Validations Queue
111,300 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 36 of 62, 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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Bulk auto-confirm by similarity threshold
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 2025-11-21 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.60 | github_release 2025-11-21 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.60 | github_release 2025-10-24 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.60 | github_release 2025-10-09 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.60 | github_release 2025-09-16 | 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 2019-03-15 | CMQ_027 The inference inflection has arrived — industry transitioning from training-dominated capex (2023-2025) to inference-dominated economics (2026+). Jensen Huang | AI/Compute | 92% | ||
| 0.60 | github_release 2024-02-22 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.60 | github_release 2023-05-10 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.60 | github_release 2022-04-28 | 248_032 First-generation neural uploads will be destructive; 2nd-4th generation will be non-destructive. Alex Wissner-Gross | Biotech/Longevity | 42% | ||
| 0.60 | github_release 2021-12-16 | 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 2020-02-05 | 231_015 Next Deep Seek model release will be when Chinese open-weight models catch up to American frontier models. Alex Wissner-Gross | AI | 34% | ||
| 0.60 | github_release 2020-01-23 | 238_009 Recursive self-improvement is already happening now (no longer three years out) Alex Wissner-Gross | AI | 78% | ||
| 0.60 | github_release 2025-11-17 | 238_025 AI computer-use benchmarks (OSWorld, Tbench) have broken through human level Emad Mostaque | AI | 45% | ||
| 0.60 | github_release 2022-08-25 | 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 2021-11-05 | CMQ_010 True AGI requires genuine scientific-discovery capabilities (AlphaFold-class breakthroughs) — brute-force LLM scaling alone is insufficient. Demis Hassabis | AI | 49% | ||
| 0.60 | github_release 2021-09-30 | INF_027 AI infrastructure applied to structural biology will compress drug-development timelines from approximately a decade to weeks — potentially eradicating many major diseases within 10 years. Requires localized high-speed InfiniBand networking inside the DC. Demis Hassabis | Biotech/Longevity | 38% | ||
| 0.60 | github_release 2026-01-13 | 248_038 We will see humanoid robot threats alongside the current Sam Altman backlash. Salim Ismail | Robotics | 34% | ||
| 0.60 | github_release 2025-02-24 | AI_010 The 2026 development landscape has entered the 'Slopacolypse' — AI writes the vast majority of new code, developer manual-coding skills atrophy, and engineering transitions from syntax-writing to high-level architectural prompting and 'vibe coding'. Andrej Karpathy | AI | 90% | ||
| 0.60 | github_release 2025-11-12 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.60 | github_release 2025-10-15 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2024-02-22 | 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 2022-08-05 | 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 2026-05-05 | IND_026 Non-coders and engineers alike must build for 'where the models are going, not where they are today' — 'this is the worst the models will ever be'. Next-generation models will 'eat your scaffolding for breakfast'; manual software configuration, standar... Kevin Weil | Labor/Jobs | 61% | ||
| 0.60 | github_release 2020-10-14 | 229_046 Current Figure robots have 3-5x headroom in speed via existing actuators once software enables it. Brett Adcock | Robotics | 28% | ||
| 0.60 | github_release 2020-10-14 | S_ROBOTAXI_MASS_2030 Robotaxi >10% urban miles by Nov 2030 | robotaxi_deployment | 30% | ||
| 0.60 | github_release 2026-04-17 | INF_009 The first multi-behavior brain-organoid upload is imminent — wetware ('brain organoid') computing has progressed from Pong (2021) to Doom-class simulators (2025), and offers a pathway out of silicon thermal limits at ~20W per brain-equivalent compute. Alex Wissner-Gross | AI | 17% | ||
| 0.60 | github_release 2019-04-05 | 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 2026-03-03 | 239_003 We are currently in AI hard takeoff Elon Musk | AI | 47% | ||
| 0.60 | github_release 2025-12-19 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2024-10-04 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2025-12-02 | 242_044 Base AI models becoming commodity; value migrates up the stack Alex Wissner-Gross | AI | 35% | ||
| 0.60 | github_release 2024-12-31 | 236_028 AI chatbot/AI romance trend growing unfortunately Andrew Yang | Consumer | 51% | ||
| 0.60 | github_release 2024-10-22 | 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 2024-07-25 | 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 2025-04-11 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.60 | github_release 2025-03-05 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.60 | github_release 2026-05-13 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.60 | github_release 2021-06-10 | FUT_003 Superforecaster consensus assigns 0.38% probability to AI-driven human extinction by 2100 vs domain-expert consensus of 3% — ~8x discrepancy per XPT 2022 adversarial collaboration tournament (89 superforecasters + 80 domain experts). Superforecasters m... Superforecaster Community | AI | 100% | ||
| 0.60 | github_release 2026-05-18 | CMQ_015 Algorithmic efficiencies will deliver ~0.5 OOMs per year of additional effective compute through 2027 — pure multiplier on raw FLOPs. Leopold Aschenbrenner | AI | 50% | ||
| 0.60 | github_release 2026-05-18 | CMQ_063 Quantum compute integration with AI optimization algorithms and material-science discovery could drastically accelerate algorithmic efficiencies for Intelligence Explosion — potentially pulling superintelligence timelines closer. Alex Wissner-Gross | Quantum/AI | 15% | ||
| 0.60 | github_release 2021-01-29 | TK01 AGI Capability Plateau (2026-27 Training Stall) | — | 15% | ||
| 0.60 | github_release 2026-06-04 | 240_013 Sam Altman predicts another architecture breakthrough as big as transformers over LSTMs Sam Altman | AI | 41% | ||
| 0.60 | github_release 2020-05-04 | AUT_016 NVIDIA Rubin platform in full production by 2026 — slashes computational cost of generating AI tokens to 1/10 of previous architectures. Autonomous reasoning model 'Alpamayo' shifts self-driving technology from fragile rule-based coding to verifiable l... Jensen Huang | AI | 75% | ||
| 0.60 | github_release 2026-06-10 | 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 2019-07-04 | 234_048 Next major revolutions in foundation models will come from small language models Alex Wissner-Gross | AI | 41% | ||
| 0.60 | github_release 2025-09-16 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.60 | github_release 2022-10-23 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.60 | github_release 2024-08-29 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.60 | github_release 2026-04-20 | 235_010 Plugins/marketplaces will get built into baseline models and won't need to exist independently. Alex Wissner-Gross | AI | 38% | ||
| 0.60 | github_release 2026-04-09 | 248_048 AI models will move to a post-binary (sub-one-bit) numerical precision paradigm. Alex Wissner-Gross | AI | 34% |