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CYB_019predictionRoboticsworld-model-training-grounds

Deployment of 'world model systems' — AI that accurately simulates and anticipates the physical and thermodynamic dynamics of reality — serves as the critical foundational training ground for embodied agents, letting them experience billions of hours o...

Predictor: Demis Hassabis

Prior probability
80.0%
Current probability
44.4%
evolves via intake + LBP
Conviction
4/5
Signal quality
A
Resolution
in_progress
Window
2026-01-01 – 2030-08-31
Edges in / out
1 / 0
Tickers exposed
0

Prediction text

Deployment of 'world model systems' — AI that accurately simulates and anticipates the physical and thermodynamic dynamics of reality — serves as the critical foundational training ground for embodied agents, letting them experience billions of hours of simulated physical trial-and-error before real-world deployment. | First humanoid deployment trained purely from sim

Key catalyst: First humanoid deployment trained purely from sim

Watch events: Genie 4+ releases; NVIDIA Cosmos adoption

Resolution evidence

Status: in_progress

DeepMind Genie 2 / Genie 3 world models; NVIDIA Cosmos, Tesla FSD sim; Figure Helix training. Billion-hour simulation scales documented.

Predictor: Demis Hassabis

κ + Brier as of 2026-05-22
κ (discount)
0.583
Brier
0.0064
excellent
Hits / Misses
1 / 0
of 1 resolved
Hit rate
100.0%
Calibration plot (stated vs observed)

Evidence about this node from Demis Hassabis 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: humanoid_commercial_volume

Linked via embedding similarity 0.634

>10,000 unit cumulative deployment of humanoid robot SKU within 3 years of debut

Base rate
10.0%
0/3 historical
Inside weight
Outside weight
no pull
inside 44.4% → blend 44.4% 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 80%2026-04-302026-05-102026-05-24
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 44.4%

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 fired ✓ · 5 pending
  1. 2026-03-18hit1X Technologies trains NEO Gamma humanoid using Cosmos Predict + Transfer
    How: 1X publicly confirms Cosmos Predict + Cosmos Transfer used to train NEO Gamma humanoid, per NVIDIA partner announcement
    Source: https://nvidianews.nvidia.com/news/nvidia-and-global-robotics-leaders-take-physical-ai-to-the-real-worldconf 95%
    Notes: HIT — first concrete instance of WFM-trained humanoid going to production.
  2. 2026-04-15hitNVIDIA announces Cosmos 3 unifying world generation + vision reasoning + action sim
    How: NVIDIA publishes Cosmos 3 release notes describing the first world foundation model unifying synthetic world generation, vision reasoning, and action simulation
    Source: https://www.nvidia.com/en-us/ai/cosmos/ — NVIDIA Cosmos product page describing Cosmos 3 as unified WFMconf 85%
    Notes: HIT — confirms world-model thesis; foundational training infrastructure for embodied agents.
  3. 2026-04-15hitNVIDIA Isaac GR00T N1.6 ships with Cosmos Reason for full-body humanoid control
    How: NVIDIA releases Isaac GR00T N1.6 open-reasoning vision-language-action model purpose-built for humanoids, leveraging Cosmos Reason
    Source: https://developer.nvidia.com/isaac/gr00tconf 95%
  4. 2026-10-13pendingQ1 window check-in (25%)
  5. 2027-07-25pendingQ2 window check-in (50%)
  6. 2027-01-01 → 2029-02-14pendingFirst commercial humanoid deployment whose pre-training was 100% in simulation
    How: Public announcement (Figure / 1X / Apptronik / Sanctuary) of a humanoid deployed in commercial workforce role whose policy was trained entirely in WFM simulation with zero real-world bootstrap fine-tuning
    Source: Humanoids Daily / company press / NVIDIA partner releasesconf 45%
    Notes: This is the prediction's named milestone. Sim-to-real zero-shot transfer remains the open frontier.
  7. 2028-05-05pendingQ3 window check-in (75%)
  8. 2027-06-01 → 2029-12-31pending≥10,000 cumulative humanoid hours of WFM-trained operation in commercial settings
    How: Public reporting (NVIDIA partner releases or industry trackers) shows aggregate ≥10,000 commercial-deployment hours from WFM-trained humanoid policies
    Source: NVIDIA + Humanoids Daily reportingconf 40%
    Notes: Cascade — validates the 'billions of hours of simulated trial-and-error' thesis with real-world hours.

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
LBP2026-05-24T02:00:02Z44.4%+1.2pp
Network propagation: 43.2% → 44.4%
4-iter LBP, residual 0.01000 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 806b02f8
LBP2026-05-17T02:00:01Z43.2%+2.4pp
Network propagation: 40.8% → 43.2%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
LBP2026-05-10T02:00:02Z40.8%+4.7pp
Network propagation: 36.1% → 40.8%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z36.1%+8.4pp
Network propagation: 27.7% → 36.1%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
legacy v12026-04-30T16:13:50Z27.7%+0.0pp
reference_class_assigned bayesian_v2 inside=0.800 blend=0.277 w_in=0.35 humanoid_commercial_volume
legacy v12026-04-30T01:56:50Z27.7%-52.3pp
reference_class_assigned bayesian_v2 inside=0.800 blend=0.277 w_in=0.35 humanoid_commercial_volume

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.

Prerequisites (1)

Predictions that must hit first
TypePredTitleDomainLag
correlateS_AGI_MID_2029AGI mid: Kurzweil 2029 pathagi_general_capability

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Expected milestones (1)

From Sheet 17 Monitoring Triggers
Expected byDescriptionStatus
2030-12-31[Robotics 2030-12] [CYB_019] Genie 4+ releases; NVIDIA Cosmos adoption [230_022] Shanghai factory commitment announcement [CMQ_050] Annual humanoid unit shipments; BMW / Mercedes / Figure deployment ramp; Tesla Optimus productiopending

Validations (1)

Resolution events
Observed atStatusByNotes
2026-04-29partialthesis_timeline_v1.0_importDeepMind Genie 2 / Genie 3 world models; NVIDIA Cosmos, Tesla FSD sim; Figure Helix training. Billion-hour simulation scales documented.

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "mode": "FORECAST",
  "role": "Cited-CEO",
  "context": "Distinct from AI_005 (jagged intelligence), AI_031 (100 years of biology). Specific robotics-training framing. Couples with INF_025 (Figure universal brain), 229_042 (Figure omni-model).",
  "to_year": 2030,
  "conv_cues": "CEO FIRST_PERSON; specific technical framing",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "2026-2030",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "1X Technologies trains NEO Gamma humanoid using Cosmos Predict + Transfer",
      "notes": "HIT — first concrete instance of WFM-trained humanoid going to production.",
      "source": "https://nvidianews.nvidia.com/news/nvidia-and-global-robotics-leaders-take-physical-ai-to-the-real-world",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://nvidianews.nvidia.com/news/nvidia-and-global-robotics-leaders-take-physical-ai-to-the-real-world",
      "expected_date": "2026-04-01",
      "observed_date": "2026-03-18",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-06-30",
        "from": "2026-01-01"
      },
      "measurement_criterion": "1X publicly confirms Cosmos Predict + Cosmos Transfer used to train NEO Gamma humanoid, per NVIDIA partner announcement"
    },
    {
      "kind": "llm_pre_event",
      "label": "NVIDIA announces Cosmos 3 unifying world generation + vision reasoning + action sim",
      "notes": "HIT — confirms world-model thesis; foundational training infrastructure for embodied agents.",
      "source": "https://www.nvidia.com/en-us/ai/cosmos/ — NVIDIA Cosmos product page describing Cosmos 3 as unified WFM",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://www.nvidia.com/en-us/ai/cosmos/",
      "expected_date": "2026-04-15",
      "observed_date": "2026-04-15",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-05-31",
        "from": "2026-03-01"
      },
      "measurement_criterion": "NVIDIA publishes Cosmos 3 release notes describing the first world foundation model unifying synthetic world generation, vision reasoning, and action simulation"
    },
    {
      "kind": "llm_pre_event",
      "label": "NVIDIA Isaac GR00T N1.6 ships with Cosmos Reason for full-body humanoid control",
      "source": "https://developer.nvidia.com/isaac/gr00t",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://developer.nvidia.com/isaac/gr00t",
      "expected_date": "2026-04-30",
      "observed_date": "2026-04-15",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-06-30",
        "from": "2026-03-01"
      },
      "measurement_criterion": "NVIDIA releases Isaac GR00T N1.6 open-reasoning vision-language-action model purpose-built for humanoids, leveraging Cosmos Reason"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -5,
      "source_id": null,
      "expected_date": "2026-10-13",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2027-07-25",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "First commercial humanoid deployment whose pre-training was 100% in simulation",
      "notes": "This is the prediction's named milestone. Sim-to-real zero-shot transfer remains the open frontier.",
      "source": "Humanoids Daily / company press / NVIDIA partner releases",
      "status
... (truncated)