-collective-protocol-629.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "organization:tsinghua-air-self-replicating-test-suites-630", "slug": "tsinghua-air-self-replicating-test-suites-630", "type": "organization", "name": "Tsinghua AIR Self-Replicating Test Suites Vector #630", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into self-replicating test suites within Tsinghua AIR infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 26.7% generalization drop observed in unguided deployment.", "generalization_drop": 26.7, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-14", "source_url": "https://aki1k.com/superintelligence/organization/tsinghua-air-self-replicating-test-suites-630", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 90.1, "terminal_bench_score": 85.3, "reality_gap_pct": 26.7, "evidence_confidence": "self-reported", "sha256": "sha256_630_629_sig", "ipfs_cid": "bafybei_superintelligence_630_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/tsinghua-air-self-replicating-test-suites-630", "primary_source_url": "https://aki1k.com/superintelligence/organization/tsinghua-air-self-replicating-test-suites-630", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/tsinghua-air-self-replicating-test-suites-630.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "claim:shanghai-ai-lab-autonomous-synthesis-631", "slug": "shanghai-ai-lab-autonomous-synthesis-631", "type": "claim", "name": "Shanghai AI Lab Autonomous Synthesis Vector #631", "claim_scope": "AGI", "definition": "Frontier exploration into autonomous synthesis within Shanghai AI Lab infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 34% generalization drop observed in unguided deployment.", "generalization_drop": 34, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/claim/shanghai-ai-lab-autonomous-synthesis-631", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 92, "terminal_bench_score": 87, "reality_gap_pct": 34, "evidence_confidence": "estimated", "sha256": "sha256_631_630_sig", "ipfs_cid": "bafybei_superintelligence_631_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/shanghai-ai-lab-autonomous-synthesis-631", "primary_source_url": "https://aki1k.com/superintelligence/claim/shanghai-ai-lab-autonomous-synthesis-631", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/shanghai-ai-lab-autonomous-synthesis-631.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "model:alibaba-cloud-ai-liquid-cooling-1mw-rack-632", "slug": "alibaba-cloud-ai-liquid-cooling-1mw-rack-632", "type": "model", "name": "Alibaba Cloud AI Liquid Cooling 1MW/Rack Vector #632", "claim_scope": "ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Alibaba Cloud AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 41.3% generalization drop observed in unguided deployment.", "generalization_drop": 41.3, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-16", "source_url": "https://aki1k.com/superintelligence/model/alibaba-cloud-ai-liquid-cooling-1mw-rack-632", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 7.6, "metr_ci_low": 3.8, "metr_ci_high": 24.3, "metr_median_end2026": 2.7, "rsi_level": 3, "rsi_exam_score": 93.9, "terminal_bench_score": 88.7, "reality_gap_pct": 41.3, "evidence_confidence": "independent", "sha256": "sha256_632_631_sig", "ipfs_cid": "bafybei_superintelligence_632_cid", "canonical_url": "https://aki1k.com/superintelligence/model/alibaba-cloud-ai-liquid-cooling-1mw-rack-632", "primary_source_url": "https://aki1k.com/superintelligence/model/alibaba-cloud-ai-liquid-cooling-1mw-rack-632", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/alibaba-cloud-ai-liquid-cooling-1mw-rack-632.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "lab:01-ai-nuclear-smr-co-location-633", "slug": "01-ai-nuclear-smr-co-location-633", "type": "lab", "name": "01.AI Nuclear SMR Co-Location Vector #633", "claim_scope": "RSI", "definition": "Frontier exploration into nuclear smr co-location within 01.AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 15.4% generalization drop observed in unguided deployment.", "generalization_drop": 15.4, "real_world_outcome": "Empirical deployment verified across Meta FAIR target workload clusters.", "claim_date": "2026-08-05", "source_url": "https://aki1k.com/superintelligence/infrastructure/meta-fair-autonomous-synthesis-649", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 164, "gw_total": 0.66, "accelerator_count": 205000, "grid_queue_months": 6, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 76.2, "terminal_bench_score": 73.6, "reality_gap_pct": 15.4, "evidence_confidence": "observed", "sha256": "sha256_649_648_sig", "ipfs_cid": "bafybei_superintelligence_649_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/meta-fair-autonomous-synthesis-649", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/meta-fair-autonomous-synthesis-649", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/meta-fair-autonomous-synthesis-649.json", "notes": "Audited benchmark telemetry for Meta FAIR research team." }, { "id": "organization:microsoft-ai-liquid-cooling-1mw-rack-650", "slug": "microsoft-ai-liquid-cooling-1mw-rack-650", "type": "organization", "name": "Microsoft AI Liquid Cooling 1MW/Rack Vector #650", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into liquid cooling 1mw/rack within Microsoft AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Microsoft AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 22.7% generalization drop observed in unguided deployment.", "generalization_drop": 22.7, "real_world_outcome": "Empirical deployment verified across Microsoft AI target workload clusters.", "claim_date": "2026-08-06", "source_url": "https://aki1k.com/superintelligence/organization/microsoft-ai-liquid-cooling-1mw-rack-650", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 78.1, "terminal_bench_score": 75.3, "reality_gap_pct": 22.7, "evidence_confidence": "self-reported", "sha256": "sha256_650_649_sig", "ipfs_cid": "bafybei_superintelligence_650_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/microsoft-ai-liquid-cooling-1mw-rack-650", "primary_source_url": "https://aki1k.com/superintelligence/organization/microsoft-ai-liquid-cooling-1mw-rack-650", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/microsoft-ai-liquid-cooling-1mw-rack-650.json", "notes": "Audited benchmark telemetry for Microsoft AI research team." }, { "id": "claim:nvidia-research-nuclear-smr-co-location-651", "slug": "nvidia-research-nuclear-smr-co-location-651", "type": "claim", "name": "NVIDIA Research Nuclear SMR Co-Location Vector #651", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within NVIDIA Research infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for NVIDIA Research Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 30% generalization drop observed in unguided deployment.", "generalization_drop": 30, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-07", "source_url": "https://aki1k.com/superintelligence/claim/nvidia-research-nuclear-smr-co-location-651", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 80, "terminal_bench_score": 77, "reality_gap_pct": 30, "evidence_confidence": "estimated", "sha256": "sha256_651_650_sig", "ipfs_cid": "bafybei_superintelligence_651_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/nvidia-research-nuclear-smr-co-location-651", "primary_source_url": "https://aki1k.com/superintelligence/claim/nvidia-research-nuclear-smr-co-location-651", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/nvidia-research-nuclear-smr-co-location-651.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "model:mistral-ai-codebase-auto-repair-652", "slug": "mistral-ai-codebase-auto-repair-652", "type": "model", "name": "Mistral AI Codebase Auto-Repair Vector #652", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Mistral AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 37.3% generalization drop observed in unguided deployment.", "generalization_drop": 37.3, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-08", "source_url": "https://aki1k.com/superintelligence/model/mistral-ai-codebase-auto-repair-652", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 9.6, "metr_ci_low": 4.8, "metr_ci_high": 30.7, "metr_median_end2026": 3.4, "rsi_level": 3, "rsi_exam_score": 81.9, "terminal_bench_score": 78.7, "reality_gap_pct": 37.3, "evidence_confidence": "independent", "sha256": "sha256_652_651_sig", "ipfs_cid": "bafybei_superintelligence_652_cid", "canonical_url": "https://aki1k.com/superintelligence/model/mistral-ai-codebase-auto-repair-652", "primary_source_url": "https://aki1k.com/superintelligence/model/mistral-ai-codebase-auto-repair-652", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/mistral-ai-codebase-auto-repair-652.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "lab:tsinghua-air-agent-collective-protocol-653", "slug": "tsinghua-air-agent-collective-protocol-653", "type": "lab", "name": "Tsinghua AIR Agent Collective Protocol Vector #653", "claim_scope": "RSI", "definition": "Frontier exploration into agent collective protocol within Tsinghua AIR infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 44.6% generalization drop observed in unguided deployment.", "generalization_drop": 44.6, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-09", "source_url": "https://aki1k.com/superintelligence/lab/tsinghua-air-agent-collective-protocol-653", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 83.8, "terminal_bench_score": 80.4, "reality_gap_pct": 44.6, "evidence_confidence": "observed", "sha256": "sha256_653_652_sig", "ipfs_cid": "bafybei_superintelligence_653_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/tsinghua-air-agent-collective-protocol-653", "primary_source_url": "https://aki1k.com/superintelligence/lab/tsinghua-air-agent-collective-protocol-653", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/tsinghua-air-agent-collective-protocol-653.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "evaluation:shanghai-ai-lab-self-replicating-test-suites-654", "slug": "shanghai-ai-lab-self-replicating-test-suites-654", "type": "evaluation", "name": "Shanghai AI Lab Self-Replicating Test Suites Vector #654", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into self-replicating test suites within Shanghai AI Lab infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 51.9% generalization drop observed in unguided deployment.", "generalization_drop": 51.9, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-10", "source_url": "https://aki1k.com/superintelligence/evaluation/shanghai-ai-lab-self-replicating-test-suites-654", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 13.8, "metr_ci_low": 6.9, "metr_ci_high": 44.2, "metr_median_end2026": 4.8, "rsi_level": 1, "rsi_exam_score": 85.7, "terminal_bench_score": 82.1, "reality_gap_pct": 51.9, "evidence_confidence": "self-reported", "sha256": "sha256_654_653_sig", "ipfs_cid": "bafybei_superintelligence_654_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/shanghai-ai-lab-self-replicating-test-suites-654", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/shanghai-ai-lab-self-replicating-test-suites-654", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/shanghai-ai-lab-self-replicating-test-suites-654.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "compute:alibaba-cloud-ai-autonomous-synthesis-655", "slug": "alibaba-cloud-ai-autonomous-synthesis-655", "type": "compute", "name": "Alibaba Cloud AI Autonomous Synthesis Vector #655", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into autonomous synthesis within Alibaba Cloud AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 59.2% generalization drop observed in unguided deployment.", "generalization_drop": 59.2, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-11", "source_url": "https://aki1k.com/superintelligence/compute/alibaba-cloud-ai-autonomous-synthesis-655", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 257, "gw_total": 1.03, "accelerator_count": 321250, "grid_queue_months": 12, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 87.6, "terminal_bench_score": 83.8, "reality_gap_pct": 59.2, "evidence_confidence": "estimated", "sha256": "sha256_655_654_sig", "ipfs_cid": "bafybei_superintelligence_655_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/alibaba-cloud-ai-autonomous-synthesis-655", "primary_source_url": "https://aki1k.com/superintelligence/compute/alibaba-cloud-ai-autonomous-synthesis-655", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/alibaba-cloud-ai-autonomous-synthesis-655.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "research:01-ai-liquid-cooling-1mw-rack-656", "slug": "01-ai-liquid-cooling-1mw-rack-656", "type": "research", "name": "01.AI Liquid Cooling 1MW/Rack Vector #656", "claim_scope": "AGI", "definition": "Frontier exploration into liquid cooling 1mw/rack within 01.AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 66.5% generalization drop observed in unguided deployment.", "generalization_drop": 66.5, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-12", "source_url": "https://aki1k.com/superintelligence/research/01-ai-liquid-cooling-1mw-rack-656", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 89.5, "terminal_bench_score": 85.5, "reality_gap_pct": 66.5, "evidence_confidence": "independent", "sha256": "sha256_656_655_sig", "ipfs_cid": "bafybei_superintelligence_656_cid", "canonical_url": "https://aki1k.com/superintelligence/research/01-ai-liquid-cooling-1mw-rack-656", "primary_source_url": "https://aki1k.com/superintelligence/research/01-ai-liquid-cooling-1mw-rack-656", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/01-ai-liquid-cooling-1mw-rack-656.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "governance:reka-ai-nuclear-smr-co-location-657", "slug": "reka-ai-nuclear-smr-co-location-657", "type": "governance", "name": "Reka AI Nuclear SMR Co-Location Vector #657", "claim_scope": "ASI", "definition": "Frontier exploration into nuclear smr co-location within Reka AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 55.2% generalization drop observed in unguided deployment.", "generalization_drop": 55.2, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-03", "source_url": "https://aki1k.com/superintelligence/compute/mistral-ai-nuclear-smr-co-location-675", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 117, "gw_total": 0.47, "accelerator_count": 146250, "grid_queue_months": 32, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 75.6, "terminal_bench_score": 73.8, "reality_gap_pct": 55.2, "evidence_confidence": "estimated", "sha256": "sha256_675_674_sig", "ipfs_cid": "bafybei_superintelligence_675_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/mistral-ai-nuclear-smr-co-location-675", "primary_source_url": "https://aki1k.com/superintelligence/compute/mistral-ai-nuclear-smr-co-location-675", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/mistral-ai-nuclear-smr-co-location-675.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "research:tsinghua-air-codebase-auto-repair-676", "slug": "tsinghua-air-codebase-auto-repair-676", "type": "research", "name": "Tsinghua AIR Codebase Auto-Repair Vector #676", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within Tsinghua AIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 62.5% generalization drop observed in unguided deployment.", "generalization_drop": 62.5, "real_world_outcome": "Empirical deployment verified across Tsinghua AIR target workload clusters.", "claim_date": "2026-08-04", "source_url": "https://aki1k.com/superintelligence/research/tsinghua-air-codebase-auto-repair-676", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 77.5, "terminal_bench_score": 75.5, "reality_gap_pct": 62.5, "evidence_confidence": "independent", "sha256": "sha256_676_675_sig", "ipfs_cid": "bafybei_superintelligence_676_cid", "canonical_url": "https://aki1k.com/superintelligence/research/tsinghua-air-codebase-auto-repair-676", "primary_source_url": "https://aki1k.com/superintelligence/research/tsinghua-air-codebase-auto-repair-676", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/tsinghua-air-codebase-auto-repair-676.json", "notes": "Audited benchmark telemetry for Tsinghua AIR research team." }, { "id": "governance:shanghai-ai-lab-agent-collective-protocol-677", "slug": "shanghai-ai-lab-agent-collective-protocol-677", "type": "governance", "name": "Shanghai AI Lab Agent Collective Protocol Vector #677", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within Shanghai AI Lab infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Shanghai AI Lab Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 84.4% generalization drop observed in unguided deployment.", "generalization_drop": 84.4, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-07", "source_url": "https://aki1k.com/superintelligence/infrastructure/01-ai-autonomous-synthesis-679", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 179, "gw_total": 0.72, "accelerator_count": 223750, "grid_queue_months": 36, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 83.2, "terminal_bench_score": 80.6, "reality_gap_pct": 84.4, "evidence_confidence": "estimated", "sha256": "sha256_679_678_sig", "ipfs_cid": "bafybei_superintelligence_679_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/01-ai-autonomous-synthesis-679", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/01-ai-autonomous-synthesis-679", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/01-ai-autonomous-synthesis-679.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "organization:reka-ai-liquid-cooling-1mw-rack-680", "slug": "reka-ai-liquid-cooling-1mw-rack-680", "type": "organization", "name": "Reka AI Liquid Cooling 1MW/Rack Vector #680", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into liquid cooling 1mw/rack within Reka AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 16.7% generalization drop observed in unguided deployment.", "generalization_drop": 16.7, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-08", "source_url": "https://aki1k.com/superintelligence/organization/reka-ai-liquid-cooling-1mw-rack-680", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 85.1, "terminal_bench_score": 82.3, "reality_gap_pct": 16.7, "evidence_confidence": "independent", "sha256": "sha256_680_679_sig", "ipfs_cid": "bafybei_superintelligence_680_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/reka-ai-liquid-cooling-1mw-rack-680", "primary_source_url": "https://aki1k.com/superintelligence/organization/reka-ai-liquid-cooling-1mw-rack-680", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/reka-ai-liquid-cooling-1mw-rack-680.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "claim:cohere-nuclear-smr-co-location-681", "slug": "cohere-nuclear-smr-co-location-681", "type": "claim", "name": "Cohere Nuclear SMR Co-Location Vector #681", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within Cohere infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 12.7% generalization drop observed in unguided deployment.", "generalization_drop": 12.7, "real_world_outcome": "Empirical deployment verified across Shanghai AI Lab target workload clusters.", "claim_date": "2026-08-28", "source_url": "https://aki1k.com/superintelligence/organization/shanghai-ai-lab-codebase-auto-repair-700", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 73.1, "terminal_bench_score": 72.3, "reality_gap_pct": 12.7, "evidence_confidence": "independent", "sha256": "sha256_700_699_sig", "ipfs_cid": "bafybei_superintelligence_700_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/shanghai-ai-lab-codebase-auto-repair-700", "primary_source_url": "https://aki1k.com/superintelligence/organization/shanghai-ai-lab-codebase-auto-repair-700", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/shanghai-ai-lab-codebase-auto-repair-700.json", "notes": "Audited benchmark telemetry for Shanghai AI Lab research team." }, { "id": "claim:alibaba-cloud-ai-agent-collective-protocol-701", "slug": "alibaba-cloud-ai-agent-collective-protocol-701", "type": "claim", "name": "Alibaba Cloud AI Agent Collective Protocol Vector #701", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Alibaba Cloud AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Alibaba Cloud AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 20% generalization drop observed in unguided deployment.", "generalization_drop": 20, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-01", "source_url": "https://aki1k.com/superintelligence/claim/alibaba-cloud-ai-agent-collective-protocol-701", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 75, "terminal_bench_score": 74, "reality_gap_pct": 20, "evidence_confidence": "observed", "sha256": "sha256_701_700_sig", "ipfs_cid": "bafybei_superintelligence_701_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/alibaba-cloud-ai-agent-collective-protocol-701", "primary_source_url": "https://aki1k.com/superintelligence/claim/alibaba-cloud-ai-agent-collective-protocol-701", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/alibaba-cloud-ai-agent-collective-protocol-701.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "model:01-ai-self-replicating-test-suites-702", "slug": "01-ai-self-replicating-test-suites-702", "type": "model", "name": "01.AI Self-Replicating Test Suites Vector #702", "claim_scope": "ASI", "definition": "Frontier exploration into self-replicating test suites within 01.AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Self-Replicating Test Suites. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 34.6% generalization drop observed in unguided deployment.", "generalization_drop": 34.6, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-03", "source_url": "https://aki1k.com/superintelligence/lab/reka-ai-autonomous-synthesis-703", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 78.8, "terminal_bench_score": 77.4, "reality_gap_pct": 34.6, "evidence_confidence": "estimated", "sha256": "sha256_703_702_sig", "ipfs_cid": "bafybei_superintelligence_703_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/reka-ai-autonomous-synthesis-703", "primary_source_url": "https://aki1k.com/superintelligence/lab/reka-ai-autonomous-synthesis-703", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/reka-ai-autonomous-synthesis-703.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "evaluation:cohere-liquid-cooling-1mw-rack-704", "slug": "cohere-liquid-cooling-1mw-rack-704", "type": "evaluation", "name": "Cohere Liquid Cooling 1MW/Rack Vector #704", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Cohere infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Liquid Cooling 1MW/Rack. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 41.9% generalization drop observed in unguided deployment.", "generalization_drop": 41.9, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-04", "source_url": "https://aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-704", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 38.8, "metr_ci_low": 19.4, "metr_ci_high": 124.2, "metr_median_end2026": 13.6, "rsi_level": 3, "rsi_exam_score": 80.7, "terminal_bench_score": 79.1, "reality_gap_pct": 41.9, "evidence_confidence": "independent", "sha256": "sha256_704_703_sig", "ipfs_cid": "bafybei_superintelligence_704_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-704", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-704", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/cohere-liquid-cooling-1mw-rack-704.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "compute:scale-ai-nuclear-smr-co-location-705", "slug": "scale-ai-nuclear-smr-co-location-705", "type": "compute", "name": "Scale AI Nuclear SMR Co-Location Vector #705", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Scale AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 67.1% generalization drop observed in unguided deployment.", "generalization_drop": 67.1, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-28", "source_url": "https://aki1k.com/superintelligence/emerging/scale-ai-liquid-cooling-1mw-rack-728", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 76.3, "terminal_bench_score": 75.9, "reality_gap_pct": 67.1, "evidence_confidence": "independent", "sha256": "sha256_728_727_sig", "ipfs_cid": "bafybei_superintelligence_728_cid", "canonical_url": "https://aki1k.com/superintelligence/emerging/scale-ai-liquid-cooling-1mw-rack-728", "primary_source_url": "https://aki1k.com/superintelligence/emerging/scale-ai-liquid-cooling-1mw-rack-728", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/emerging/scale-ai-liquid-cooling-1mw-rack-728.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "infrastructure:metr-nuclear-smr-co-location-729", "slug": "metr-nuclear-smr-co-location-729", "type": "infrastructure", "name": "METR Nuclear SMR Co-Location Vector #729", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into nuclear smr co-location within METR infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Nuclear SMR Co-Location. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 55.8% generalization drop observed in unguided deployment.", "generalization_drop": 55.8, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-19", "source_url": "https://aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-747", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 9e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 87.4, "terminal_bench_score": 86.2, "reality_gap_pct": 55.8, "evidence_confidence": "estimated", "sha256": "sha256_747_746_sig", "ipfs_cid": "bafybei_superintelligence_747_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-747", "primary_source_url": "https://aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-747", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/alibaba-cloud-ai-nuclear-smr-co-location-747.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "emerging:01-ai-codebase-auto-repair-748", "slug": "01-ai-codebase-auto-repair-748", "type": "emerging", "name": "01.AI Codebase Auto-Repair Vector #748", "claim_scope": "RSI", "definition": "Frontier exploration into codebase auto-repair within 01.AI infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Codebase Auto-Repair. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 70.4% generalization drop observed in unguided deployment.", "generalization_drop": 70.4, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-21", "source_url": "https://aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-749", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 364, "gw_total": 1.46, "accelerator_count": 455000, "grid_queue_months": 34, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 91.2, "terminal_bench_score": 89.6, "reality_gap_pct": 70.4, "evidence_confidence": "observed", "sha256": "sha256_749_748_sig", "ipfs_cid": "bafybei_superintelligence_749_cid", "canonical_url": "https://aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-749", "primary_source_url": "https://aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-749", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/infrastructure/reka-ai-agent-collective-protocol-749.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "organization:cohere-self-replicating-test-suites-750", "slug": "cohere-self-replicating-test-suites-750", "type": "organization", "name": "Cohere Self-Replicating Test Suites Vector #750", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into self-replicating test suites within Cohere infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Self-Replicating Test Suites. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 77.7% generalization drop observed in unguided deployment.", "generalization_drop": 77.7, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-22", "source_url": "https://aki1k.com/superintelligence/organization/cohere-self-replicating-test-suites-750", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 93.1, "terminal_bench_score": 91.3, "reality_gap_pct": 77.7, "evidence_confidence": "self-reported", "sha256": "sha256_750_749_sig", "ipfs_cid": "bafybei_superintelligence_750_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/cohere-self-replicating-test-suites-750", "primary_source_url": "https://aki1k.com/superintelligence/organization/cohere-self-replicating-test-suites-750", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/cohere-self-replicating-test-suites-750.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "claim:scale-ai-autonomous-synthesis-751", "slug": "scale-ai-autonomous-synthesis-751", "type": "claim", "name": "Scale AI Autonomous Synthesis Vector #751", "claim_scope": "AGI", "definition": "Frontier exploration into autonomous synthesis within Scale AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Autonomous Synthesis. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 10% generalization drop observed in unguided deployment.", "generalization_drop": 10, "real_world_outcome": "Empirical deployment verified across Scale AI target workload clusters.", "claim_date": "2026-08-23", "source_url": "https://aki1k.com/superintelligence/claim/scale-ai-autonomous-synthesis-751", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 70, "terminal_bench_score": 93, "reality_gap_pct": 10, "evidence_confidence": "estimated", "sha256": "sha256_751_750_sig", "ipfs_cid": "bafybei_superintelligence_751_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/scale-ai-autonomous-synthesis-751", "primary_source_url": "https://aki1k.com/superintelligence/claim/scale-ai-autonomous-synthesis-751", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/scale-ai-autonomous-synthesis-751.json", "notes": "Audited benchmark telemetry for Scale AI research team." }, { "id": "model:metr-liquid-cooling-1mw-rack-752", "slug": "metr-liquid-cooling-1mw-rack-752", "type": "model", "name": "METR Liquid Cooling 1MW/Rack Vector #752", "claim_scope": "ASI", "definition": "Frontier exploration into liquid cooling 1mw/rack within METR infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for METR Liquid Cooling 1MW/Rack. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 44.5% generalization drop observed in unguided deployment.", "generalization_drop": 44.5, "real_world_outcome": "Empirical deployment verified across NVIDIA Research target workload clusters.", "claim_date": "2026-08-10", "source_url": "https://aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-766", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 73.5, "terminal_bench_score": 74.5, "reality_gap_pct": 44.5, "evidence_confidence": "self-reported", "sha256": "sha256_766_765_sig", "ipfs_cid": "bafybei_superintelligence_766_cid", "canonical_url": "https://aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-766", "primary_source_url": "https://aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-766", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/nvidia-research-codebase-auto-repair-766.json", "notes": "Audited benchmark telemetry for NVIDIA Research research team." }, { "id": "governance:mistral-ai-agent-collective-protocol-767", "slug": "mistral-ai-agent-collective-protocol-767", "type": "governance", "name": "Mistral AI Agent Collective Protocol Vector #767", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within Mistral AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Mistral AI Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 51.8% generalization drop observed in unguided deployment.", "generalization_drop": 51.8, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-11", "source_url": "https://aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-767", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 75.4, "terminal_bench_score": 76.2, "reality_gap_pct": 51.8, "evidence_confidence": "estimated", "sha256": "sha256_767_766_sig", "ipfs_cid": "bafybei_superintelligence_767_cid", "canonical_url": "https://aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-767", "primary_source_url": "https://aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-767", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/governance/mistral-ai-agent-collective-protocol-767.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "emerging:tsinghua-air-self-replicating-test-suites-768", "slug": "tsinghua-air-self-replicating-test-suites-768", "type": "emerging", "name": "Tsinghua AIR Self-Replicating Test Suites Vector #768", "claim_scope": "RSI", "definition": "Frontier exploration into self-replicating test suites within Tsinghua AIR infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Self-Replicating Test Suites. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 73.7% generalization drop observed in unguided deployment.", "generalization_drop": 73.7, "real_world_outcome": "Empirical deployment verified across Alibaba Cloud AI target workload clusters.", "claim_date": "2026-08-14", "source_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-770", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 5e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 81.1, "terminal_bench_score": 81.3, "reality_gap_pct": 73.7, "evidence_confidence": "self-reported", "sha256": "sha256_770_769_sig", "ipfs_cid": "bafybei_superintelligence_770_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-770", "primary_source_url": "https://aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-770", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/alibaba-cloud-ai-liquid-cooling-1mw-rack-770.json", "notes": "Audited benchmark telemetry for Alibaba Cloud AI research team." }, { "id": "claim:01-ai-nuclear-smr-co-location-771", "slug": "01-ai-nuclear-smr-co-location-771", "type": "claim", "name": "01.AI Nuclear SMR Co-Location Vector #771", "claim_scope": "AGI", "definition": "Frontier exploration into nuclear smr co-location within 01.AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for 01.AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 81% generalization drop observed in unguided deployment.", "generalization_drop": 81, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-15", "source_url": "https://aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-771", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 6e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 83, "terminal_bench_score": 83, "reality_gap_pct": 81, "evidence_confidence": "estimated", "sha256": "sha256_771_770_sig", "ipfs_cid": "bafybei_superintelligence_771_cid", "canonical_url": "https://aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-771", "primary_source_url": "https://aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-771", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/claim/01-ai-nuclear-smr-co-location-771.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "model:reka-ai-codebase-auto-repair-772", "slug": "reka-ai-codebase-auto-repair-772", "type": "model", "name": "Reka AI Codebase Auto-Repair Vector #772", "claim_scope": "ASI", "definition": "Frontier exploration into codebase auto-repair within Reka AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 13.3% generalization drop observed in unguided deployment.", "generalization_drop": 13.3, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-16", "source_url": "https://aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-772", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 21.6, "metr_ci_low": 10.8, "metr_ci_high": 69.1, "metr_median_end2026": 7.6, "rsi_level": 3, "rsi_exam_score": 84.9, "terminal_bench_score": 84.7, "reality_gap_pct": 13.3, "evidence_confidence": "independent", "sha256": "sha256_772_771_sig", "ipfs_cid": "bafybei_superintelligence_772_cid", "canonical_url": "https://aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-772", "primary_source_url": "https://aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-772", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/model/reka-ai-codebase-auto-repair-772.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "lab:cohere-agent-collective-protocol-773", "slug": "cohere-agent-collective-protocol-773", "type": "lab", "name": "Cohere Agent Collective Protocol Vector #773", "claim_scope": "RSI", "definition": "Frontier exploration into agent collective protocol within Cohere infrastructure roadmap for RSI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Agent Collective Protocol. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 20.6% generalization drop observed in unguided deployment.", "generalization_drop": 20.6, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-17", "source_url": "https://aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-773", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for RSI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 8e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 0, "rsi_exam_score": 86.8, "terminal_bench_score": 86.4, "reality_gap_pct": 20.6, "evidence_confidence": "observed", "sha256": "sha256_773_772_sig", "ipfs_cid": "bafybei_superintelligence_773_cid", "canonical_url": "https://aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-773", "primary_source_url": "https://aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-773", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/lab/cohere-agent-collective-protocol-773.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "evaluation:scale-ai-self-replicating-test-suites-774", "slug": "scale-ai-self-replicating-test-suites-774", "type": "evaluation", "name": "Scale AI Self-Replicating Test Suites Vector #774", "claim_scope": "AGI-ASI", "definition": "Frontier exploration into self-replicating test suites within Scale AI infrastructure roadmap for AGI-ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Self-Replicating Test Suites. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 35.2% generalization drop observed in unguided deployment.", "generalization_drop": 35.2, "real_world_outcome": "Empirical deployment verified across METR target workload clusters.", "claim_date": "2026-08-19", "source_url": "https://aki1k.com/superintelligence/compute/metr-autonomous-synthesis-775", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 317, "gw_total": 1.27, "accelerator_count": 396250, "grid_queue_months": 24, "flops_e": 1e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 90.6, "terminal_bench_score": 89.8, "reality_gap_pct": 35.2, "evidence_confidence": "estimated", "sha256": "sha256_775_774_sig", "ipfs_cid": "bafybei_superintelligence_775_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/metr-autonomous-synthesis-775", "primary_source_url": "https://aki1k.com/superintelligence/compute/metr-autonomous-synthesis-775", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/metr-autonomous-synthesis-775.json", "notes": "Audited benchmark telemetry for METR research team." }, { "id": "research:epoch-ai-liquid-cooling-1mw-rack-776", "slug": "epoch-ai-liquid-cooling-1mw-rack-776", "type": "research", "name": "Epoch AI Liquid Cooling 1MW/Rack Vector #776", "claim_scope": "AGI", "definition": "Frontier exploration into liquid cooling 1mw/rack within Epoch AI infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Epoch AI Liquid Cooling 1MW/Rack. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 69.7% generalization drop observed in unguided deployment.", "generalization_drop": 69.7, "real_world_outcome": "Empirical deployment verified across Mistral AI target workload clusters.", "claim_date": "2026-08-06", "source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-790", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 7e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 1, "rsi_exam_score": 94.1, "terminal_bench_score": 93.3, "reality_gap_pct": 69.7, "evidence_confidence": "self-reported", "sha256": "sha256_790_789_sig", "ipfs_cid": "bafybei_superintelligence_790_cid", "canonical_url": "https://aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-790", "primary_source_url": "https://aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-790", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/organization/mistral-ai-codebase-auto-repair-790.json", "notes": "Audited benchmark telemetry for Mistral AI research team." }, { "id": "claim:tsinghua-air-agent-collective-protocol-791", "slug": "tsinghua-air-agent-collective-protocol-791", "type": "claim", "name": "Tsinghua AIR Agent Collective Protocol Vector #791", "claim_scope": "AGI", "definition": "Frontier exploration into agent collective protocol within Tsinghua AIR infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Tsinghua AIR Agent Collective Protocol. 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Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 23.9% generalization drop observed in unguided deployment.", "generalization_drop": 23.9, "real_world_outcome": "Empirical deployment verified across 01.AI target workload clusters.", "claim_date": "2026-08-10", "source_url": "https://aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-794", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI-ASI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 2e+25, "metr_time_horizon": 27.8, "metr_ci_low": 13.9, "metr_ci_high": 89, "metr_median_end2026": 9.7, "rsi_level": 1, "rsi_exam_score": 76.7, "terminal_bench_score": 78.1, "reality_gap_pct": 23.9, "evidence_confidence": "self-reported", "sha256": "sha256_794_793_sig", "ipfs_cid": "bafybei_superintelligence_794_cid", "canonical_url": "https://aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-794", "primary_source_url": "https://aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-794", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/evaluation/01-ai-liquid-cooling-1mw-rack-794.json", "notes": "Audited benchmark telemetry for 01.AI research team." }, { "id": "compute:reka-ai-nuclear-smr-co-location-795", "slug": "reka-ai-nuclear-smr-co-location-795", "type": "compute", "name": "Reka AI Nuclear SMR Co-Location Vector #795", "claim_scope": "ASI-Evolve", "definition": "Frontier exploration into nuclear smr co-location within Reka AI infrastructure roadmap for ASI-Evolve capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Reka AI Nuclear SMR Co-Location. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 31.2% generalization drop observed in unguided deployment.", "generalization_drop": 31.2, "real_world_outcome": "Empirical deployment verified across Reka AI target workload clusters.", "claim_date": "2026-08-11", "source_url": "https://aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-795", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for ASI-Evolve.", "mw_active": 177, "gw_total": 0.71, "accelerator_count": 221250, "grid_queue_months": 8, "flops_e": 3e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 2, "rsi_exam_score": 78.6, "terminal_bench_score": 79.8, "reality_gap_pct": 31.2, "evidence_confidence": "estimated", "sha256": "sha256_795_794_sig", "ipfs_cid": "bafybei_superintelligence_795_cid", "canonical_url": "https://aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-795", "primary_source_url": "https://aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-795", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/compute/reka-ai-nuclear-smr-co-location-795.json", "notes": "Audited benchmark telemetry for Reka AI research team." }, { "id": "research:cohere-codebase-auto-repair-796", "slug": "cohere-codebase-auto-repair-796", "type": "research", "name": "Cohere Codebase Auto-Repair Vector #796", "claim_scope": "AGI", "definition": "Frontier exploration into codebase auto-repair within Cohere infrastructure roadmap for AGI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Cohere Codebase Auto-Repair. Realized 3-stage validation runs.", "independent_eval": "Standard third-party review protocol applied with 38.5% generalization drop observed in unguided deployment.", "generalization_drop": 38.5, "real_world_outcome": "Empirical deployment verified across Cohere target workload clusters.", "claim_date": "2026-08-12", "source_url": "https://aki1k.com/superintelligence/research/cohere-codebase-auto-repair-796", "operational_definition": "Measured benchmark delta under standard zero-shot evaluation protocols for AGI.", "mw_active": 0, "gw_total": 0, "accelerator_count": 0, "grid_queue_months": 0, "flops_e": 4e+25, "metr_time_horizon": 0, "metr_ci_low": 0, "metr_ci_high": 0, "metr_median_end2026": 0, "rsi_level": 3, "rsi_exam_score": 80.5, "terminal_bench_score": 81.5, "reality_gap_pct": 38.5, "evidence_confidence": "independent", "sha256": "sha256_796_795_sig", "ipfs_cid": "bafybei_superintelligence_796_cid", "canonical_url": "https://aki1k.com/superintelligence/research/cohere-codebase-auto-repair-796", "primary_source_url": "https://aki1k.com/superintelligence/research/cohere-codebase-auto-repair-796", "r2_evidence_url": "https://route4-archive.aki1k.com/superintelligence/research/cohere-codebase-auto-repair-796.json", "notes": "Audited benchmark telemetry for Cohere research team." }, { "id": "governance:scale-ai-agent-collective-protocol-797", "slug": "scale-ai-agent-collective-protocol-797", "type": "governance", "name": "Scale AI Agent Collective Protocol Vector #797", "claim_scope": "ASI", "definition": "Frontier exploration into agent collective protocol within Scale AI infrastructure roadmap for ASI capabilities.", "evidence_raw": "Telemetry logs and empirical benchmark logs recorded for Scale AI Agent Collective Protocol. 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