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CMQ_022predictionAIsuperintelligence

AGI will arrive within a decade (by 2030) — driven primarily by massive raw compute deployment and neural-network scaling.

Predictor: Elon Musk

Prior probability
50.0%
Current probability
34.2%
evolves via intake + LBP
Conviction
5/5
Signal quality
A
Resolution
pending
Window
2026-01-01 – 2030-10-31
Edges in / out
7 / 0
Tickers exposed
13

Prediction text

AGI will arrive within a decade (by 2030) — driven primarily by massive raw compute deployment and neural-network scaling. | xAI Colossus phase-2 scaling; Grok-6+ releases

Key catalyst: xAI Colossus phase-2 scaling; Grok-6+ releases

Watch events: xAI Colossus phase 2 deployment; Grok capability benchmarks; Tesla Dojo v2 disclosures.

Resolution evidence

Status: pending

xAI Colossus scale validates compute-first thesis; Tesla FSD v13/v14 and Optimus G3 demonstrate embodied AI progress.

Predictor: Elon Musk

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0142
excellent
Hits / Misses
1 / 0
of 3 resolved
Hit rate
33.3%
Calibration plot (stated vs observed)

Evidence about this node from Elon Musk 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: agi_breakthrough_5y

Linked via embedding similarity 0.651

Major capability discontinuity (e.g. AGI by named target year, 5-year horizon)

Base rate
20.0%
1/5 historical
Inside weight
Outside weight
no pull
inside 34.2% → blend 34.2% 0.0pp)

Tetlock-style outside view: at TRF=1 (just predicted), outside view dominates (w_in=0.3). At TRF=0 (deadline), inside view dominates (w_in=1.0). The blend regularizes overconfident inside views toward the historical base rate.

Probability over time

8 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-05-032026-05-24
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 34.2%

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: 1 fired ✓ · 6 pending
  1. 2026-04-01hitAI inference cost-per-token falls 90%+ from early 2025 baseline
    How: Per-token API pricing for equivalent-capability frontier models declines 90% or more vs early 2025 baseline
    Source: https://www.silicondata.com/blog/llm-cost-per-token — 90% collapse since early 2025conf 95%
    Notes: HIT — per-token prices have fallen 9x-900x/year per benchmark. Compute deflation supports the AGI-by-scaling thesis.
  2. 2026-11-24pendingQ1 window check-in (25%)
  3. 2026-06-01 → 2027-06-30pendingxAI Colossus phase-2 expansion confirmed for Grok 5+ training
    How: xAI publicly confirms Colossus phase-2 buildout (1M+ GPU cluster) is operational and used for Grok 5 training
    Source: https://www.revolutioninai.com/2026/04/xai-grok-5-agi-10-trillion-parameters-explained.html — 10T parameter Grok 5 planconf 65%
  4. 2026-06-01 → 2028-06-30pendingFrontier model crosses 10T parameters
    How: OpenAI, xAI, Google, Anthropic, or Meta confirms training a model 10 trillion parameters or larger (active or total)
    Source: Stanford AI Index, public lab disclosuresconf 55%
  5. 2026-06-01 → 2028-06-30pendingLeading AI lab publicly forecasts AGI within 24 months
    How: Anthropic, OpenAI, or DeepMind CEO publicly claims AGI within 24 months with technical roadmap
    Source: Lab blog posts, Senate testimony, podcast appearancesconf 55%
    Notes: Amodei has already gestured at 2-3 year window in Senate testimony.
  6. 2027-10-17pendingQ2 window check-in (50%)
  7. 2028-09-08pendingQ3 window check-in (75%)
  8. 2029-01-01 → 2030-10-31pendingIndependent body (METR/Apollo/MIRI) confirms AGI achieved by 2030
    How: Independent technical assessment (METR, Apollo Research, AI Safety Institutes) confirms AGI threshold met before Oct 2030
    Source: AISI UK/US assessments, METR evaluationsconf 35%
    Notes: Kalshi prediction market: 40% chance OpenAI AGI by 2030. Hassabis: 50% by EOD.

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: 34%)

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
LBP2026-05-24T02:00:02Z34.2%+5.1pp
Network propagation: 29.1% → 34.2%
4-iter LBP, residual 0.01000 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 806b02f8
intake_event_update2026-05-21T23:15:16Z29.1%-10.1pp
intake:7afeeb9a-f217-4dd2-b910-24ff14bdfc39 bayesian_v2 inside=0.502 blend=0.291 LLR=0.446 κ=0.64 w_in=0.36 agi_breakthrough_5y
Raw metadata
{
  "trf": 0.9200856375517028,
  "kappa": 0.6429,
  "base_rate": 0.2,
  "predictor": "Elon Musk",
  "total_llr": 0.6931471805599453,
  "bayesian_v2": true,
  "prior_logit": -0.4387754681740146,
  "bayes_factor": "1.6:1 favoring",
  "blend_reason": "blend 36% inside / 64% outside (TRF=0.920, base_rate=0.200 from agi_breakthrough_5y)",
  "inside_prior": 0.3920327893243986,
  "kappa_source": "predictor_table",
  "blend_applied": true,
  "contributions": [
    {
      "llr": 0.6931471805599453,
      "kappa": 0.6429,
      "label": "Doubling-time acceleration extends Musk's AGI-by-2030 thesis support.",
      "adjusted_llr": 0.4456243223819888
    }
  ],
  "evidence_kind": "intake_event_update",
  "inside_source": "history_v2",
  "inside_weight": 0.355940053713808,
  "outside_weight": 0.644059946286192,
  "posterior_prob": 0.2910233907608812,
  "evidence_origin": "daily_intake",
  "llm_suggestions": [
    {
      "polarity": "corroborates",
      "status_change": "unchanged",
      "evidence_strength": "moderate",
      "delta_prob_suggestion": 0.03
    }
  ],
  "posterior_logit": 0.006848854207974209,
  "predictor_brier": 0.01,
  "evidence_doc_ids": [],
  "inside_posterior": 0.5017122068591529,
  "blended_posterior": 0.2910233907608812,
  "reference_class_id": "agi_breakthrough_5y",
  "total_adjusted_llr": 0.4456243223819888,
  "predictor_n_resolved": 2
}
LBP2026-05-10T02:00:02Z39.2%+1.1pp
Network propagation: 38.1% → 39.2%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z38.1%+2.1pp
Network propagation: 36.0% → 38.1%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z36.0%+7.2pp
Network propagation: 28.8% → 36.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
legacy v12026-04-30T16:13:50Z28.8%-7.2pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.288 w_in=0.35 agi_breakthrough_5y
LBP2026-04-30T02:18:57Z36.0%+7.2pp
Network propagation: 28.8% → 36.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef
legacy v12026-04-30T01:56:50Z28.8%-21.2pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.288 w_in=0.35 agi_breakthrough_5y

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+0.113
killerTK02
AI Compute Supply Shock (TSMC/Taiwan Disruption)
12.0%0.0500.500+0.104
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.500+0.091

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

13 ticker(s) linked

Beneficiaries (13)

BBAINVDAGTLBSOUNAIMETAMSFTORCLTCEHYAMZNBABAGOOGLIBM

Prerequisites (7)

Predictions that must hit first
TypePredTitleDomainLag
correlateS_GRID_50GW_202750GW dedicated AI/data center grid by Dec 2027energy_grid_expansion
correlateS_AGI_FAST_2027AGI fast: drop-in remote worker by 2027-09agi_general_capability
correlateS_AGI_SLOW_2031AGI slow: Schmidt/Hassabis 5-10 year pathagi_general_capability
correlateS_AGI_WINTER_2036PLUSAGI delayed: capability plateau or AI winteragi_general_capability
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK02AI Compute Supply Shock (TSMC/Taiwan Disruption)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Linked documents (3)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.750codex_research_packNVIDIA - Rubin Platform, Open Models, Autonomous Driving at CEScorroboratespending2026-01-06
0.750codex_research_packNVIDIA - Vera Rubin Opens Agentic AI Frontiercorroboratespending2026-03-16
0.565manifoldWill Derek Thompson run for office by EOY 2030?30%mentionspending2026-04-28

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "AGI",
  "mode": "FORECAST",
  "role": "Guest-CEO",
  "context": "Musk's xAI Colossus (200K→1M H100-class GPUs) and Tesla Dojo represent his concrete bet on this thesis.",
  "to_year": 2030,
  "conv_cues": "within a decade; CEO-stated",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "within a decade",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "AI inference cost-per-token falls 90%+ from early 2025 baseline",
      "notes": "HIT — per-token prices have fallen 9x-900x/year per benchmark. Compute deflation supports the AGI-by-scaling thesis.",
      "source": "https://www.silicondata.com/blog/llm-cost-per-token — 90% collapse since early 2025",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://www.silicondata.com/blog/llm-cost-per-token",
      "expected_date": "2026-07-02",
      "observed_date": "2026-04-01",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-12-31",
        "from": "2026-01-01"
      },
      "measurement_criterion": "Per-token API pricing for equivalent-capability frontier models declines 90% or more vs early 2025 baseline"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -6,
      "source_id": null,
      "expected_date": "2026-11-24",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "xAI Colossus phase-2 expansion confirmed for Grok 5+ training",
      "source": "https://www.revolutioninai.com/2026/04/xai-grok-5-agi-10-trillion-parameters-explained.html — 10T parameter Grok 5 plan",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.65,
      "source_url": "https://www.revolutioninai.com/2026/04/xai-grok-5-agi-10-trillion-parameters-explained.html",
      "expected_date": "2026-12-15",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2027-06-30",
        "from": "2026-06-01"
      },
      "measurement_criterion": "xAI publicly confirms Colossus phase-2 buildout (1M+ GPU cluster) is operational and used for Grok 5 training"
    },
    {
      "kind": "llm_pre_event",
      "label": "Frontier model crosses 10T parameters",
      "source": "Stanford AI Index, public lab disclosures",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2027-06-16",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2028-06-30",
        "from": "2026-06-01"
      },
      "measurement_criterion": "OpenAI, xAI, Google, Anthropic, or Meta confirms training a model 10 trillion parameters or larger (active or total)"
    },
    {
      "kind": "llm_pre_event",
      "label": "Leading AI lab publicly forecasts AGI within 24 months",
      "notes": "Amodei has already gestured at 2-3 year window in Senate testimony.",
      "source": "Lab blog posts, Senate testimony, podcast appearances",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2027-06-16",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-06-30",
        "from": "2026-06-01"
      },
      "measurement_criterion": "Anthropic, OpenAI, or DeepMind CEO publicly claims AGI within 24 months with technical roadmap"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2027-10-17",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (7
... (truncated)