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SPC_022predictionAIAI-science-2026

'2026 will be for AI in science what 2025 was for AI in software engineering' — a transition from AI as coding assistant to acting as scientific sparring partner: generating novel hypotheses, analyzing vast datasets, and dramatically accelerating R&D c...

Predictor: Kevin Weil

Prior probability
62.0%
Current probability
41.4%
evolves via intake + LBP
Conviction
5/5
Signal quality
B
Resolution
in_progress
Window
2026-01-01 – 2026-09-30
Edges in / out
0 / 0
Tickers exposed
6

Prediction text

'2026 will be for AI in science what 2025 was for AI in software engineering' — a transition from AI as coding assistant to acting as scientific sparring partner: generating novel hypotheses, analyzing vast datasets, and dramatically accelerating R&D cycles for material science and propulsion engineering. | First major AI-coauthored scientific breakthrough

Key catalyst: First major AI-coauthored scientific breakthrough

Watch events: OpenAI Deep Research science-grade publications; Nobel-class AI contributions

Resolution evidence

Status: in_progress

OpenAI Science team publications 2025-2026; Deep Research tool enterprise adoption; AlphaProteo / AlphaFold momentum continuing.

Predictor: Kevin Weil

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0200
excellent
Hits / Misses
2 / 0
of 3 resolved
Hit rate
66.7%
Calibration plot (stated vs observed)

Evidence about this node from Kevin Weil 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

2 prob_history rows
0%25%50%75%100%prior 62%2026-05-022026-05-30
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 41.4%

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: 3 overdue ⏱
  1. 2026-02-14overdueQ1 window check-in (25%)
  2. 2026-03-30overdueQ2 window check-in (50%)
  3. 2026-05-13overdueQ3 window check-in (75%)

No downstream cascades — this prediction is a leaf in the dependency graph.

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: 41%)

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_sweep2026-05-30T22:15:00Z41.4%-6.9pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.414 blend=0.414 LLR=-0.279 κ=0.69 no_blend
Raw metadata
{
  "trf": 0.4487974555581937,
  "kappa": 0.6875,
  "base_rate": null,
  "predictor": "Kevin Weil",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": -0.06796629833002035,
  "bayes_factor": "1.3:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.4830149633290875,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "quartile_checkpoint",
      "kappa": 0.6875,
      "label": "Q3 window check-in (75%)",
      "weight": 0.05,
      "strength": "weak",
      "confidence": null,
      "source_url": null,
      "adjusted_llr": -0.278757261824363,
      "expected_date": "2026-05-13",
      "measurement_criterion": null
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.6858417811092643,
  "outside_weight": 0.3141582188907357,
  "posterior_prob": 0.41417717404793875,
  "posterior_logit": -0.3467235601543833,
  "predictor_brier": 0.02,
  "inside_posterior": 0.41417717404793875,
  "blended_posterior": 0.41417717404793875,
  "reference_class_id": null,
  "total_adjusted_llr": -0.278757261824363,
  "predictor_n_resolved": 3
}
metadata_milestone_miss_sweep2026-05-02T22:07:21Z48.3%-13.7pp
metadata_milestone_miss_sweep bayesian_v2 n=2 inside=0.483 blend=0.483 LLR=-0.558 κ=0.69 no_blend
Raw metadata
{
  "trf": 0.5517581791161151,
  "kappa": 0.6875,
  "base_rate": null,
  "predictor": "Kevin Weil",
  "total_llr": -0.8109302162163288,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": 0.4895482253187058,
  "bayes_factor": "1.7:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.62,
  "kappa_source": "predictor_table",
  "n_milestones": 2,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "quartile_checkpoint",
      "kappa": 0.6875,
      "label": "Q1 window check-in (25%)",
      "weight": 0.05,
      "strength": "weak",
      "confidence": null,
      "source_url": null,
      "adjusted_llr": -0.278757261824363,
      "expected_date": "2026-02-14",
      "measurement_criterion": null
    },
    {
      "llr": -0.4054651081081644,
      "kind": "quartile_checkpoint",
      "kappa": 0.6875,
      "label": "Q2 window check-in (50%)",
      "weight": 0.05,
      "strength": "weak",
      "confidence": null,
      "source_url": null,
      "adjusted_llr": -0.278757261824363,
      "expected_date": "2026-03-30",
      "measurement_criterion": null
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "prior_prob",
  "inside_weight": 0.6137692746187193,
  "outside_weight": 0.38623072538128067,
  "posterior_prob": 0.4830149633290875,
  "posterior_logit": -0.06796629833002021,
  "predictor_brier": 0.02,
  "inside_posterior": 0.4830149633290875,
  "blended_posterior": 0.4830149633290875,
  "reference_class_id": null,
  "total_adjusted_llr": -0.557514523648726,
  "predictor_n_resolved": 3
}

Network propagation neighbors

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

No propagation data yet. Run inference/.venv/bin/python scripts/ops/run_loopy_belief_propagation.py on the droplet, or wait for the Sunday 02:00 UTC weekly cron.

Ticker exposure

6 ticker(s) linked

Beneficiaries (6)

FROGGTLBBABAGOOGLMSFTTEAM

Prerequisites (0)

Predictions that must hit first
TypePredTitleDomainLag
No prerequisites

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Validations (1)

Resolution events
Observed atStatusByNotes
2026-04-29partialthesis_timeline_v1.0_importOpenAI Science team publications 2025-2026; Deep Research tool enterprise adoption; AlphaProteo / AlphaFold momentum continuing.

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.622manifoldWhat award will I get at the 2026 AMM?mentionspending2026-05-07
0.622manifoldWhat award will I get at the 2026 AMM?mentionspending2026-05-03
0.615manifoldWhat award will I get on the 2026 AMM?mentionspending2026-05-18
0.611manifoldWhat award will I get at AMM 2026?mentionspending2026-05-18
0.592manifoldWhich philosophical subfields will be represented by 3+ PhD-holders at Manifest 2026?mentionspending2026-05-18
0.592manifoldWill MIT accept anyone from their 2026 waitlist?60%mentionspending2026-05-04
0.587manifoldHow many fives will 2025-2026 Frazer AP Biology get?mentionspending2026-05-04
0.581manifoldWho will make Indonesia's IOI 2026 Team?mentionspending2026-05-15
0.576manifoldHow will I do on ARML 2026mentionspending2026-05-26
0.568manifoldWho will make Indonesia's IOAI 2026 Team?mentionspending2026-06-05

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "mode": "FORECAST",
  "role": "Cited-Other",
  "context": "Weil's landmark 2026 framing, extending 234_007 / 238_012 (100 Nobel Prizes). Couples with AI_031 (Hassabis 100 years of biology), CYB_006 (self-writing memory).",
  "to_year": 2026,
  "conv_cues": "coined phrasing; signature Weil framing",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "2026",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2026-02-14",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2026-03-30",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -1,
      "source_id": null,
      "expected_date": "2026-05-13",
      "observed_date": null,
      "miss_emitted_at": "2026-05-30T22:15:00.756418+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "event",
      "label": "'2026 will be for AI in science what 2025 was for AI in software engineering' — a transition from AI as coding assistant to acting as scient",
      "status": "pending",
      "weight": 1,
      "ordinal": 0,
      "source_id": "SPC_022",
      "expected_date": "2026-06-27",
      "observed_date": null
    }
  ],
  "repeat_eps": 1,
  "affiliation": "OpenAI (Head of Science)",
  "attribution": "FIRST_PERSON",
  "granularity": "YEAR",
  "source_refs": "34, 35",
  "target_date": "2026-12-15T00:00:00",
  "display_date": "2026-06-27",
  "episode_date": "2026-04-21T00:00:00",
  "key_catalyst": "First major AI-coauthored scientific breakthrough",
  "parse_method": "YEAR endpoint",
  "domain_bucket": "AI",
  "episode_title": "Strategic Forecasts in Space, Satellites, and Propulsion: 2023-2026 Retrospective and Future Outlook",
  "flag_repeated": false,
  "in_5yr_window": true,
  "source_report": "Space Prediction Research Plan.md (2026-04-21)",
  "appears_in_eps": "SPC-RPT",
  "futurist_phase": "Phase 1 (2026)",
  "is_macro_claim": false,
  "total_mentions": 1,
  "priority_weight": 4,
  "ps_cluster_tags": [
    "C5"
  ],
  "report_evidence": "Anchor section: Deflation of Intelligence / Autonomous Science.",
  "active_end_month": "2026-12",
  "recent_statement": "Weil 2026 OpenAI commentary.",
  "watch_events_raw": "OpenAI Deep Research science-grade publications; Nobel-class AI contributions",
  "months_from_today": 8,
  "probability_layer": "Base-case",
  "active_start_month": "2026-01",
  "december_dispersal": {
    "reason": "december_dispersal: domain=AI → 09/2026",
    "new_date": "2026-09-30",
    "old_date": "2026-12-31",
    "applied_at": "2026-04-30T16:28:34.304992+00:00"
  },
  "flag_nia_bracketed": false,
  "track_record_grade": "A-",
  "track_record_notes": "Weil roadmap framing directionally accurate.",
  "contradicting_notes": "Wet-lab physical constraints still dominant; \"AI-science\" parity with \"AI-software\" may be overstated for 2026 specifically.",
  "flag_near_term_2027": false,
  "flag_high_conviction": true,
  "milestones_phase2_at": "2026-05-01T18:11:32.930476+00:00",
  "milestones_derived_at": "2026-05-02T03:08:51.321889+00:00",
  "reference_class_match": {
    "decision": "keyword_filtered",
    "computed_at": "2026-04-30T01:49:13.796883+00:00",
    "best_id_unfiltered": "regulatory_freeze_window",
    "best_similarity_unfiltered": 0.6086
  },
  "validation_sta