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230_008predictionAIAI-timing

AI will bulk-solve math, physical sciences, engineering, medicine, and material sciences.

Predictor: Alex Wissner-Gross · ep#230 "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230" · source

Prior probability
50.0%
Current probability
39.7%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2028-06-01 – 2028-06-30
Edges in / out
8 / 5
Tickers exposed
33

Prediction text

AI will bulk-solve math, physical sciences, engineering, medicine, and material sciences. | I've been predicting on the public record for many many episodes now that we're nearing a time, in fact, we'll talk about it later in this episode, when AI is positioned to bulk solve math, the physical sciences, engineering, medicine, material sciences. These will all get bulk solved.

Verbatim quote

From episode "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230"
I've been predicting on the public record for many many episodes now that we're nearing a time, in fact, we'll talk about it later in this episode, when AI is positioned to bulk solve math, the physical sciences, engineering, medicine, material sciences. These will all get bulk solved.

Predictor: Alex Wissner-Gross

κ + Brier as of 2026-05-22
κ (discount)
0.844
Brier
0.0341
excellent
Hits / Misses
6 / 1
of 11 resolved
Hit rate
54.5%
Calibration plot (stated vs observed)

Evidence about this node from Alex Wissner-Gross is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

3 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-04-302026-05-02
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 39.7%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 6 fired ✓ · 1 overdue ⏱ · 4 pending
  1. 2026-02-01hitOpen-source AI literature-review tool surpasses major LLMs on citation accuracy
    How: Nature documents AI tool exceeding major LLMs at scientific literature review with human-level citation accuracy
    Source: Nature: Open-source AI tool beats giant LLMs in literature reviewsconf 85%
  2. 2026-03-01overdueAI compresses drug-discovery timelines from years to weeks (validated pipeline)
    How: Published case study or industry confirmation of AI compressing lead-to-candidate timeline by >=10x in named therapeutic program
    Source: Medium / industry analysis: How AI is Transforming Drug Discovery in 2026conf 60%
  3. 2026-06-01 → 2027-12-31pendingAutonomous AI agent contributes co-author / primary credit on Nature/Science paper
    How: AI agent listed as substantive contributor (co-author or methodological primary) in Nature/Science/Cell/PNAS publication for novel scientific result
    Source: Nature/Science journal listingsconf 55%
  4. 2026-09-01 → 2028-06-30pendingAI solves new mathematical conjecture or proves significant open problem
    How: AI system credited (e.g., AlphaProof-class) with novel proof of significant open conjecture, validated by Fields-medalist-level review
    Source: Annals of Mathematics; arXiv math reviewconf 45%
  5. 2026-09-01 → 2028-06-30pendingAI discovers new material with experimentally verified order-of-magnitude property improvement
    How: AI-designed material (battery, superconductor, catalyst) experimentally verified to deliver >=10x improvement on key figure of merit vs prior state-of-art
    Source: Nature Materials; ACS journalsconf 45%
  6. 2027-06-01 → 2028-12-31pendingAI-driven AGI/AI labs report multiple sciences 'bulk-solved' simultaneously
    How: >=3 distinct scientific domains report concurrent AI-driven step-change discoveries (math, physics, materials, biology) within rolling 12-month window
    Source: Royal Society / NAS reports; AI-lab annual papersconf 30%
    Notes: Direct test of 'bulk solve' simultaneity claim.

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 40%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
metadata_milestone_miss_sweep2026-05-02T22:07:21Z39.7%-5.0pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.397 blend=0.397 LLR=-0.205 κ=0.84 no_blend
Raw metadata
{
  "trf": 1,
  "kappa": 0.8438,
  "base_rate": null,
  "predictor": "Alex Wissner-Gross",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": -0.21232187956239004,
  "bayes_factor": "1.2:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.4471180434475905,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.50628,
      "label": "AI compresses drug-discovery timelines from years to weeks (validated pipeline)",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.6,
      "source_url": "https://medium.com/@unicodeveloper/how-ai-is-transforming-drug-discovery-in-2026-0d8c7c600428",
      "adjusted_llr": -0.20527887493300145,
      "expected_date": "2026-03-01",
      "measurement_criterion": "Published case study or industry confirmation of AI compressing lead-to-candidate timeline by >=10x in named therapeutic program"
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.3,
  "outside_weight": 0.7,
  "posterior_prob": 0.3970910108149057,
  "posterior_logit": -0.41760075449539147,
  "predictor_brier": 0.03413,
  "inside_posterior": 0.3970910108149057,
  "blended_posterior": 0.3970910108149057,
  "reference_class_id": null,
  "total_adjusted_llr": -0.20527887493300145,
  "predictor_n_resolved": 11
}
LBP2026-04-30T16:39:51Z44.7%-2.2pp
Network propagation: 46.9% → 44.7%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z46.9%-3.1pp
Network propagation: 50.0% → 46.9%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.500+0.058
prereq234_012
Anthropic revenue will cross OpenAI revenue in middle of 202Peter Diamandis
67.1%0.5000.050-0.048
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.500+0.035
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.5000.050-0.019
prereq235_002
Anthropic will exceed OpenAI in revenue this year (2026).Dave Blundin
74.6%0.5000.050-0.015

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq246_017
Europa Clipper will arrive at Jupiter in 2030, conducting 50Peter Diamandis
37.7%0.6500.050-0.086
prereq247_035
Dario Amodei will solve most/all neurological diseases by enDario Amodei
38.8%0.7000.050-0.077
prereq246_016
Dragonfly nuclear-powered octicopter arrives at Titan in 203Peter Diamandis
35.6%0.6500.050-0.065
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050-0.061
prereqSEM_034
True artificial general intelligence will be achieved betweeDemis Hassabis
28.7%0.5500.050-0.036

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (8)

Predictions that must hit first
TypePredTitleDomainLag
prereq235_002Anthropic will exceed OpenAI in revenue this year (2026).AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereq234_012Anthropic revenue will cross OpenAI revenue in middle of 2026Markets/Stocks
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
prereqSEM_0422025 will be the definitive year that agentic systems finally hit the mainstream.AI/Agents
killerTK14Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (5)

Predictions enabled by this
TypePredTitleDomainLag
prereq235_030Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 2033.Biotech/Longevity
prereq247_035Dario Amodei will solve most/all neurological diseases by end of decadeBiotech/Longevity
prereq246_017Europa Clipper will arrive at Jupiter in 2030, conducting 50 passes near Europa.Space
prereq246_016Dragonfly nuclear-powered octicopter arrives at Titan in 2034.Space
prereqSEM_034True artificial general intelligence will be achieved between 2032 and 2042 — 'first we solve AI, then use AI to solve everything else'.AI/AGI

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=6P0uTDGDr-I",
  "mode": "FORECAST",
  "role": "Host",
  "context": "I've been predicting on the public record for many many episodes now that we're nearing a time... when AI is positioned to bulk solve math, the physical sciences, engineering, medicine, material sciences. These will all get bulk solved.",
  "to_year": 2030,
  "verbatim": "I've been predicting on the public record for many many episodes now that we're nearing a time, in fact, we'll talk about it later in this episode, when AI is positioned to bulk solve math, the physical sciences, engineering, medicine, material sciences. These will all get bulk solved.",
  "conv_cues": "been predicting on the public record",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "nearing a time / starting now",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Open-source AI literature-review tool surpasses major LLMs on citation accuracy",
      "source": "Nature: Open-source AI tool beats giant LLMs in literature reviews",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -11,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://www.nature.com/articles/d41586-026-00347-9",
      "expected_date": "2026-02-01",
      "observed_date": "2026-02-01",
      "research_origin": "deep_research",
      "measurement_criterion": "Nature documents AI tool exceeding major LLMs at scientific literature review with human-level citation accuracy"
    },
    {
      "kind": "llm_pre_event",
      "label": "AI compresses drug-discovery timelines from years to weeks (validated pipeline)",
      "source": "Medium / industry analysis: How AI is Transforming Drug Discovery in 2026",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -10,
      "source_id": null,
      "confidence": 0.6,
      "source_url": "https://medium.com/@unicodeveloper/how-ai-is-transforming-drug-discovery-in-2026-0d8c7c600428",
      "expected_date": "2026-03-01",
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep",
      "research_origin": "deep_research",
      "measurement_criterion": "Published case study or industry confirmation of AI compressing lead-to-candidate timeline by >=10x in named therapeutic program"
    },
    {
      "kind": "prereq",
      "label": "Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) a",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -9,
      "source_id": "SEM_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Training runs costing $10 billion for a single model will commence sometime in 2025.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -8,
      "source_id": "SEM_008",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic revenue will cross OpenAI revenue in middle of 2026",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -7,
      "source_id": "234_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic will exceed OpenAI in revenue this year (2026).",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "235_002",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "2025 will be the definitive year that agentic systems finally hit the mainstream.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -5,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "Autonomous AI a
... (truncated)