Validations Queue
63,896 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 7 of 51, 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 | |
|---|---|---|---|---|---|---|
| 0.65 | github_release 2026-05-28 | 234_012 Anthropic revenue will cross OpenAI revenue in middle of 2026 Peter Diamandis | Markets/Stocks | 67% | ||
| 0.65 | github_release 2026-05-20 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.65 | github_release 2021-06-30 | ROB_013 Research foundations enabling seamless human-robot interaction in complex 3D physical spaces — algorithms translating human natural-language intent directly into complex robotic actuation eliminate hard-coded robotics engineering, allowing systems to g... Jimmy Ba | Robotics | 62% | ||
| 0.65 | github_release 2021-06-30 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.65 | github_release 2025-11-10 | 241_037 Chinese AI strategy will stay open source / open weights Eric Schmidt | AI | 49% | ||
| 0.65 | github_release 2026-04-01 | 238_028 Anthropic plugins will enable market-by-market disruption (could short stocks and announce plugins) Emad Mostaque | Markets/Stocks | 31% | ||
| 0.65 | 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% | ||
| 0.65 | github_release 2026-02-09 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.65 | github_release 2024-07-11 | 246_036 Terafab will deliver 1 terawatt/year AI compute, 50x current global output of 20 gigawatt. Peter Diamandis | AI | 46% | ||
| 0.65 | github_release 2025-04-23 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.65 | github_release 2024-04-24 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.65 | github_release 2021-02-17 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.65 | github_release 2020-01-21 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.65 | github_release 2024-03-01 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.65 | github_release 2025-03-20 | CYB_009 Hardware-software alignment will force widespread foundational-codebase rewrites — exemplified by Midjourney's strategic migration from Google TPU architecture to native GPU framework, enabling hyper-fast personalization, HD generation, and massive par... David Holz | AI | 77% | ||
| 0.65 | github_release 2026-05-26 | 238_025 AI computer-use benchmarks (OSWorld, Tbench) have broken through human level Emad Mostaque | AI | 45% | ||
| 0.65 | github_release 2020-01-21 | 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% | ||
| 0.65 | github_release 2022-02-15 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.65 | github_release 2025-10-07 | 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% | ||
| 0.64 | github_release 2025-11-19 | 246_047 Anthropic ARR reached $30B, surpassing OpenAI's $24-25B. Peter Diamandis | AI | 76% | ||
| 0.64 | github_release 2025-11-19 | 247_060 Anthropic will win over OpenAI via better/smarter AI regardless of installed base Dave Blundin | AI | 50% | ||
| 0.64 | github_release 2026-01-26 | 240_019 Post-transformer architecture will come out of left field within a year Dave Blundin | AI | 45% | ||
| 0.64 | github_release 2025-10-03 | 240_013 Sam Altman predicts another architecture breakthrough as big as transformers over LSTMs Sam Altman | AI | 41% | ||
| 0.64 | github_release 2022-06-28 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.64 | github_release 2026-05-06 | 239_003 We are currently in AI hard takeoff Elon Musk | AI | 47% | ||
| 0.64 | github_release 2026-01-18 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.64 | github_release 2025-08-12 | 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% | ||
| 0.64 | github_release 2024-10-30 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.64 | github_release 2026-01-27 | 234_017 OpenAI codex lead predicts current coding agents will seem primitive in 10 weeks OpenAI Codex Lead | AI | 41% | ||
| 0.64 | github_release 2026-01-29 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.64 | github_release 2026-01-29 | 238_028 Anthropic plugins will enable market-by-market disruption (could short stocks and announce plugins) Emad Mostaque | Markets/Stocks | 31% | ||
| 0.64 | github_release 2023-04-05 | AI_025 Most current generative AI wrappers are transient — they will fade into the background as infrastructure layers, analogous to Radio Shack fading in the Windows/PC era; winners will be infrastructure and verticalized depth plays, not thin API-wrapper apps. Mark Cuban | AI | 60% | ||
| 0.64 | github_release 2026-04-28 | 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% | ||
| 0.64 | github_release 2026-04-23 | 248_038 We will see humanoid robot threats alongside the current Sam Altman backlash. Salim Ismail | Robotics | 34% | ||
| 0.64 | github_release 2026-01-08 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.64 | github_release 2026-03-02 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.64 | github_release 2022-10-28 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.64 | github_release 2022-06-28 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.64 | github_release 2021-06-30 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.64 | github_release 2025-08-12 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.64 | github_release 2024-03-01 | INF_001 Reaching AGI by 2027 will require deployment of hundreds of millions of AI GPUs — forcing total mobilization of US industrial capacity for semiconductor fab and data-center shell construction. Leopold Aschenbrenner | AI | 48% | ||
| 0.64 | github_release 2018-08-31 | CYB_009 Hardware-software alignment will force widespread foundational-codebase rewrites — exemplified by Midjourney's strategic migration from Google TPU architecture to native GPU framework, enabling hyper-fast personalization, HD generation, and massive par... David Holz | AI | 77% | ||
| 0.64 | github_release 2024-03-15 | 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% | ||
| 0.64 | github_release 2023-10-25 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.64 | github_release 2022-04-22 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.64 | github_release 2026-02-24 | 234_017 OpenAI codex lead predicts current coding agents will seem primitive in 10 weeks OpenAI Codex Lead | AI | 41% | ||
| 0.64 | github_release 2026-02-10 | 241_037 Chinese AI strategy will stay open source / open weights Eric Schmidt | AI | 49% | ||
| 0.64 | github_release 2026-05-05 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.64 | github_release 2026-02-16 | 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% | ||
| 0.64 | github_release 2026-05-06 | 238_023 Neural nets will be 100x bigger at end of 2026 than at beginning (already in the bag) Dave Blundin | AI | 49% |