← Cockpit
241_037predictionAIAI-timing

Chinese AI strategy will stay open source / open weights

Predictor: Eric Schmidt · ep#241 "Eric Schmidt on the Robotics Race, Singularity Timeline, and Energy Shortage" · source

Prior probability
60.0%
Current probability
49.5%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2026-06-01 – 2026-06-30
Edges in / out
12 / 5
Tickers exposed
33

Prediction text

Chinese AI strategy will stay open source / open weights | China's approach, which has produced DCV4, Quinn, Kimmy 2, Kimmy version 3, etc. and more coming, is it's all open source open weights

Verbatim quote

From episode "Eric Schmidt on the Robotics Race, Singularity Timeline, and Energy Shortage"
China's approach, which has produced DCV4, Quinn, Kimmy 2, Kimmy version 3, etc. and more coming, is it's all open source open weights

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

4 prob_history rows
0%25%50%75%100%prior 60%2026-04-302026-05-032026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 49.5%

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 fired ✓
  1. 2026-02-12hitQwen image gen model released open-source for IOC
    How: Alibaba publicly releases Qwen-Image 2.0 or peer model under open-source license with Olympic deployment
    Source: https://www.technologyreview.com/2026/02/12/1132811/whats-next-for-chinese-open-source-ai/conf 95%
    Notes: HIT — Qwen-Image 2.0 powers IOC tools for 2026 Milan Olympics, validating sustained Chinese open-source strategy.
  2. 2026-04-15hitKimi K2.5 released open-source and surpasses Claude Opus by token usage
    How: Moonshot AI releases Kimi 2.5+ with open weights and reaches top-3 in OpenRouter or comparable usage rankings
    Source: https://benchlm.ai/best/chinese-modelsconf 95%
    Notes: HIT — Kimi K2.5 surpassed Claude Opus by token count, most-used AI model.
  3. 2026-04-24hitDeepSeek V4 released as open-source weights
    How: DeepSeek publicly releases V4 model with open weights, continuing R1/V3 open-source pattern
    Source: https://www.cnbc.com/2026/04/24/deepseek-v4-llm-preview-open-source-ai-competition-china.htmlconf 99%
    Notes: HIT — DeepSeek V4 released open-source April 24 2026, validating Schmidt's claim about Chinese open-weight strategy.
  4. 2026-06-01 → 2026-12-31pendingChinese open-weight downloads exceed 1B cumulative
    How: Hugging Face or comparable tracker shows Qwen+DeepSeek+Kimi cumulative downloads exceed 1B
    Source: https://www.understandingai.org/p/the-best-chinese-open-weight-modelsconf 85%
    Notes: Qwen alone exceeded 600M downloads by Sep 2024; trajectory points to 1B+ for combined Chinese open-weights.
  5. 2027-01-01 → 2028-12-31pendingChinese model market share in commercial deployments exceeds 30%
    How: OpenRouter, Together.ai or peer infra layer reports ≥30% of inference traffic on Chinese open-weight models globally
    Source: https://www.cfr.org/articles/deepseek-v4-signals-a-new-phase-in-the-u-s-china-ai-rivalryconf 40%

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: 49%)

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
LBP2026-05-10T02:00:02Z49.5%-1.3pp
Network propagation: 50.8% → 49.5%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z50.8%-2.1pp
Network propagation: 52.9% → 50.8%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z52.9%-3.3pp
Network propagation: 56.2% → 53.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z56.2%-3.8pp
Network propagation: 60.0% → 56.2%
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
prereq234_012
Anthropic revenue will cross OpenAI revenue in middle of 202Peter Diamandis
67.1%0.6000.050-0.079
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.600+0.050
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.6000.050-0.044
prereqSEM_012
Nvidia quadrupled chip production output while only doublingJensen Huang
75.0%0.6000.050-0.036
prereqSEM_008
Training runs costing $10 billion for a single model will coDario Amodei
76.9%0.6000.050-0.026

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq231_013
Math is cooked (will be solved), physics cooked, biology chaAlex Wissner-Gross
35.4%0.6200.050-0.027
prereqCMQ_002
By 2028, AI systems will reach 'independent researcher' leveSam Altman
31.4%0.5500.050-0.021
prereq241_043
ASI will arrive within 2 years to 5 years to this next decadPeter Diamandis
35.9%0.6500.050-0.017
prereq232_055
We're exiting the industrial age permanently as recursive sePeter Diamandis
35.5%0.7000.050+0.011
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050-0.002

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (12)

Predictions that must hit first
TypePredTitleDomainLag
prereq234_012Anthropic revenue will cross OpenAI revenue in middle of 2026Markets/Stocks
prereq238_009Recursive self-improvement is already happening now (no longer three years out)AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereqSEM_0422025 will be the definitive year that agentic systems finally hit the mainstream.AI/Agents
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
correlateS_AGI_MID_2029AGI mid: Kurzweil 2029 pathagi_general_capability
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
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
prereq232_055We're exiting the industrial age permanently as recursive self-improvement unfolds.AI
prereq241_043ASI will arrive within 2 years to 5 years to this next decadeAI
prereq231_013Math is cooked (will be solved), physics cooked, biology char broiled.AI
prereqCMQ_002By 2028, AI systems will reach 'independent researcher' level — driving autonomous scientific discoveries without human intervention.AI

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.701manifoldWill OpenAI publicly share software it developed to make its AI run on chips from different providers, in 2026?26%mentionspending2026-06-01
0.673manifoldWill OpenAI broadly release a dedicated Cyber model to Trusted Access users by Sep 30, 2026?68%mentionspending2026-05-14
0.664github_releasefacebookresearch/neuroai v0.2.2mentionspending2026-05-26
0.652manifoldWill a US open-weights LLM outrank every Chinese open-weights LLM on LMArena at the end of 2027?32%mentionspending2026-05-31
0.650github_releaseopenai/openai-python v2.21.0mentionspending2026-02-14
0.648github_releaseopenai/openai-python v2.29.0mentionspending2026-03-17
0.648github_releaseopenai/openai-python v2.14.0mentionspending2025-12-19
0.647github_releasegoogle-deepmind/alphafold v2.3.2mentionspending2023-04-05
0.645github_releaseopenai/openai-python v2.7.2mentionspending2025-11-10
0.642github_releaseopenai/openai-python v2.20.0mentionspending2026-02-10

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=DpwmmXmzvfo",
  "mode": "THESIS",
  "role": "Guest-CEO",
  "context": "it's all open source open weights... and more coming",
  "to_year": 2026,
  "verbatim": "China's approach, which has produced DCV4, Quinn, Kimmy 2, Kimmy version 3, etc. and more coming, is it's all open source open weights",
  "conv_cues": "and more coming",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "ongoing",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Qwen image gen model released open-source for IOC",
      "notes": "HIT — Qwen-Image 2.0 powers IOC tools for 2026 Milan Olympics, validating sustained Chinese open-source strategy.",
      "source": "https://www.technologyreview.com/2026/02/12/1132811/whats-next-for-chinese-open-source-ai/",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://www.technologyreview.com/2026/02/12/1132811/whats-next-for-chinese-open-source-ai/",
      "expected_date": "2026-02-12",
      "observed_date": "2026-02-12",
      "research_origin": "deep_research",
      "measurement_criterion": "Alibaba publicly releases Qwen-Image 2.0 or peer model under open-source license with Olympic deployment"
    },
    {
      "kind": "llm_pre_event",
      "label": "Kimi K2.5 released open-source and surpasses Claude Opus by token usage",
      "notes": "HIT — Kimi K2.5 surpassed Claude Opus by token count, most-used AI model.",
      "source": "https://benchlm.ai/best/chinese-models",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://benchlm.ai/best/chinese-models",
      "expected_date": "2026-04-01",
      "observed_date": "2026-04-15",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-06-30",
        "from": "2026-01-01"
      },
      "measurement_criterion": "Moonshot AI releases Kimi 2.5+ with open weights and reaches top-3 in OpenRouter or comparable usage rankings"
    },
    {
      "kind": "llm_pre_event",
      "label": "DeepSeek V4 released as open-source weights",
      "notes": "HIT — DeepSeek V4 released open-source April 24 2026, validating Schmidt's claim about Chinese open-weight strategy.",
      "source": "https://www.cnbc.com/2026/04/24/deepseek-v4-llm-preview-open-source-ai-competition-china.html",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.99,
      "source_url": "https://www.cnbc.com/2026/04/24/deepseek-v4-llm-preview-open-source-ai-competition-china.html",
      "expected_date": "2026-04-24",
      "observed_date": "2026-04-24",
      "research_origin": "deep_research",
      "measurement_criterion": "DeepSeek publicly releases V4 model with open weights, continuing R1/V3 open-source pattern"
    },
    {
      "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": -5,
      "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": -4,
      "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": -3,
      "source_id": "234_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "2025 wil
... (truncated)