True AGI requires genuine scientific-discovery capabilities (AlphaFold-class breakthroughs) — brute-force LLM scaling alone is insufficient.

True AGI requires genuine scientific-discovery capabilities (AlphaFold-class breakthroughs) — brute-force LLM scaling alone is insufficient. | AI-authored Nobel-caliber scientific results

Key catalyst: AI-authored Nobel-caliber scientific results

Watch events: AlphaProof/AlphaEvolve-class papers; novel scientific discoveries credited to AI systems; Millennium Prize / Nobel-level AI results.

DeepMind AlphaEvolve (2025) demonstrates exactly this paradigm — model-search loop for algorithm discovery. Weakly aligned with pure scaling critique.

{
  "nia": false,
  "mode": "THESIS",
  "role": "Cited-CEO",
  "context": "Hassabis's core methodological critique: scaling != discovery. AGI needs search, novel hypothesis generation, and verification loops.",
  "to_year": 2035,
  "conv_cues": "requires; definitional critique",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "this decade",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2027-09-26",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2029-06-21",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2031-03-16",
      "observed_date": null
    },
    {
      "kind": "scenario_signal",
      "label": "Scenario fires: AGI slow: Schmidt/Hassabis 5-10 year path",
      "status": "pending",
      "weight": 0.5,
      "ordinal": -1,
      "source_id": "S_AGI_SLOW_2031",
      "expected_date": "2031-11-30",
      "observed_date": null
    },
    {
      "kind": "event",
      "label": "True AGI requires genuine scientific-discovery capabilities (AlphaFold-class breakthroughs) — brute-force LLM scaling alone is insufficient.",
      "status": "pending",
      "weight": 1,
      "ordinal": 0,
      "source_id": "CMQ_010",
      "expected_date": "2032-12-09",
      "observed_date": null
    }
  ],
  "repeat_eps": 1,
  "affiliation": "Google DeepMind",
  "attribution": "FIRST_PERSON",
  "granularity": "RELATIVE_DURATION",
  "source_refs": "2",
  "target_date": "2030-06-15T00:00:00",
  "display_date": "2032-12-09",
  "episode_date": "2026-04-21T00:00:00",
  "key_catalyst": "AI-authored Nobel-caliber scientific results",
  "parse_method": "Report midpoint",
  "domain_bucket": "AI",
  "episode_title": "The Global Architecture of Machine Intelligence: Exhaustive Synthesis of AI Compute, Memory & Quantum Predictions (2023-2026)",
  "flag_repeated": false,
  "in_5yr_window": true,
  "source_report": "AI_Chip__Compute__Memory__Quantum_Predictions.md (2026-04-21)",
  "appears_in_eps": "CMQ-RPT",
  "futurist_phase": "Phase 2 (2027-2028)",
  "is_macro_claim": false,
  "total_mentions": 1,
  "priority_weight": 5,
  "report_evidence": "Frames AGI as a scientific-discovery threshold vs a benchmark threshold — the most intellectually serious AGI definition.",
  "active_end_month": "2035-12",
  "recent_statement": "Hassabis 2026 reaffirms AGI-as-discovery framing; DeepMind research direction consistent (AlphaEvolve, AlphaProof, FunSearch).",
  "watch_events_raw": "AlphaProof/AlphaEvolve-class papers; novel scientific discoveries credited to AI systems; Millennium Prize / Nobel-level AI results.",
  "months_from_today": 50,
  "probability_layer": "Medium",
  "active_start_month": "2026-01",
  "december_dispersal": {
    "reason": "december_dispersal: domain=AI → 11/2035",
    "new_date": "2035-11-30",
    "old_date": "2035-12-31",
    "applied_at": "2026-04-30T16:28:34.304992+00:00"
  },
  "flag_nia_bracketed": false,
  "track_record_grade": "A",
  "track_record_notes": "Hassabis's 2016 AlphaGo and 2020 protein-folding calls both validated. Definitional predictions are harder to score but directionally important.",
  "contradicting_notes": "OpenAI o-series reasoning models and Anthropic extended thinking show scaling + test-time compute already generates novel discovery; Hassabis may be under-crediting LLM-based search.",
  "flag_near_term_2027": false,
  "flag_high_conviction": true,
  "milestones_phase2_at": "2026-05-01T21:26:03.387296+00:00",
  "milestones_d