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234_044predictionAIAI-timing

Intelligence does not have a fixed upper bound; governance will cap it before IQ

Predictor: Salim Ismail · ep#234 "Anthropic vs. The Pentagon, Claude Outpaces ChatGPT, and Consulting Gets Replaced" · source

Prior probability
50.0%
Current probability
38.8%
evolves via intake + LBP
Conviction
3/5
Signal quality
C
Resolution
pending
Window
2026-04-30 – 2040-08-31
Edges in / out
4 / 0
Tickers exposed
33

Prediction text

Intelligence does not have a fixed upper bound; governance will cap it before IQ | intelligence if we define it in the traditional term because everybody knows my beef with the the framing here but it probably doesn't have a fixed upper bound because once you have recursive self-improvement there it becomes a function of compute and architecture that you're going to end up with governance ceilings and other constraints much more so than the IQ ceilings.

Verbatim quote

From episode "Anthropic vs. The Pentagon, Claude Outpaces ChatGPT, and Consulting Gets Replaced"
intelligence if we define it in the traditional term because everybody knows my beef with the the framing here but it probably doesn't have a fixed upper bound because once you have recursive self-improvement there it becomes a function of compute and architecture that you're going to end up with governance ceilings and other constraints much more so than the IQ ceilings.

Predictor: Salim Ismail

κ + Brier as of 2026-05-22
κ (discount)
0.643
Brier
0.0144
excellent
Hits / Misses
1 / 0
of 2 resolved
Hit rate
50.0%
Calibration plot (stated vs observed)

Evidence about this node from Salim Ismail 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 0.586

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 38.8% → blend 38.8% 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

6 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-04-302026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 38.8%

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: 8 pending
  1. 2026-08-02pendingEU AI Act fully applicable (Aug 2 2026)
    How: EU AI Act becomes fully enforceable per AIA Art. 113
    Source: deep_research_enrichedconf 95%
  2. 2026-06-01 → 2027-12-31pendingFirst model crosses 10^26 FLOP training compute threshold
    How: Public disclosure (paper, system card, or regulatory filing) that a model was trained at >=10^26 FLOPs
    Source: deep_research_enrichedconf 70%
  3. 2027-01-01 → 2029-12-31pendingEU Commission lowers compute threshold for systemic-risk GPAI from 10^25 toward 10^24
    How: EU Commission delegated act adjusts the systemic-risk compute threshold downward from 10^25 FLOPs
    Source: llm_enrichedconf 45%
  4. 2028-08-20pendingQ1 window check-in (25%)
  5. 2028-01-01 → 2032-12-31pendingFirst major nation imposes compute or capability cap on frontier AI training
    How: G7 government enacts statute or executive order limiting training-run compute or capability scope (not just notification)
    Source: llm_enrichedconf 55%
  6. 2030-12-12pendingQ2 window check-in (50%)
  7. 2033-04-04pendingQ3 window check-in (75%)
  8. 2030-01-01 → 2040-12-31pendingInternational compute-cap treaty (analogous to nuclear non-proliferation) signed by >=3 of US/EU/UK/China
    How: Multilateral treaty formally limiting frontier-AI training compute signed by >=3 major AI powers
    Source: llm_enrichedconf 30%

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: 39%)

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
LBP2026-05-10T02:00:02Z38.8%+1.4pp
Network propagation: 37.4% → 38.8%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z37.4%+2.7pp
Network propagation: 34.7% → 37.4%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z34.7%+7.2pp
Network propagation: 27.5% → 34.7%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
legacy v12026-04-30T16:13:50Z27.5%-7.2pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.275 w_in=0.30 agi_breakthrough_5y
LBP2026-04-30T02:18:57Z34.7%+7.2pp
Network propagation: 27.5% → 34.7%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef
legacy v12026-04-30T01:56:50Z27.5%-22.5pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.275 w_in=0.30 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
prereqS_ASI_SLOW_2040PLUS
ASI slow: post-2040 / soft takeoff
60.0%0.5000.050-0.068
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.500+0.067
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.500+0.044
killerTK14
Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
20.0%0.0500.500+0.022

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (4)

Predictions that must hit first
TypePredTitleDomainLag
prereqS_ASI_SLOW_2040PLUSASI slow: post-2040 / soft takeoffasi_recursive_self_improvement
killerTK14Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Linked documents (2)

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=dmtvGKuRE64",
  "mode": "THESIS",
  "role": "Host",
  "context": "intelligence if we define it in the traditional term because everybody knows my beef with the the framing here but it probably doesn't have a fixed upper bound because once you have recursive self-improvement there it becomes a function of compute and architecture that you're going to end up with governance ceilings and other constraints much more so than the IQ ceilings.",
  "verbatim": "intelligence if we define it in the traditional term because everybody knows my beef with the the framing here but it probably doesn't have a fixed upper bound because once you have recursive self-improvement there it becomes a function of compute and architecture that you're going to end up with governance ceilings and other constraints much more so than the IQ ceilings.",
  "conv_cues": "probably",
  "direction": "MIXED",
  "timeframe": "Unspecified future",
  "conv_level": "MEDIUM",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "EU AI Act fully applicable (Aug 2 2026)",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai",
      "expected_date": "2026-08-02",
      "research_origin": "deep_research",
      "measurement_criterion": "EU AI Act becomes fully enforceable per AIA Art. 113"
    },
    {
      "kind": "llm_pre_event",
      "label": "First model crosses 10^26 FLOP training compute threshold",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.7,
      "source_url": "https://law-ai.org/the-role-of-compute-thresholds-for-ai-governance/",
      "expected_date": "2027-03-17",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2027-12-31",
        "from": "2026-06-01"
      },
      "measurement_criterion": "Public disclosure (paper, system card, or regulatory filing) that a model was trained at >=10^26 FLOPs"
    },
    {
      "kind": "llm_pre_event",
      "label": "EU Commission lowers compute threshold for systemic-risk GPAI from 10^25 toward 10^24",
      "source": "llm_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.45,
      "expected_date": "2028-07-01",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2029-12-31",
        "from": "2027-01-01"
      },
      "measurement_criterion": "EU Commission delegated act adjusts the systemic-risk compute threshold downward from 10^25 FLOPs"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -5,
      "source_id": null,
      "expected_date": "2028-08-20",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "First major nation imposes compute or capability cap on frontier AI training",
      "source": "llm_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2030-07-02",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2032-12-31",
        "from": "2028-01-01"
      },
      "measurement_criterion": "G7 government enacts statute or executive order limiting training-run compute or capability scope (not just notification)"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2030-12-12",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpo
... (truncated)