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64,690 candidate doc → node links pending adjudication. Each was auto-generated by cosine similarity ≥ 0.55 between document and prediction embeddings (bge-base-en-v1.5, 768-dim). Showing page 28 of 52, 50 rows by similarity. Adjudicating updates doc_node_links.reviewed=true with the chosen polarity, writes per-link rows to audit_log, and removes the row from this queue. Phase 4 inference will use confirmed corroborates/contradicts links as Bayesian evidence.
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Confirm or label (corroborates / contradicts) all unreviewed links above a similarity threshold in one transaction. Each affected row writes a per-link audit_log entry. Capped at 1,000 links per call. Use Preview first.
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| Sim | Doc | Source | Pred | Domain | Prior | |
|---|---|---|---|---|---|---|
| 0.60 | github_release 2021-07-30 | S_HUMANOID_ENTERPRISE_2028 Humanoid R2: 100K+ enterprise by Nov 2028 | humanoid_deployment | 50% | ||
| 0.60 | github_release 2025-01-29 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.60 | github_release 2020-04-28 | 241_011 By end of 2026, no one will write code manually - it'll be a quaint skill Peter Diamandis | Labor/Jobs | 47% | ||
| 0.60 | github_release 2026-06-08 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.60 | github_release 2026-03-26 | COD_SPC_003 SpaceX completes large-scale Starship vehicle-to-vehicle cryogenic propellant transfer by end 2026 Codex Research Pack | Space | 30% | ||
| 0.60 | github_release 2026-03-16 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.60 | github_release 2026-02-25 | COD_BIO_001 FDA finalizes or materially advances AI-for-drug-submission guidance by end 2026 Codex Research Pack | Biotech/Longevity | 47% | ||
| 0.60 | github_release 2026-03-25 | 242_044 Base AI models becoming commodity; value migrates up the stack Alex Wissner-Gross | AI | 35% | ||
| 0.60 | github_release 2026-02-05 | 238_025 AI computer-use benchmarks (OSWorld, Tbench) have broken through human level Emad Mostaque | AI | 45% | ||
| 0.60 | github_release 2021-11-05 | 230_031 We are in an era of domain collapse — AlphaFold pattern will repeat across many fields starting now. Alex Wissner-Gross | AI | 43% | ||
| 0.60 | github_release 2021-07-16 | CMQ_056 Small Language Model (SLM) optimizations and model-distillation techniques will enable localized humanoid reasoning with extreme power efficiency — embedded AI without cloud dependency. Dario Amodei | AI/Compute | 19% | ||
| 0.60 | github_release 2025-03-11 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2023-08-31 | CMQ_030 In the modern AI pipeline, the CPU no longer merely supports the model — it drives the model (agentic workloads invert historical CPU:GPU ratio). Jensen Huang | AI/Compute | 34% | ||
| 0.60 | github_release 2021-04-28 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2026-05-07 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2024-10-30 | CMQ_044 Future data-center architectures optimized for agentic workflows may require 1:2 or even 2:1 CPU-to-GPU ratio (vs historical 1:12) to prevent GPU idle-waiting. Morgan Stanley | AI/Compute | 65% | ||
| 0.60 | github_release 2024-07-09 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.60 | github_release 2023-12-15 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.60 | github_release 2026-01-07 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 41% | ||
| 0.60 | github_release 2025-09-10 | 237_002 We will see a lot of evolution and many OpenClaw variants emerging very quickly as an early domain being developed. Peter Diamandis | AI | 55% | ||
| 0.60 | github_release 2025-05-02 | SEM_047 At 200,000-GPU scale, orchestration becomes a literal 'battle against entropy' — single cosmic-ray-flipped transistor can derail 100k-GPU training run. Jimmy Ba | AI/Hardware | 71% | ||
| 0.60 | github_release 2025-03-05 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 41% | ||
| 0.60 | github_release 2026-06-04 | 238_071 Future AI models may compress all human knowledge into megabytes via post-transformer breakthroughs Alex Wissner-Gross | AI | 35% | ||
| 0.60 | github_release 2025-03-25 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.60 | github_release 2020-11-06 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.60 | github_release 2020-05-04 | SEM_033 AI is gaining the capability to autonomously conduct original physics research (e.g., GPT-5.2 Pro proved new gluon scattering formulas). Alex Wissner-Gross | AI/Physics | 56% | ||
| 0.60 | github_release 2020-04-28 | 230_040 AI capability/accuracy will improve recursively; output-checking issues will be eliminated quickly. Peter Diamandis | AI | 50% | ||
| 0.60 | github_release 2025-09-24 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2026-04-09 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.60 | github_release 2025-11-24 | 248_038 We will see humanoid robot threats alongside the current Sam Altman backlash. Salim Ismail | Robotics | 34% | ||
| 0.60 | github_release 2025-02-14 | 245_033 Colossal will work to reintroduce all de-extincted species back into their environments Ben Lamm | Biotech/Longevity | 44% | ||
| 0.60 | github_release 2024-09-25 | 234_048 Next major revolutions in foundation models will come from small language models Alex Wissner-Gross | AI | 41% | ||
| 0.60 | github_release 2023-09-26 | CMQ_030 In the modern AI pipeline, the CPU no longer merely supports the model — it drives the model (agentic workloads invert historical CPU:GPU ratio). Jensen Huang | AI/Compute | 34% | ||
| 0.60 | github_release 2022-08-05 | CMQ_044 Future data-center architectures optimized for agentic workflows may require 1:2 or even 2:1 CPU-to-GPU ratio (vs historical 1:12) to prevent GPU idle-waiting. Morgan Stanley | AI/Compute | 65% | ||
| 0.60 | github_release 2022-03-10 | SEM_047 At 200,000-GPU scale, orchestration becomes a literal 'battle against entropy' — single cosmic-ray-flipped transistor can derail 100k-GPU training run. Jimmy Ba | AI/Hardware | 71% | ||
| 0.60 | github_release 2020-05-28 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.60 | github_release 2026-03-06 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.60 | github_release 2025-12-02 | 248_048 AI models will move to a post-binary (sub-one-bit) numerical precision paradigm. Alex Wissner-Gross | AI | 34% | ||
| 0.60 | github_release 2024-10-30 | 229_047 Figure's 3,000 B200 GPU cluster is coming online for Helix pre-training with much larger GPUs planned. Brett Adcock | AI | 77% | ||
| 0.60 | github_release 2024-07-26 | 248_048 AI models will move to a post-binary (sub-one-bit) numerical precision paradigm. Alex Wissner-Gross | AI | 34% | ||
| 0.60 | github_release 2024-07-25 | CMQ_056 Small Language Model (SLM) optimizations and model-distillation techniques will enable localized humanoid reasoning with extreme power efficiency — embedded AI without cloud dependency. Dario Amodei | AI/Compute | 19% | ||
| 0.60 | github_release 2023-10-25 | 239_004 xAI/Grok will catch up and exceed competitors on coding by mid-2026 Elon Musk | AI | 40% | ||
| 0.60 | github_release 2025-10-15 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.60 | github_release 2025-06-10 | 248_022 Deepseek-style hyperdeflation moments from algorithmic innovation will become more frequent but less effective at causing price swings. Alex Wissner-Gross | Markets/Stocks | 42% | ||
| 0.60 | github_release 2025-04-11 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.60 | github_release 2024-02-16 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.60 | github_release 2025-08-27 | CYB_029 Corporate API providers will increasingly restrict third-party agent harnesses (exemplified by Anthropic's April 2026 ban of OpenClaw) — this structural conflict highlights the precarious nature of building autonomous enterprises atop proprietary APIs,... Anthropic | AI | 80% | ||
| 0.60 | github_release 2026-04-26 | CMQ_044 Future data-center architectures optimized for agentic workflows may require 1:2 or even 2:1 CPU-to-GPU ratio (vs historical 1:12) to prevent GPU idle-waiting. Morgan Stanley | AI/Compute | 65% | ||
| 0.60 | github_release 2021-01-29 | CMQ_058 Localized hardware setups (multiple Apple Mac Studios, dedicated 'AI Max 300' silicon) will allow developers to run powerful inference workloads directly on-premises — reducing cloud dependency. Alex Finn | AI/Compute | 59% | ||
| 0.60 | github_release 2020-07-08 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% |