Novel / Unknown Approaches

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  "title": "Novel / Unknown Approaches",
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  "lastUpdated": "2026-03-13",
  "dateCreated": "2026-02-15",
  "llmSummary": "Analyzes probability (1-15%) of novel AI paradigms emerging before transformative AI, systematically reviewing historical prediction failures (expert AGI timelines shifted 43 years in 4 years, 13 years in one survey cycle) and comparing alternative approaches like neuro-symbolic (8-15% probability), SSMs (5-12%), and NAS (15-30%). Concludes current paradigm faces quantified limits (data exhaustion ~2028, compute costs approaching economic constraints) but near-term timelines favor incumbent approaches.",
  "description": "Analysis of potential AI paradigm shifts drawing on historical precedent. Expert forecasts have shortened AGI timelines from 50 years to 5 years in just four years (Metaculus 2020-2024), with median expert estimates dropping from 2060 to 2047 between 2022-2023 surveys alone. Probability of novel paradigm dominance estimated at 1-15% depending on timeline assumptions.",
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    {
      "text": "80,000 Hours' analysis of expert forecasts",
      "url": "https://80000hours.org/2025/03/when-do-experts-expect-agi-to-arrive/",
      "resourceId": "f2394e3212f072f5",
      "resourceTitle": "80,000 Hours AGI Timelines Review"
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    {
      "text": "AI Impacts 2023 survey",
      "url": "https://ourworldindata.org/ai-timelines",
      "resourceId": "d23472ea324bb482",
      "resourceTitle": "Our World in Data: AI Timelines"
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    {
      "text": "NAS tools",
      "url": "https://link.springer.com/article/10.1007/s10462-024-11058-w",
      "resourceId": "e7b7fb411e65d3d1",
      "resourceTitle": "Systematic review on neural architecture search"
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    {
      "text": "Training compute grew 5x/year",
      "url": "https://epoch.ai/blog/can-ai-scaling-continue-through-2030",
      "resourceId": "9587b65b1192289d",
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      "text": "AGI by 2047",
      "url": "https://ourworldindata.org/ai-timelines",
      "resourceId": "d23472ea324bb482",
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    {
      "text": "Metaculus AGI median",
      "url": "https://80000hours.org/2025/03/when-do-experts-expect-agi-to-arrive/",
      "resourceId": "f2394e3212f072f5",
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      "text": "AI Impacts survey",
      "url": "https://ourworldindata.org/ai-timelines",
      "resourceId": "d23472ea324bb482",
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    {
      "text": "5x/year compute growth",
      "url": "https://epoch.ai/blog/can-ai-scaling-continue-through-2030",
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      "text": "NASNet, EfficientNet",
      "url": "https://link.springer.com/article/10.1007/s10462-024-11058-w",
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      "text": "AutoML/NAS advancing",
      "url": "https://academic.oup.com/nsr/article/11/8/nwae282/7740455",
      "resourceId": "d1a3f270ea185ba1",
      "resourceTitle": "Advances in neural architecture search"
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      "text": "Google quantum supremacy",
      "url": "https://blog.google/technology/ai/2025-research-breakthroughs/",
      "resourceId": "4f0d130db1361363",
      "resourceTitle": "Google's 2025 Research Breakthroughs"
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    {
      "text": "NAS matches human designs",
      "url": "https://www.automl.org/nas-overview/",
      "resourceId": "d01d8824d9b6171b",
      "resourceTitle": "NAS Overview"
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    {
      "text": "Epoch AI's scaling analysis",
      "url": "https://epoch.ai/blog/can-ai-scaling-continue-through-2030",
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      "text": "32% yearly growth",
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      "text": "NAS/AutoML progress",
      "url": "https://link.springer.com/article/10.1007/s10462-024-11058-w",
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      "text": "Metaculus",
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      "text": "5x/year growth continuing",
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      "text": "NAS producing competitive models",
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      "text": "median Metaculus estimate",
      "url": "https://80000hours.org/2025/03/when-do-experts-expect-agi-to-arrive/",
      "resourceId": "f2394e3212f072f5",
      "resourceTitle": "80,000 Hours AGI Timelines Review"
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      "text": "NAS producing competitive models",
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      "text": "Epoch: 2e29 FLOP feasible by 2030",
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      "text": "Epoch AI: Can AI Scaling Continue?",
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      "text": "Our World in Data: AI Timelines",
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      "text": "Neural Architecture Search Advances (NSR)",
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      "text": "Google 2025 Research Breakthroughs",
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