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232_014predictionAIAI-timing

Recursive self-improvement is already here, not 12 months away.

Predictor: Alex Wissner-Gross · ep#232 "Ben Horowitz: xAI Executive Exodus, Apple's AI Crisis, The Pace of AI | EP #232" · source

Prior probability
92.0%
Current probability
70.2%
evolves via intake + LBP
Conviction
5/5
Signal quality
B
Resolution
hit
Window
2026-01-01 – 2026-11-30
Edges in / out
11 / 16
Tickers exposed
33

Prediction text

Recursive self-improvement is already here, not 12 months away. | I I think we've already hit the era of recursive self-improvement. I'm banging the the table rhetorically every episode and and every day in my newsletter talking about recursive self-improvement. We're there. All of the Frontier Labs are are using their own models at this point to develop their models. That's practically the definition of recursive self-improvement at at this point in practice. I I don't think it's the next 12 months. I I think it's it's now. | Ongoing monthly capability delta measurements

Key catalyst: Ongoing monthly capability delta measurements

Verbatim quote

From episode "Ben Horowitz: xAI Executive Exodus, Apple's AI Crisis, The Pace of AI | EP #232"
I I think we've already hit the era of recursive self-improvement. I'm banging the the table rhetorically every episode and and every day in my newsletter talking about recursive self-improvement. We're there. All of the Frontier Labs are are using their own models at this point to develop their models. That's practically the definition of recursive self-improvement at at this point in practice. I I don't think it's the next 12 months. I I think it's it's now.

Resolution evidence

Status: hit

Recursive self-improvement: all frontier labs confirm models help train next-gen. Anthropic's SWE-bench leaderboard has Claude 4.x agents ranking above human interns on AI R&D. Recursive loop validated.

Predictor: Alex Wissner-Gross

κ + Brier as of 2026-05-22
κ (discount)
0.844
Brier
0.0341
excellent
Hits / Misses
6 / 1
of 11 resolved
Hit rate
54.5%
Calibration plot (stated vs observed)

Evidence about this node from Alex Wissner-Gross 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 0.584

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 70.2% → blend 70.2% 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 92%2026-04-292026-04-302026-05-03
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 70.2%

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 overdue ⏱
  1. 2026-01-30overdueQ1 window check-in (25%)
  2. 2026-03-01overdueQ2 window check-in (50%)
  3. 2026-03-30overdueQ3 window check-in (75%)

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: 70%)

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
LBP2026-05-03T02:00:01Z70.2%+1.2pp
Network propagation: 69.0% → 70.2%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z69.0%+3.5pp
Network propagation: 65.6% → 69.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
legacy v12026-04-30T16:13:50Z65.6%-7.3pp
reference_class_assigned bayesian_v2 inside=0.920 blend=0.656 w_in=0.53 agi_breakthrough_5y
LBP2026-04-30T02:18:57Z72.9%+7.4pp
Network propagation: 65.5% → 72.9%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef
legacy v12026-04-30T01:56:50Z65.5%-26.5pp
reference_class_assigned bayesian_v2 inside=0.920 blend=0.655 w_in=0.53 agi_breakthrough_5y
resolution_terminal2026-04-29T22:23:17Z100.0%+31.0pp
resolution_terminal hit outcome=1.0 pre_resolution=0.690
Raw metadata
{
  "source": "backfill_resolution_history.py",
  "status": "hit",
  "bayesian_v2": false,
  "outcome_prob": 1,
  "evidence_kind": "resolution_terminal",
  "posterior_prob": 1,
  "delta_to_outcome": 0.30955999999999995,
  "inside_posterior": 0.69044,
  "validation_notes": "Recursive self-improvement: all frontier labs confirm models help train next-gen. Anthropic's SWE-bench leaderboard has Claude 4.x agents ranking above human interns on AI R&D. Recursive loop validated.",
  "validation_status": "hit",
  "pre_resolution_prob": 0.69044,
  "resolution_evidence": "Recursive self-improvement: all frontier labs confirm models help train next-gen. Anthropic's SWE-bench leaderboard has Claude 4.x agents ranking above human interns on AI R&D. Recursive loop validated.",
  "does_not_update_current_prob": true
}

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%0.0500.920+0.131
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.920+0.087
killerTK14
Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
20.0%0.0500.920+0.044
prereq238_009
Recursive self-improvement is already happening now (no longAlex Wissner-Gross
78.1%0.9200.050+0.020
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.9200.050-0.018

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq232_055
We're exiting the industrial age permanently as recursive sePeter Diamandis
35.5%0.7000.050+0.152
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050+0.150
prereqSEM_034
True artificial general intelligence will be achieved betweeDemis Hassabis
28.7%0.5500.050+0.115
prereq239_008
Moon base will exist in 10 yearsElon Musk
28.8%0.5500.050+0.114
prereq241_043
ASI will arrive within 2 years to 5 years to this next decadPeter Diamandis
35.9%0.6500.050+0.113

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (11)

Predictions that must hit first
TypePredTitleDomainLag
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereq238_009Recursive self-improvement is already happening now (no longer three years out)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 (16)

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
prereq242_001Elon's Terafab will build 1 terawatt of AI compute per year, 50x current global productionAI
prereq238_052$100 trillion companies within 5 years (3 years from now, per Diamandis interpretation of Musk)Markets/Stocks
prereq239_008Moon base will exist in 10 yearsSpace
prereqCMQ_002By 2028, AI systems will reach 'independent researcher' level — driving autonomous scientific discoveries without human intervention.AI
prereq239_009People will be on Mars within 10 yearsSpace
prereq241_057Elon Musk believes robot building robot is imminentRobotics
prereq232_047Mass drivers on the moon will shoot AI satellites into deep space; self-sustaining lunar city will follow.Space
prereqSEM_034True artificial general intelligence will be achieved between 2032 and 2042 — 'first we solve AI, then use AI to solve everything else'.AI/AGI
prereq237_023Baby AGI agents will need and develop an 'immune system' for prompt injection and cybersecurity threats in real time.AI
prereq239_010Mass driver on the moon within 10 yearsSpace
prereq233_021AI learning will improve via closed-loop reinforcement learning cycle making results keep increasing.AI
prereq230_022Elon plans to produce tens of millions of robots per year in just a few years.Robotics

Validations (1)

Resolution events
Observed atStatusByNotes
2026-04-29hitthesis_timeline_v1.0_importRecursive self-improvement: all frontier labs confirm models help train next-gen. Anthropic's SWE-bench leaderboard has Claude 4.x agents ranking above human interns on AI R&D. Recursive loop validated.

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.626arxivThree-Stage Learning Unlocks Strong Performance in Simple Models for Long-Term Time Series Forecastingmentionspending2026-05-13
0.623manifoldWhen will Manifest 2026 have 10+ session videos available online?mentionspending2026-06-03
0.623manifoldWill the Experience Machines substack post 2+ times a month for the rest of the year?82%mentionspending2026-05-02
0.618manifoldI go through the scaling book this week?32%mentionspending2026-05-04
0.608github_releasefacebookresearch/projectaria_tools 1.3.0mentionspending2023-12-19
0.595manifoldWhen will I reach 100 followers on this account?mentionspending2026-05-25
0.594github_releasefacebookresearch/projectaria_tools 1.3.3mentionspending2024-02-16
0.593manifoldWill "Not a Paper: "Frontier Lab CEOs are Capable o..." make the top fifty posts in LessWrong's 2026 Annual Review?12%mentionspending2026-04-29
0.589github_releasefacebookresearch/spdl v0.1.7mentionspending2025-12-08
0.585github_releasefacebookresearch/spdl v0.1.3mentionspending2025-09-01

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=C1GLT9_tag0",
  "mode": "THESIS",
  "role": "Host",
  "context": "I I think we've already hit the era of recursive self-improvement. I'm banging the the table rhetorically every episode and and every day in my newsletter talking about recursive self-improvement. We're there. All of the Frontier Labs are are using their own models at this point to develop their models. That's practically the definition of recursive self-improvement at at this point in practice. I I don't think it's the next 12 months. I I think it's it's now.",
  "to_year": 2026,
  "verbatim": "I I think we've already hit the era of recursive self-improvement. I'm banging the the table rhetorically every episode and and every day in my newsletter talking about recursive self-improvement. We're there. All of the Frontier Labs are are using their own models at this point to develop their models. That's practically the definition of recursive self-improvement at at this point in practice. I I don't think it's the next 12 months. I I think it's it's now.",
  "conv_cues": "already hit; banging the table; We're there",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "now",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2026-01-30",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2026-03-01",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -1,
      "source_id": null,
      "expected_date": "2026-03-30",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "event",
      "label": "Recursive self-improvement is already here, not 12 months away.",
      "status": "hit",
      "weight": 1,
      "ordinal": 0,
      "source_id": "232_014",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "cascade",
      "label": "Math is cooked (will be solved), physics cooked, biology char broiled.",
      "status": "pending",
      "weight": 0.5,
      "ordinal": 1,
      "source_id": "231_013",
      "expected_date": "2027-06-26",
      "observed_date": null
    },
    {
      "kind": "cascade",
      "label": "We're exiting the industrial age permanently as recursive self-improvement unfolds.",
      "status": "pending",
      "weight": 0.5,
      "ordinal": 2,
      "source_id": "232_055",
      "expected_date": "2028-06-25",
      "observed_date": null
    },
    {
      "kind": "cascade",
      "label": "By 2028, AI systems will reach 'independent researcher' level — driving autonomous scientific discoveries without human intervention.",
      "status": "pending",
      "weight": 0.5,
      "ordinal": 3,
      "source_id": "CMQ_002",
      "expected_date": "2028-09-07",
      "observed_date": null
    },
    {
      "kind": "cascade",
      "label": "Elon plans to produce tens of millions of robots per year in just a few years.",
      "status": "pending",
      "weight": 0.5,
      "ordinal": 4,
      "source_id": "230_022",
      "expected_date": "2029-12-10",
      "observed_date": null
    },
    {
      "kind": "cascade",
      "label": "Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 20
... (truncated)