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| Sim | Doc | Source | Pred | Domain | Prior | |
|---|---|---|---|---|---|---|
| 0.62 | github_release 2025-12-22 | 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% | ||
| 0.62 | github_release 2024-03-01 | 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% | ||
| 0.62 | github_release 2018-08-31 | 238_025 AI computer-use benchmarks (OSWorld, Tbench) have broken through human level Emad Mostaque | AI | 45% | ||
| 0.62 | github_release 2026-05-07 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.62 | github_release 2026-02-20 | 237_018 We are seeing a Cambrian explosion of OpenClaw variants (PicoClaw, IronClaw, NanoClaw, Nanobot, etc.) with many more to come. Alex Wissner-Gross | AI | 40% | ||
| 0.62 | github_release 2025-08-13 | 238_038 Compute will remain scarce until Dyson swarm is built; scarce AI agent attention will be monetized Alex Wissner-Gross | AI | 35% | ||
| 0.62 | github_release 2024-12-31 | 241_049 Underage kids / AI vulnerability problem must be solved - line we can't cross Eric Schmidt | AI | 51% | ||
| 0.62 | github_release 2025-05-09 | AUT_021 Defining software movement of 2026: startups building autonomous platforms specifically designed to clean/structure/continuously validate multimodal data — unstructured corporate sludge (PDFs, logs, videos, emails) causes autonomous agentic workflows t... Marc Andreessen | AI | 57% | ||
| 0.62 | github_release 2023-12-19 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.62 | github_release 2026-05-13 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.62 | github_release 2026-05-14 | 240_016 Everyone is underestimating the next year of AI improvements (more than 2x gain) Dave Blundin | AI | 50% | ||
| 0.62 | github_release 2020-01-21 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.62 | github_release 2026-06-03 | 241_037 Chinese AI strategy will stay open source / open weights Eric Schmidt | AI | 49% | ||
| 0.62 | github_release 2020-02-07 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.62 | github_release 2026-02-24 | 232_012 US-China AI situation about to get more complicated regarding open source models and secrets. Ben Horowitz | Geopolitics | 44% | ||
| 0.62 | github_release 2026-02-09 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.62 | github_release 2022-09-21 | 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% | ||
| 0.62 | github_release 2022-01-28 | 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% | ||
| 0.62 | github_release 2021-11-02 | 229_042 Figure believes there will be a single omni-model fusing language, vision, action, memory — not multiple specialized neural nets per task. Brett Adcock | AI | 40% | ||
| 0.62 | github_release 2026-04-28 | INF_072 There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. Demis Hassabis | AI | 40% | ||
| 0.62 | github_release 2025-09-04 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.62 | github_release 2026-02-09 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.62 | github_release 2025-03-12 | 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% | ||
| 0.62 | github_release 2023-07-05 | 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% | ||
| 0.62 | github_release 2025-01-29 | 248_010 AI capabilities will advance 100x in 2026 (by summer, potentially more). Dave Blundin | AI | 31% | ||
| 0.62 | github_release 2019-08-15 | AI_006 True autonomous agents are 'not anywhere close' — AGI and reliable long-horizon agents will require a full decade (2034 or beyond) to develop the holistic contextual reasoning and robust world models needed for unconstrained physical and digital enviro... Andrej Karpathy | AI | 38% | ||
| 0.62 | github_release 2025-12-19 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.62 | github_release 2024-10-04 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.62 | github_release 2018-08-31 | SEM_012 Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering. Jensen Huang | AI/Manufacturing | 75% | ||
| 0.62 | github_release 2018-08-31 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.62 | github_release 2023-05-22 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.62 | github_release 2025-06-25 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.62 | github_release 2023-12-06 | 248_023 Ternary (sub-bit) parameter precision will be optimal for AI models. Dave Blundin | AI | 50% | ||
| 0.62 | github_release 2026-05-20 | 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% | ||
| 0.62 | github_release 2026-06-01 | 230_046 OpenAI's Noam Brown has only ~3 months of future model access internally — dramatic capability gap with public. Dave Blundin | AI | 43% | ||
| 0.62 | github_release 2026-06-01 | 247_011 OpenAI user count will soon reach 1 billion Alex Wissner-Gross | AI | 41% | ||
| 0.62 | github_release 2021-11-02 | 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% | ||
| 0.62 | github_release 2026-03-05 | 234_021 OpenAI will launch consumer AI devices in 2027 Peter Diamandis | AI | 50% | ||
| 0.62 | github_release 2026-02-10 | 239_003 We are currently in AI hard takeoff Elon Musk | AI | 47% | ||
| 0.62 | github_release 2026-02-09 | 241_037 Chinese AI strategy will stay open source / open weights Eric Schmidt | AI | 49% | ||
| 0.62 | github_release 2025-12-11 | 247_011 OpenAI user count will soon reach 1 billion Alex Wissner-Gross | AI | 41% | ||
| 0.62 | github_release 2025-11-04 | 241_037 Chinese AI strategy will stay open source / open weights Eric Schmidt | AI | 49% | ||
| 0.62 | github_release 2022-09-21 | 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% | ||
| 0.62 | github_release 2021-11-02 | INF_072 There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. Demis Hassabis | AI | 40% | ||
| 0.62 | github_release 2026-04-13 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.62 | github_release 2026-01-26 | 229_002 Figure will scale out robots in industrial/commercial workforce in 2026 via its signed customers. Brett Adcock | Robotics | 56% | ||
| 0.62 | github_release 2026-01-26 | INF_072 There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. Demis Hassabis | AI | 40% | ||
| 0.62 | github_release 2026-01-13 | 229_001 Figure will put robots on its own manufacturing lines (BotQ) this year to build robots. Brett Adcock | Robotics | 62% | ||
| 0.62 | github_release 2025-09-04 | 229_039 Figure will integrate additional sensors (infrared, ultraviolet, etc.) into future humanoids. Brett Adcock | Robotics | 28% | ||
| 0.62 | github_release 2026-03-02 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.62 | github_release 2023-11-14 | 248_048 AI models will move to a post-binary (sub-one-bit) numerical precision paradigm. Alex Wissner-Gross | AI | 34% | ||
| 0.62 | 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% | ||
| 0.62 | github_release 2023-11-15 | 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% | ||
| 0.62 | github_release 2023-10-04 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.62 | github_release 2023-10-04 | SEM_012 Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering. Jensen Huang | AI/Manufacturing | 75% | ||
| 0.62 | github_release 2026-05-06 | 230_046 OpenAI's Noam Brown has only ~3 months of future model access internally — dramatic capability gap with public. Dave Blundin | AI | 43% | ||
| 0.62 | github_release 2026-05-05 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.62 | github_release 2019-05-30 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.62 | github_release 2023-01-31 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.62 | github_release 2023-01-31 | TK04 Macro Recession 2026-27 (Structural Deleveraging) | — | 25% | ||
| 0.62 | github_release 2025-05-12 | INF_035 Advanced U.S. manufacturing capacity for 3D-printed liquid-cooling plates will scale rapidly — Fabric8Labs secured $50M (NEA + Intel Capital) specifically to address the AI-DC thermal bottleneck with electrochemically-deposited intricate cold-plate geo... Fabric8Labs (NEA / Intel Capital funded) | Semis | 65% | ||
| 0.62 | github_release 2025-03-20 | 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% | ||
| 0.62 | github_release 2021-01-07 | 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% | ||
| 0.62 | github_release 2021-06-30 | S_HUMANOID_ENTERPRISE_2028 Humanoid R2: 100K+ enterprise by Nov 2028 | humanoid_deployment | 50% | ||
| 0.62 | github_release 2020-09-18 | 242_051 Dyson swarm compute infrastructure will be realized in a few years Alex Wissner-Gross | Space | 37% | ||
| 0.62 | github_release 2020-05-28 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.62 | github_release 2020-08-04 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.62 | github_release 2020-05-17 | 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% | ||
| 0.61 | github_release 2026-04-15 | 234_017 OpenAI codex lead predicts current coding agents will seem primitive in 10 weeks OpenAI Codex Lead | AI | 41% | ||
| 0.61 | github_release 2026-02-23 | 247_011 OpenAI user count will soon reach 1 billion Alex Wissner-Gross | AI | 41% | ||
| 0.61 | github_release 2026-02-05 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.61 | github_release 2025-12-15 | 247_011 OpenAI user count will soon reach 1 billion Alex Wissner-Gross | AI | 41% | ||
| 0.61 | github_release 2025-11-13 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.61 | github_release 2025-11-10 | 232_012 US-China AI situation about to get more complicated regarding open source models and secrets. Ben Horowitz | Geopolitics | 44% | ||
| 0.61 | github_release 2026-03-04 | 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% | ||
| 0.61 | github_release 2026-01-13 | 248_038 We will see humanoid robot threats alongside the current Sam Altman backlash. Salim Ismail | Robotics | 34% | ||
| 0.61 | github_release 2023-11-14 | 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% | ||
| 0.61 | github_release 2023-07-05 | 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% | ||
| 0.61 | github_release 2026-03-23 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.61 | github_release 2023-10-04 | 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% | ||
| 0.61 | github_release 2026-05-05 | 247_012 The bar for AI startups will rise to require being recursively self-improving Alex Wissner-Gross | AI | 32% | ||
| 0.61 | github_release 2019-08-15 | AUT_017 Defining 2023-2026 shift: maturation of 'Agentic AI' via heavy fine-tuning of pre-trained LLMs using advanced reinforcement learning techniques — single foundational models seamlessly handling diverse complex tasks (market analysis, software engineerin... Jimmy Ba | AI | 65% | ||
| 0.61 | github_release 2019-05-30 | 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% | ||
| 0.61 | github_release 2018-07-12 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.61 | github_release 2018-07-12 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.61 | github_release 2025-10-15 | 241_037 Chinese AI strategy will stay open source / open weights Eric Schmidt | AI | 49% | ||
| 0.61 | github_release 2023-01-31 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.61 | github_release 2025-11-12 | 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% | ||
| 0.61 | github_release 2026-05-11 | AUT_021 Defining software movement of 2026: startups building autonomous platforms specifically designed to clean/structure/continuously validate multimodal data — unstructured corporate sludge (PDFs, logs, videos, emails) causes autonomous agentic workflows t... Marc Andreessen | AI | 57% | ||
| 0.61 | github_release 2025-05-12 | CMQ_042 As AI evolves from Generative to Agentic, structural computing bottlenecks shift away from GPU and heavily toward CPU and system memory. Morgan Stanley | AI/Compute | 35% | ||
| 0.61 | github_release 2025-02-28 | 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% | ||
| 0.61 | github_release 2021-02-22 | 243_015 Software space for autonomous may consolidate to fewer than 10 providers Dara Khosrowshahi | Auto/Transport | 46% | ||
| 0.61 | github_release 2023-10-19 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.61 | github_release 2021-07-30 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.61 | github_release 2026-06-03 | 247_011 OpenAI user count will soon reach 1 billion Alex Wissner-Gross | AI | 41% | ||
| 0.61 | github_release 2021-03-13 | 237_018 We are seeing a Cambrian explosion of OpenClaw variants (PicoClaw, IronClaw, NanoClaw, Nanobot, etc.) with many more to come. Alex Wissner-Gross | AI | 40% | ||
| 0.61 | github_release 2020-05-17 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.61 | github_release 2025-12-11 | 239_004 xAI/Grok will catch up and exceed competitors on coding by mid-2026 Elon Musk | AI | 40% | ||
| 0.61 | github_release 2025-11-13 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.61 | github_release 2023-01-12 | 230_040 AI capability/accuracy will improve recursively; output-checking issues will be eliminated quickly. Peter Diamandis | AI | 50% | ||
| 0.61 | github_release 2022-08-25 | CMQ_010 True AGI requires genuine scientific-discovery capabilities (AlphaFold-class breakthroughs) — brute-force LLM scaling alone is insufficient. Demis Hassabis | AI | 49% | ||
| 0.61 | github_release 2022-06-13 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.61 | github_release 2022-01-28 | 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% | ||
| 0.61 | github_release 2021-09-30 | 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% | ||
| 0.61 | github_release 2026-03-27 | 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% | ||
| 0.61 | github_release 2026-03-02 | 248_023 Ternary (sub-bit) parameter precision will be optimal for AI models. Dave Blundin | AI | 50% | ||
| 0.61 | github_release 2026-02-09 | 248_023 Ternary (sub-bit) parameter precision will be optimal for AI models. Dave Blundin | AI | 50% | ||
| 0.61 | github_release 2022-03-10 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.61 | github_release 2023-05-22 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.61 | github_release 2025-08-13 | 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% | ||
| 0.61 | github_release 2024-10-22 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.61 | github_release 2024-09-13 | 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% | ||
| 0.61 | github_release 2024-09-13 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.61 | github_release 2026-01-07 | 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% | ||
| 0.61 | github_release 2025-05-28 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.61 | github_release 2020-09-18 | 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% | ||
| 0.61 | github_release 2026-02-23 | 232_012 US-China AI situation about to get more complicated regarding open source models and secrets. Ben Horowitz | Geopolitics | 44% | ||
| 0.61 | github_release 2026-02-14 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.61 | github_release 2026-02-14 | 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% | ||
| 0.61 | github_release 2025-11-04 | 238_025 AI computer-use benchmarks (OSWorld, Tbench) have broken through human level Emad Mostaque | AI | 45% | ||
| 0.61 | github_release 2026-04-13 | INF_072 There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. Demis Hassabis | AI | 40% | ||
| 0.61 | github_release 2026-04-09 | INF_072 There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. Demis Hassabis | AI | 40% | ||
| 0.61 | github_release 2026-01-13 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.61 | github_release 2025-11-24 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.61 | github_release 2025-09-04 | 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% | ||
| 0.61 | github_release 2025-09-04 | COD_BIO_005 Colossal adds at least one more de-extinction species to active embryo-transfer pipeline by end 2028 Codex Research Pack | Biotech/Longevity | 47% | ||
| 0.61 | github_release 2025-07-28 | TK01 AGI Capability Plateau (2026-27 Training Stall) | — | 15% | ||
| 0.61 | 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% | ||
| 0.61 | github_release 2026-05-05 | 239_003 We are currently in AI hard takeoff Elon Musk | AI | 47% | ||
| 0.61 | github_release 2026-03-06 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.61 | github_release 2025-12-03 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.61 | github_release 2025-01-31 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.61 | github_release 2018-08-31 | 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% | ||
| 0.61 | github_release 2026-05-07 | 241_011 By end of 2026, no one will write code manually - it'll be a quaint skill Peter Diamandis | Labor/Jobs | 55% | ||
| 0.61 | github_release 2026-04-26 | 230_045 GDP will be replaced by an 'Abundance Capability Index' measuring capacity to solve problems. Alex Wissner-Gross | Macro/Economy | 39% | ||
| 0.61 | github_release 2026-04-06 | 234_048 Next major revolutions in foundation models will come from small language models Alex Wissner-Gross | AI | 41% | ||
| 0.61 | github_release 2024-10-30 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.61 | github_release 2024-09-12 | 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% | ||
| 0.61 | github_release 2025-05-12 | 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% | ||
| 0.61 | github_release 2025-02-28 | 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% | ||
| 0.61 | github_release 2024-01-03 | 238_022 From here forward, training data will be synthetic (pre-training era of human internet data is over) Alex Wissner-Gross | AI | 39% | ||
| 0.61 | github_release 2026-06-01 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.61 | github_release 2020-09-18 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.61 | github_release 2021-03-13 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.61 | github_release 2026-05-04 | 230_046 OpenAI's Noam Brown has only ~3 months of future model access internally — dramatic capability gap with public. Dave Blundin | AI | 43% | ||
| 0.61 | github_release 2026-03-13 | 232_012 US-China AI situation about to get more complicated regarding open source models and secrets. Ben Horowitz | Geopolitics | 44% | ||
| 0.61 | github_release 2026-02-23 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.61 | github_release 2026-02-16 | INF_072 There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. Demis Hassabis | AI | 40% | ||
| 0.61 | github_release 2025-11-25 | 236_028 AI chatbot/AI romance trend growing unfortunately Andrew Yang | Consumer | 51% | ||
| 0.61 | github_release 2026-02-09 | 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% | ||
| 0.61 | github_release 2025-08-13 | TK01 AGI Capability Plateau (2026-27 Training Stall) | — | 15% | ||
| 0.61 | 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% | ||
| 0.61 | github_release 2024-03-15 | CYB_020 Starlink expansion — navigating regulatory regimes like India's IN-SPACe approvals — establishes a ubiquitous, high-bandwidth data canopy essential for routing planetary-scale AI agent communications without terrestrial fiber-optic latency. Gwynne Shotwell | Space | 65% | ||
| 0.61 | github_release 2026-02-09 | 242_048 FDA will move to zero clinical trial model given enough Bayesian/computational evidence Alex Wissner-Gross | Biotech/Longevity | 36% | ||
| 0.61 | github_release 2023-01-31 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 41% | ||
| 0.61 | github_release 2026-05-15 | 232_012 US-China AI situation about to get more complicated regarding open source models and secrets. Ben Horowitz | Geopolitics | 44% | ||
| 0.61 | github_release 2021-06-10 | CYB_014 The Exponential Organization (ExO) framework becomes mandatory corporate structure — ExOs leverage AI agents to scale operations non-linearly without corresponding headcount increases. High-friction services historically reserved for high-net-worth cli... Salim Ismail | Macro/Economy | 58% | ||
| 0.61 | github_release 2019-06-14 | CYB_003 Localized, ungoverned multi-agent networks will spontaneously generate their own social networks, governance manifestos, debated ethics, and closed-loop digital economies — exemplified by the Moltbook platform in early 2026 where 150,000+ autonomous AI... Alex Finn | AI | 55% | ||
| 0.61 | github_release 2026-02-09 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.61 | github_release 2025-12-19 | 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% | ||
| 0.61 | github_release 2022-09-21 | 235_005 AI capability will grow 100x this year in raw parameter count as lower bound. Dave Blundin | AI | 49% | ||
| 0.61 | github_release 2022-01-28 | 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% | ||
| 0.61 | github_release 2021-07-16 | 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% | ||
| 0.61 | github_release 2026-04-23 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.61 | github_release 2026-04-13 | 238_071 Future AI models may compress all human knowledge into megabytes via post-transformer breakthroughs Alex Wissner-Gross | AI | 35% | ||
| 0.61 | github_release 2026-04-09 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.61 | github_release 2026-04-09 | INF_072 There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. Demis Hassabis | AI | 40% | ||
| 0.61 | github_release 2026-01-13 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.61 | github_release 2025-09-12 | 238_040 Google may announce a locally hosted Gemma-type model at WWDC in June 2026 for Apple OS Alex Wissner-Gross | AI | 34% | ||
| 0.61 | github_release 2025-02-24 | 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% | ||
| 0.61 | github_release 2023-09-26 | 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% | ||
| 0.61 | github_release 2025-04-23 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.61 | github_release 2024-07-24 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.61 | github_release 2024-07-24 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.61 | github_release 2024-01-30 | 240_021 Post-transformer architecture will be even more specialized than GPUs Alex Wissner-Gross | AI | 35% | ||
| 0.61 | github_release 2023-03-15 | 240_013 Sam Altman predicts another architecture breakthrough as big as transformers over LSTMs Sam Altman | AI | 41% | ||
| 0.61 | github_release 2026-04-17 | CYB_003 Localized, ungoverned multi-agent networks will spontaneously generate their own social networks, governance manifestos, debated ethics, and closed-loop digital economies — exemplified by the Moltbook platform in early 2026 where 150,000+ autonomous AI... Alex Finn | AI | 55% | ||
| 0.61 | github_release 2026-02-09 | 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% | ||
| 0.61 | github_release 2025-01-06 | TK01 AGI Capability Plateau (2026-27 Training Stall) | — | 15% | ||
| 0.61 | github_release 2023-04-26 | 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% | ||
| 0.61 | github_release 2025-08-13 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.61 | github_release 2023-12-06 | 248_048 AI models will move to a post-binary (sub-one-bit) numerical precision paradigm. Alex Wissner-Gross | AI | 34% | ||
| 0.61 | github_release 2026-04-21 | IND_005 Convergence of computational biology + AI-driven data modeling + CRISPR gene editing enables bringing back extinct species — Form Bio platform (spun out 2022) enables successful resurrection of woolly mammoth and Tasmanian tiger within the decade (by ~... Ben Lamm | Biotech/Longevity | 33% | ||
| 0.61 | github_release 2026-05-20 | 240_013 Sam Altman predicts another architecture breakthrough as big as transformers over LSTMs Sam Altman | AI | 41% | ||
| 0.61 | github_release 2023-10-19 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.61 | github_release 2026-02-09 | 234_017 OpenAI codex lead predicts current coding agents will seem primitive in 10 weeks OpenAI Codex Lead | AI | 41% | ||
| 0.61 | github_release 2022-06-13 | 239_003 We are currently in AI hard takeoff Elon Musk | AI | 47% | ||
| 0.61 | github_release 2021-11-02 | 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% | ||
| 0.61 | github_release 2021-09-30 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% | ||
| 0.61 | github_release 2026-04-09 | 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% | ||
| 0.61 | github_release 2026-01-26 | 248_038 We will see humanoid robot threats alongside the current Sam Altman backlash. Salim Ismail | Robotics | 34% | ||
| 0.61 | github_release 2025-11-24 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.61 | github_release 2026-03-02 | 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% | ||
| 0.61 | github_release 2025-08-13 | CMQ_025 The entire global installed base of data centers must be ripped out and replaced — legacy DCs unfit for AI factory workloads. Jensen Huang | AI/Compute | 49% | ||
| 0.61 | github_release 2023-11-03 | 248_048 AI models will move to a post-binary (sub-one-bit) numerical precision paradigm. Alex Wissner-Gross | AI | 34% | ||
| 0.61 | github_release 2023-10-25 | 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% | ||
| 0.61 | github_release 2023-07-05 | 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% | ||
| 0.61 | github_release 2023-07-05 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.61 | github_release 2023-03-15 | 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% | ||
| 0.61 | github_release 2022-03-10 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 87% |