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| Sim | Doc | Source | Pred | Domain | Prior | |
|---|---|---|---|---|---|---|
| 0.60 | github_release 2020-03-05 | 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 2026-05-11 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.60 | github_release 2025-10-24 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.60 | github_release 2025-09-23 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.60 | github_release 2025-09-18 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.60 | github_release 2025-09-18 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.60 | github_release 2018-03-01 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.60 | github_release 2021-01-05 | S_HUMANOID_ENTERPRISE_2028 Humanoid R2: 100K+ enterprise by Nov 2028 | humanoid_deployment | 50% | ||
| 0.60 | github_release 2026-06-18 | 230_040 AI capability/accuracy will improve recursively; output-checking issues will be eliminated quickly. Peter Diamandis | AI | 27% | ||
| 0.60 | github_release 2026-06-23 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.60 | github_release 2021-12-13 | 242_034 AI could compress S&P 500 equity valuations 2-7x free cash flow (down from 22x) Chamath Palihapitiya | Markets/Stocks | 38% | ||
| 0.59 | github_release 2026-03-27 | 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% | ||
| 0.59 | github_release 2024-07-23 | 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% | ||
| 0.59 | github_release 2025-10-01 | 237_019 Code generation models are pushing development in the direction of TypeScript instead of Rust for memory safety. Alex Wissner-Gross | AI | 35% | ||
| 0.59 | github_release 2021-12-15 | 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% | ||
| 0.59 | github_release 2025-12-22 | 235_005 AI capability will grow 100x this year in raw parameter count as lower bound. Dave Blundin | AI | 49% | ||
| 0.59 | github_release 2024-10-30 | 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% | ||
| 0.59 | github_release 2020-05-28 | 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% | ||
| 0.59 | github_release 2019-04-05 | AI_017 NVIDIA will make Agentic AI the primary demand vector via two specialized products: the 'NemoClaw' developer toolkit for building/orchestrating autonomous agents, and the 'Vera CPU rack' hardware platform explicitly designed to host, deploy, and execut... Jensen Huang | Semis | 75% | ||
| 0.59 | github_release 2019-04-05 | 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% | ||
| 0.59 | github_release 2019-05-30 | 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% | ||
| 0.59 | github_release 2018-03-01 | 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% | ||
| 0.59 | github_release 2026-01-20 | 241_037 Chinese AI strategy will stay open source / open weights Eric Schmidt | AI | 49% | ||
| 0.59 | github_release 2023-01-19 | TK04 Macro Recession 2026-27 (Structural Deleveraging) | — | 25% | ||
| 0.59 | github_release 2025-02-10 | 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% | ||
| 0.59 | github_release 2023-12-06 | 230_040 AI capability/accuracy will improve recursively; output-checking issues will be eliminated quickly. Peter Diamandis | AI | 27% | ||
| 0.59 | github_release 2026-01-07 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.59 | github_release 2023-02-10 | 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% | ||
| 0.59 | github_release 2023-06-16 | 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 | 52% | ||
| 0.59 | github_release 2026-05-15 | 234_017 OpenAI codex lead predicts current coding agents will seem primitive in 10 weeks OpenAI Codex Lead | AI | 33% | ||
| 0.59 | github_release 2021-06-10 | 242_051 Dyson swarm compute infrastructure will be realized in a few years Alex Wissner-Gross | Space | 24% | ||
| 0.59 | github_release 2020-09-23 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.59 | github_release 2026-05-30 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.59 | github_release 2020-05-06 | 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% | ||
| 0.59 | github_release 2021-07-30 | S_ROBOTAXI_MASS_2030 Robotaxi >10% urban miles by Nov 2030 | robotaxi_deployment | 30% | ||
| 0.59 | github_release 2020-07-08 | 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% | ||
| 0.59 | github_release 2023-12-15 | 238_005 By September 2026 there will be 1000+ ultra-high-inspirational-quality videos of the future generated nearly free Alex Wissner-Gross | AI | 39% | ||
| 0.59 | github_release 2019-07-04 | 237_009 ChatGPT will release a model specifically for OpenClaw within the next 6 months. Alex Finn | AI | 31% | ||
| 0.59 | github_release 2026-02-17 | 241_013 Agents from incompatible vendors combined will produce unpredictable effects Eric Schmidt | AI | 45% | ||
| 0.59 | github_release 2026-02-17 | 242_048 FDA will move to zero clinical trial model given enough Bayesian/computational evidence Alex Wissner-Gross | Biotech/Longevity | 31% | ||
| 0.59 | github_release 2026-02-17 | TK11 Autonomous Regulatory Block (Level 4 Halt) | — | 10% | ||
| 0.59 | github_release 2025-11-14 | COD_BIO_001 FDA finalizes or materially advances AI-for-drug-submission guidance by end 2026 Codex Research Pack | Biotech/Longevity | 47% | ||
| 0.59 | github_release 2025-10-23 | COD_BIO_001 FDA finalizes or materially advances AI-for-drug-submission guidance by end 2026 Codex Research Pack | Biotech/Longevity | 47% | ||
| 0.59 | github_release 2025-09-17 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.59 | github_release 2021-01-05 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.59 | github_release 2019-06-20 | 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% | ||
| 0.59 | github_release 2021-08-05 | 248_032 First-generation neural uploads will be destructive; 2nd-4th generation will be non-destructive. Alex Wissner-Gross | Biotech/Longevity | 42% | ||
| 0.59 | github_release 2026-06-18 | CMQ_047 Autonomous code agents and AutoResearch systems will close the loop on complex scientific experimentation without human-in-the-loop. Andrej Karpathy | AI | 51% | ||
| 0.59 | github_release 2025-10-10 | FUT_024 XPT 2022 tournament assigned mere 2.3% probability to AI achieving gold-medal performance in International Mathematical Olympiad by 2025 — actual achievement empirically reached forcing systemic re-evaluation within forecasting community. Historical tr... Superforecaster Community | AI | 100% | ||
| 0.59 | github_release 2025-03-24 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.59 | github_release 2020-03-09 | 248_032 First-generation neural uploads will be destructive; 2nd-4th generation will be non-destructive. Alex Wissner-Gross | Biotech/Longevity | 42% | ||
| 0.59 | github_release 2021-11-05 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.59 | github_release 2025-09-12 | 229_039 Figure will integrate additional sensors (infrared, ultraviolet, etc.) into future humanoids. Brett Adcock | Robotics | 28% | ||
| 0.59 | github_release 2023-08-31 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.59 | github_release 2024-03-27 | 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% | ||
| 0.59 | github_release 2024-02-22 | 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% | ||
| 0.59 | github_release 2022-08-05 | 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% | ||
| 0.59 | github_release 2025-12-22 | SEM_021 Largest AI models will see a 100x leap in size by 2026, driven largely by Chinese research efforts using quantization breakthroughs. Dave Blundin | AI/China | 45% | ||
| 0.59 | github_release 2026-04-17 | SEM_021 Largest AI models will see a 100x leap in size by 2026, driven largely by Chinese research efforts using quantization breakthroughs. Dave Blundin | AI/China | 45% | ||
| 0.59 | github_release 2024-10-30 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.59 | github_release 2025-01-31 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.59 | github_release 2026-04-06 | AUT_002 Models excelling at highly structured mathematical benchmarks exhibit a 'unified capability substrate' enabling dominance in seemingly unrelated fields (coding, logical reasoning, scientific discovery) — the 'mathematical skeleton' of the technological... Alex Wissner-Gross | AI | 59% | ||
| 0.59 | github_release 2026-03-17 | 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% | ||
| 0.59 | github_release 2025-12-14 | 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% | ||
| 0.59 | github_release 2023-04-10 | 229_028 Figure will NOT license out its neural net or hardware IP to third-party form-factor builders. Brett Adcock | Robotics | 69% | ||
| 0.59 | github_release 2023-01-19 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.59 | github_release 2023-12-15 | SEM_022 FP4 / ternary-weight architectures decouple AI capability from raw transistor density — embargoed nations maintain competitive development. Dave Blundin | AI/Architecture | 65% | ||
| 0.59 | github_release 2026-05-11 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.59 | github_release 2026-03-23 | 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 | 52% | ||
| 0.59 | github_release 2025-02-28 | INF_026 'Software 3.0' LLM infrastructure will operate like public utilities — requiring massive upfront capex (training compute, specialized hardware), specialized networking protocols for synchrony across hundreds of thousands of GPUs, and flawless uninterru... Andrej Karpathy | AI | 64% | ||
| 0.59 | github_release 2025-05-09 | 248_050 Opus 4.7 removes manual dials; prompts become the new hyperparameters. Alex Wissner-Gross | AI | 45% | ||
| 0.59 | github_release 2024-03-21 | 232_011 Jury is still out on whether speech will be the modality of the future for high-bandwidth operation. Alex Wissner-Gross | AI | 38% | ||
| 0.59 | github_release 2024-02-16 | 232_014 Recursive self-improvement is already here, not 12 months away. Alex Wissner-Gross | AI | 70% | ||
| 0.59 | github_release 2020-06-29 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.59 | github_release 2024-03-15 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.59 | github_release 2023-03-31 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.59 | github_release 2023-03-31 | S_HUMANOID_CONSUMER_2030 Humanoid R3: 1M+ consumer by Nov 2030 | humanoid_deployment | 20% | ||
| 0.59 | github_release 2023-12-15 | 238_022 From here forward, training data will be synthetic (pre-training era of human internet data is over) Alex Wissner-Gross | AI | 39% | ||
| 0.59 | github_release 2019-07-04 | 235_005 AI capability will grow 100x this year in raw parameter count as lower bound. Dave Blundin | AI | 49% | ||
| 0.59 | github_release 2025-10-23 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.59 | github_release 2019-08-14 | 234_048 Next major revolutions in foundation models will come from small language models Alex Wissner-Gross | AI | 41% | ||
| 0.59 | github_release 2026-06-15 | 235_037 Auto-regressive transformers and diffusion models will consolidate into one unified architecture. Alex Wissner-Gross | AI | 35% | ||
| 0.59 | github_release 2025-10-10 | S_HUMANOID_ENTERPRISE_2028 Humanoid R2: 100K+ enterprise by Nov 2028 | humanoid_deployment | 50% | ||
| 0.59 | github_release 2025-03-24 | 238_009 Recursive self-improvement is already happening now (no longer three years out) Alex Wissner-Gross | AI | 78% | ||
| 0.59 | github_release 2023-07-20 | 247_057 Parameter scaling race is over; frontier labs plateauing at 10T parameters Alex Wissner-Gross | AI | 28% | ||
| 0.59 | github_release 2023-06-15 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.59 | github_release 2026-04-15 | 235_008 Anthropic/OpenAI will be forced to release first-party OpenClaw competitor in next couple months. Alex Wissner-Gross | AI | 42% | ||
| 0.59 | github_release 2023-01-12 | SEM_021 Largest AI models will see a 100x leap in size by 2026, driven largely by Chinese research efforts using quantization breakthroughs. Dave Blundin | AI/China | 45% | ||
| 0.59 | github_release 2026-04-23 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.59 | github_release 2026-03-27 | 240_013 Sam Altman predicts another architecture breakthrough as big as transformers over LSTMs Sam Altman | AI | 41% | ||
| 0.59 | github_release 2024-03-27 | 240_020 New architecture won't map to current NVIDIA architecture; will create next Anthropic/OpenAI Dave Blundin | AI | 46% | ||
| 0.59 | github_release 2023-07-29 | 241_031 Scientists don't agree yet on approach for recursive self-improvement Eric Schmidt | AI | 48% | ||
| 0.59 | github_release 2026-03-06 | 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% | ||
| 0.59 | github_release 2025-04-25 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.59 | github_release 2025-02-10 | CMQ_026 NVIDIA silicon roadmap: Blackwell (2025) → Vera Rubin (2026) → Vera Rubin Ultra (2027) → Feynman (2028) — annual architectural cadence. Jensen Huang | Semis | 83% | ||
| 0.59 | github_release 2023-12-15 | COD_TECH_001 A16/N2-class TSMC process availability materially supports 2027 AI accelerator ramps Codex Research Pack | Semis | 50% | ||
| 0.59 | github_release 2025-10-15 | 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% | ||
| 0.59 | github_release 2026-04-21 | CMQ_010 True AGI requires genuine scientific-discovery capabilities (AlphaFold-class breakthroughs) — brute-force LLM scaling alone is insufficient. Demis Hassabis | AI | 49% | ||
| 0.59 | github_release 2021-05-13 | 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% | ||
| 0.59 | github_release 2026-06-04 | 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% |