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238_007predictionAIAI-scaling

There will be no more than ~10 foundation model labs globally, but thousands of successful AI startups

Predictor: Eric Schmidt · ep#238 "Meta Buys Moltbook, GPT 5.4, and Fruitfly Brain Upload | Moonshots Live at The Abundance Summit 238" · source

Prior probability
60.0%
Current probability
44.1%
evolves via intake + LBP
Conviction
4/5
Signal quality
C
Resolution
pending
Window
2026-04-30 – 2031-11-30
Edges in / out
6 / 0
Tickers exposed
37

Prediction text

There will be no more than ~10 foundation model labs globally, but thousands of successful AI startups | he said well look there's five there there won't be more than 10 but there will be thousands of successful AI startups that percolate out... yes, a few AI labs worth trillions of dollars, thousands and thousands of successful startups and a lot of incumbent companies that are in deep deep trouble.

Verbatim quote

From episode "Meta Buys Moltbook, GPT 5.4, and Fruitfly Brain Upload | Moonshots Live at The Abundance Summit 238"
he said well look there's five there there won't be more than 10 but there will be thousands of successful AI startups that percolate out... yes, a few AI labs worth trillions of dollars, thousands and thousands of successful startups and a lot of incumbent companies that are in deep deep trouble.

Predictor: Eric Schmidt

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0064
excellent
Hits / Misses
3 / 0
of 3 resolved
Hit rate
100.0%
Calibration plot (stated vs observed)

Evidence about this node from Eric Schmidt 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

5 prob_history rows
0%25%50%75%100%prior 60%2026-04-302026-05-032026-05-17
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 44.1%

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. 2027-04-23pendingQ1 window check-in (25%)
  2. 2026-06-01 → 2028-06-30pendingOpenAI or Anthropic crosses $1T valuation
    How: Primary or secondary funding round (or IPO) prices either firm at >=$1T post-money
    Source: deep_research_enrichedconf 55%
  3. 2026-09-01 → 2028-12-31pendingFirst major frontier lab acquired or shuttered citing scaling-cost economics
    How: Public M&A or wind-down of one of: Mistral, Cohere, Reka, AI21, Inflection-style consolidation, with explicit reasoning tied to compute economics
    Source: deep_research_enrichedconf 55%
  4. 2026-12-01 → 2028-12-31pendingFunded foundation-model labs (>=$100M raised) plateaus at <=10 globally
    How: Pitchbook / Crunchbase / SemiAnalysis tally confirms <=10 firms have raised >=$100M for frontier foundation-model training (>=10^25 FLOP run)
    Source: deep_research_enrichedconf 70%
  5. 2028-04-16pendingQ2 window check-in (50%)
  6. 2027-01-01 → 2029-12-31pendingNumber of profitable AI-application startups (>$10M ARR) exceeds 1,000
    How: ICONIQ, Bessemer State of AI, or peer report tallies >=1,000 distinct AI-application companies at >=$10M ARR
    Source: deep_research_enrichedconf 50%
  7. 2027-06-01 → 2029-12-31pendingPublic 10-K/earnings disclosure: legacy SaaS incumbent revenue down >15% citing AI displacement
    How: At least one publicly-traded incumbent (CRM, ADBE, NOW, INTU, DOCU, or peer) reports >=15% YoY revenue decline with management explicitly citing AI native competitors
    Source: deep_research_enrichedconf 35%
  8. 2029-04-10pendingQ3 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: 44%)

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
LBP2026-05-17T02:00:01Z44.1%-1.1pp
Network propagation: 45.2% → 44.1%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
LBP2026-05-10T02:00:02Z45.2%-2.2pp
Network propagation: 47.4% → 45.2%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z47.4%-4.4pp
Network propagation: 51.8% → 47.4%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z51.8%-2.8pp
Network propagation: 54.6% → 51.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z54.6%-5.4pp
Network propagation: 60.0% → 54.6%
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
prereqS_AGI_SLOW_2031
AGI slow: Schmidt/Hassabis 5-10 year path
25.0%0.6000.050-0.253
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.600+0.104
killerTK02
AI Compute Supply Shock (TSMC/Taiwan Disruption)
12.0%0.0500.600+0.093
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.600+0.077
killerTK09
Energy Grid Cap (Data Center Power Wall)
35.0%0.0500.600-0.033

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

37 ticker(s) linked

Beneficiaries (24)

MUWULFIRENEQIXALABAPLDASMIYASMLPLABNVDANBISCRWVAAPLAMTAMZNDELLGOOGLIRMLNVGYMETAMSFTORCLSFTBYSTX

Adverse (6)

ACNGENCHGGIBMWNSLRN

Prerequisites (6)

Predictions that must hit first
TypePredTitleDomainLag
prereqS_AGI_SLOW_2031AGI slow: Schmidt/Hassabis 5-10 year pathagi_general_capability
killerTK09Energy Grid Cap (Data Center Power Wall)
killerTK05Rate Regime Persistence (10y > 5% through 2028)
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

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "5-10 foundation model labs; thousands of startups",
  "url": "https://www.youtube.com/watch?v=d__HRChE2ZE",
  "mode": "CITED_PREDICTION",
  "role": "Cited-Executive",
  "context": "Eric uh he he said um one of the questions actually from the crowd is how many foundation model labs are there going to be? uh and he said well look there's five there there won't be more than 10 but there will be thousands of successful AI startups that percolate out and a lot of what we'll see in the news here reinforces what he was saying.",
  "cited_by": "Salim Ismail",
  "verbatim": "he said well look there's five there there won't be more than 10 but there will be thousands of successful AI startups that percolate out... yes, a few AI labs worth trillions of dollars, thousands and thousands of successful startups and a lot of incumbent companies that are in deep deep trouble.",
  "conv_cues": "won't be more than",
  "direction": "NUMERIC_TARGET",
  "timeframe": "Unspecified future",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -8,
      "source_id": null,
      "expected_date": "2027-04-23",
      "observed_date": null
    },
    {
      "kind": "llm_post_event",
      "label": "OpenAI or Anthropic crosses $1T valuation",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -7,
      "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": "Primary or secondary funding round (or IPO) prices either firm at >=$1T post-money"
    },
    {
      "kind": "llm_pre_event",
      "label": "First major frontier lab acquired or shuttered citing scaling-cost economics",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2027-11-01",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2026-09-01"
      },
      "measurement_criterion": "Public M&A or wind-down of one of: Mistral, Cohere, Reka, AI21, Inflection-style consolidation, with explicit reasoning tied to compute economics"
    },
    {
      "kind": "llm_pre_event",
      "label": "Funded foundation-model labs (>=$100M raised) plateaus at <=10 globally",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.7,
      "source_url": "https://llm-stats.com/llm-updates",
      "expected_date": "2027-12-16",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2026-12-01"
      },
      "measurement_criterion": "Pitchbook / Crunchbase / SemiAnalysis tally confirms <=10 firms have raised >=$100M for frontier foundation-model training (>=10^25 FLOP run)"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2028-04-16",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Number of profitable AI-application startups (>$10M ARR) exceeds 1,000",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.5,
      "expected_date": "2028-07-01",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2029-12-31",
        "from": "2027-01-01"
      },
      "measurement_criterion": "ICONIQ, Bessemer State of AI, 
... (truncated)