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ROB_005predictionRoboticsphysical-intelligence-AGI-prerequisite

True AGI requires 'physical intelligence' — an AGI system must be able to control a robotic chassis to play sports or perform complex physical manipulations at amazing levels to truly mirror human brain architecture; software alone cannot achieve full ...

Predictor: Demis Hassabis

Prior probability
55.0%
Current probability
47.4%
evolves via intake + LBP
Conviction
4/5
Signal quality
A
Resolution
pending
Window
2027-01-01 – 2036-10-31
Edges in / out
4 / 0
Tickers exposed
0

Prediction text

True AGI requires 'physical intelligence' — an AGI system must be able to control a robotic chassis to play sports or perform complex physical manipulations at amazing levels to truly mirror human brain architecture; software alone cannot achieve full general intelligence without embodied interactions. | First published AGI-benchmark definition including embodiment

Key catalyst: First published AGI-benchmark definition including embodiment

Watch events: DeepMind Gemini Robotics next release; humanoid-robot dexterity benchmarks

Resolution evidence

Status: pending

DeepMind Gemini Robotics / DeepMind GNoME / Figure Helix all embody this thesis; jury out on whether physical integration is strictly necessary for AGI.

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: agi_breakthrough_5y

Linked via embedding similarity 0.558

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 47.4% → blend 47.4% 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

7 prob_history rows
0%25%50%75%100%prior 55%2026-04-302026-04-302026-05-17
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 47.4%

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: 10 pending
  1. 2026-06-30 → 2028-12-31pendingVision-language-action (VLA) foundation model demonstrates zero-shot transfer across >=1000 manipulation tasks
    How: Published benchmark (RoboArena, ManiSkill, Open X-Embodiment) showing single VLA model handling >=1000 distinct manipulation tasks at >=80% success without per-task finetuning
    Source: Helix (Figure), GR00T (NVIDIA), Pi0 (Physical Intelligence)conf 60%
  2. 2028-09-13pendingQ1 window check-in (25%)
  3. 2027-01-01 → 2030-06-30pendingFrontier AI lab publicly states physical embodiment is required for AGI claims
    How: OpenAI, Anthropic, Google DeepMind, or peer publishes formal position paper or AGI definition that requires demonstrated physical-world capability (manipulation/sport/lab work) as gating criterion
    Source: Industry debate Hassabis vs. Altman embodiment requirementconf 40%
  4. 2029-03-31pendingScenario fires: AGI mid: Kurzweil 2029 path
  5. 2030-05-27pendingQ2 window check-in (50%)
  6. 2028-01-01 → 2032-12-31pendingHumanoid robot achieves Olympic-level performance on at least one athletic discipline (sub-3-min mile, gymnastics floor routine, etc.)
    How: Verifiable third-party demonstration (broadcast, peer review) of Optimus/Figure/Unitree successor completing an athletic event at performance equivalent to 90th-percentile human Olympic athlete
    Source: Unitree H2/G1 sport demos; Figure 03 Helixconf 35%
  7. 2028-06-30 → 2032-12-31pendingTesla Optimus or Figure deploys >=1M units globally
    How: Verified by SEC filings or production data: aggregate humanoid robot deployment exceeds 1M operational units across consumer/industrial markets
    Source: Tesla Gen-2 Gigafactory Texas 10M/yr target 2027conf 45%
  8. 2030-01-01 → 2033-12-31pendingAGI definition revised in major AI lab roadmaps to include embodiment requirement
    How: At least 2 of OpenAI/Anthropic/DeepMind/xAI roadmap updates explicitly add physical-world capability tests (lab automation, household autonomy, sports) as part of AGI evaluation suite
    Source: Industry trend toward embodied evaluationconf 45%
  9. 2032-02-07pendingQ3 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: 47%)

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
LBP2026-05-17T02:00:01Z47.4%+1.4pp
Network propagation: 46.0% → 47.4%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
LBP2026-05-10T02:00:02Z46.0%+2.8pp
Network propagation: 43.2% → 46.0%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z43.2%+5.3pp
Network propagation: 37.9% → 43.2%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z37.9%+9.2pp
Network propagation: 28.7% → 37.9%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
legacy v12026-04-30T16:13:50Z28.7%-9.2pp
reference_class_assigned bayesian_v2 inside=0.550 blend=0.287 w_in=0.30 agi_breakthrough_5y
LBP2026-04-30T02:18:57Z37.9%+9.2pp
Network propagation: 28.7% → 37.9%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef
legacy v12026-04-30T01:56:50Z28.7%-26.3pp
reference_class_assigned bayesian_v2 inside=0.550 blend=0.287 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
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.550+0.026
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.550+0.001

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Prerequisites (4)

Predictions that must hit first
TypePredTitleDomainLag
correlateS_HUMANOID_ENTERPRISE_2028Humanoid R2: 100K+ enterprise by Nov 2028humanoid_deployment
correlateS_AGI_MID_2029AGI mid: Kurzweil 2029 pathagi_general_capability
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
SimSourceTitleMarket probPolarityReviewedPublished
0.550codex_research_packMETR - Measuring AI Ability to Complete Long Tasksmentionspending2025-03-19
0.550codex_research_packOECD - Exploring Possible AI Trajectories Through 2030mentionspending2026-04-26

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "mode": "FORECAST",
  "role": "Cited-CEO",
  "context": "Hassabis bridge thesis: digital AGI cannot stand alone; embodiment is prerequisite. Couples with ROB_006 (Huang $50T Physical AI), ROB_009 (Musk 10B robots).",
  "to_year": 2036,
  "conv_cues": "CEO FIRST_PERSON; AGI-definition framing",
  "direction": "HAPPEN",
  "from_year": 2027,
  "timeframe": "2027-2036",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Vision-language-action (VLA) foundation model demonstrates zero-shot transfer across >=1000 manipulation tasks",
      "source": "Helix (Figure), GR00T (NVIDIA), Pi0 (Physical Intelligence)",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -10,
      "source_id": null,
      "confidence": 0.6,
      "expected_date": "2027-09-30",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2026-06-30"
      },
      "measurement_criterion": "Published benchmark (RoboArena, ManiSkill, Open X-Embodiment) showing single VLA model handling >=1000 distinct manipulation tasks at >=80% success without per-task finetuning"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -9,
      "source_id": null,
      "expected_date": "2028-09-13",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Frontier AI lab publicly states physical embodiment is required for AGI claims",
      "source": "Industry debate Hassabis vs. Altman embodiment requirement",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.4,
      "expected_date": "2028-09-30",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2030-06-30",
        "from": "2027-01-01"
      },
      "measurement_criterion": "OpenAI, Anthropic, Google DeepMind, or peer publishes formal position paper or AGI definition that requires demonstrated physical-world capability (manipulation/sport/lab work) as gating criterion"
    },
    {
      "kind": "scenario_signal",
      "label": "Scenario fires: Humanoid R2: 100K+ enterprise by Nov 2028",
      "status": "pending",
      "weight": 0.5,
      "ordinal": -7,
      "source_id": "S_HUMANOID_ENTERPRISE_2028",
      "expected_date": "2028-11-30",
      "observed_date": null
    },
    {
      "kind": "scenario_signal",
      "label": "Scenario fires: AGI mid: Kurzweil 2029 path",
      "status": "pending",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "S_AGI_MID_2029",
      "expected_date": "2029-03-31",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -5,
      "source_id": null,
      "expected_date": "2030-05-27",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Humanoid robot achieves Olympic-level performance on at least one athletic discipline (sub-3-min mile, gymnastics floor routine, etc.)",
      "source": "Unitree H2/G1 sport demos; Figure 03 Helix",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.35,
      "expected_date": "2030-07-02",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2032-12-31",
        "from": "2028-01-01"
      },
      "measurement_criterion": "Verifiable third-party demonstration (broadcast, peer review) of Optimus/Figure/Unitree successor completing an athletic event at performance equivalent to 90th-percentile human Olympic athlete"
    },
    {
      "kind": "llm_pre_event",
      "label": "Tesla Optimus or Figure deploys >=1M units globally",
      "source": "Tesla Gen-2 Gigafactory Texas 10M/yr target 2027",
      "status": "pending",
      "we
... (truncated)