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234_019predictionAIAI-scaling

Expect big AI capability improvements via recursive self-improvement over next few weeks

Predictor: Alex Wissner-Gross · ep#234 "Anthropic vs. The Pentagon, Claude Outpaces ChatGPT, and Consulting Gets Replaced" · source

Prior probability
50.0%
Current probability
39.4%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2026-01-01 – 2026-11-30
Edges in / out
11 / 5
Tickers exposed
37

Prediction text

Expect big AI capability improvements via recursive self-improvement over next few weeks | So expect big things over the next few weeks. We're capability jumps in weeks not quarters.

Verbatim quote

From episode "Anthropic vs. The Pentagon, Claude Outpaces ChatGPT, and Consulting Gets Replaced"
So expect big things over the next few weeks. We're capability jumps in weeks not quarters.

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 0.621

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 39.4% → blend 39.4% 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

9 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-05-022026-05-24
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 39.4%

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: 4 fired ✓ · 5 overdue ⏱ · 1 pending
  1. 2026-02-15overdueOpenAI's GPT-5.5 trained at Stargate Abilene with internal AI assistance
    How: OpenAI publicly confirms GPT-5.5 was trained at the flagship Stargate Abilene site with significant AI-assisted training/debugging contributions, citing recursive self-improvement loop language
    Source: https://openai.com/index/building-the-compute-infrastructure-for-the-intelligence-age/ — OpenAI infrastructure announcementconf 85%
  2. 2026-02-28overdueAnthropic publicly states most code now written by AI
    How: Anthropic executive (CEO/CTO) publicly confirms majority of internal code generation is AI-driven, indicating recursive feedback loop in production
    Source: https://eu.36kr.com/en/p/3680937611062920 — Silicon Valley Article on AI Singularityconf 80%
  3. 2026-02-01 → 2026-03-31overdueMajor frontier model release cluster (Feb-Mar 2026)
    How: Google, Anthropic, OpenAI, xAI, and Alibaba all release significant model updates within 60-day window with measurable benchmark improvements >5pp on capability suites
    Source: https://blog.mean.ceo/new-ai-model-releases-news-april-2026/ — AI model release roundupconf 92%
  4. 2026-03-05overdueGPT-5.4 sets new computer-use benchmark record
    How: OpenAI releases GPT-5.4 with publicly reported benchmark improvement >5pp on at least one major capability benchmark (OSWorld, SWE-Bench, MMLU)
    Source: https://kersai.com/ai-breakthroughs-in-2026-march-update/ — March 2026 AI breakthroughsconf 90%
  5. 2026-04-15overdueRecursive Superintelligence startup funding signal
    How: Self-improving AI startup raises >=$500M funding round within 6 months of founding, validating market belief in recursive self-improvement
    Source: https://the-decoder.com/self-improving-ai-startup-recursive-superintelligence-pulls-in-500-million-just-four-months-after-founding/ — The Decoderconf 90%
  6. 2026-08-01 → 2026-12-31pendingCascade: AI capability gains compress to <60-day cycles
    How: Major frontier-model release cadence drops below 60 days between SOTA-setting releases from any single lab, indicating accelerating self-improvement loop
    Source: Pattern extrapolation from observed Dec 2025 to Feb 2026 OpenAI cadenceconf 55%

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: 39%)

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
LBP2026-05-24T02:00:02Z39.4%+2.0pp
Network propagation: 37.4% → 39.4%
4-iter LBP, residual 0.01000 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 806b02f8
LBP2026-05-17T02:00:01Z37.4%+3.9pp
Network propagation: 33.5% → 37.4%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
LBP2026-05-10T02:00:02Z33.5%+7.3pp
Network propagation: 26.2% → 33.5%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z26.2%+11.1pp
Network propagation: 15.1% → 26.2%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
metadata_milestone_miss_sweep2026-05-02T22:07:21Z15.1%-22.6pp
metadata_milestone_miss_sweep bayesian_v2 n=5 inside=0.120 blend=0.151 LLR=-1.495 κ=0.84 w_in=0.56 agi_breakthrough_5y
Raw metadata
{
  "trf": 0.6338685427014515,
  "kappa": 0.8438,
  "base_rate": 0.2,
  "predictor": "Alex Wissner-Gross",
  "total_llr": -2.027325540540822,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": -0.4998786328260134,
  "bayes_factor": "4.5:1 against",
  "blend_reason": "blend 55% inside / 44% outside (TRF=0.634, base_rate=0.200 from agi_breakthrough_5y)",
  "inside_prior": 0.37756919095844854,
  "kappa_source": "predictor_table",
  "n_milestones": 5,
  "blend_applied": true,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.7172299999999999,
      "label": "OpenAI's GPT-5.5 trained at Stargate Abilene with internal AI assistance",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.85,
      "source_url": "https://openai.com/index/building-the-compute-infrastructure-for-the-intelligence-age/",
      "adjusted_llr": -0.2908117394884187,
      "expected_date": "2026-02-15",
      "measurement_criterion": "OpenAI publicly confirms GPT-5.5 was trained at the flagship Stargate Abilene site with significant AI-assisted training/debugging contributions, citing recursive self-improvement loop language"
    },
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.6750400000000001,
      "label": "Anthropic publicly states most code now written by AI",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.8,
      "source_url": "https://eu.36kr.com/en/p/3680937611062920",
      "adjusted_llr": -0.27370516657733535,
      "expected_date": "2026-02-28",
      "measurement_criterion": "Anthropic executive (CEO/CTO) publicly confirms majority of internal code generation is AI-driven, indicating recursive feedback loop in production"
    },
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.776296,
      "label": "Major frontier model release cluster (Feb-Mar 2026)",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.92,
      "source_url": "https://blog.mean.ceo/new-ai-model-releases-news-april-2026/",
      "adjusted_llr": -0.3147609415639356,
      "expected_date": "2026-03-02",
      "measurement_criterion": "Google, Anthropic, OpenAI, xAI, and Alibaba all release significant model updates within 60-day window with measurable benchmark improvements >5pp on capability suites"
    },
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.75942,
      "label": "GPT-5.4 sets new computer-use benchmark record",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.9,
      "source_url": "https://kersai.com/ai-breakthroughs-in-2026-march-update/",
      "adjusted_llr": -0.3079183123995022,
      "expected_date": "2026-03-05",
      "measurement_criterion": "OpenAI releases GPT-5.4 with publicly reported benchmark improvement >5pp on at least one major capability benchmark (OSWorld, SWE-Bench, MMLU)"
    },
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.75942,
      "label": "Recursive Superintelligence startup funding signal",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.9,
      "source_url": "https://the-decoder.com/self-improving-ai-startup-recursive-superintelligence-pulls-in-500-million-just-four-months-after-founding/",
      "adjusted_llr": -0.3079183123995022,
      "expected_date": "2026-04-15",
      "measurement_criterion": "Self-improving AI startup raises >=$500M funding round within 6 months of founding, validating market belief in recursive self-improvement"
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.5562920201089838,
  "outside_weight": 0.4437079798910162,
  "posterior_prob": 0.15123998288627608,
  "posterior_logit": -1.9949931052547074,
  "predictor_brier": 0.03413,
  "inside_posterior": 0.11972961695514925,
  "blended_posterior": 0.15123998288627608,
  "reference_class_id": "agi_breakthrough_5y",
  "total_adjusted_llr": -1.495114472428694,
  "predictor_n_resolved": 11
}
LBP2026-04-30T16:39:51Z37.8%+3.5pp
Network propagation: 34.3% → 37.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
legacy v12026-04-30T16:13:50Z34.3%-4.0pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.343 w_in=0.53 agi_breakthrough_5y
LBP2026-04-30T02:18:57Z38.3%+4.1pp
Network propagation: 34.2% → 38.3%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef
legacy v12026-04-30T01:56:50Z34.2%-15.8pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.342 w_in=0.53 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%0.0500.500+0.061
killerTK09
Energy Grid Cap (Data Center Power Wall)
35.0%0.0500.500-0.052
killerTK02
AI Compute Supply Shock (TSMC/Taiwan Disruption)
12.0%0.0500.500+0.052
prereqSEM_015
Nvidia agreed to remit 15% of China chip-sale revenue directJensen Huang
66.3%0.5000.050-0.042
prereqSEM_027
Nvidia Data Center revenue +66% YoY, contributing ~90% of $5Joseph Moore
68.3%0.5000.050-0.042

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq247_023
AI will be able to do everything a white collar worker does Dave Blundin
40.8%0.7200.050-0.086
prereq244_019
Peter's son won't need a driver's license in 2 yearsPeter Diamandis
48.4%0.9200.050-0.081
prereq242_031
Most large companies' business models will be disrupted in 2Peter Diamandis
36.1%0.6500.050-0.068
prereq230_020
Peter's 14-year-old son Milan will never get a driver's licePeter Diamandis
34.7%0.6500.050-0.054
prereq232_055
We're exiting the industrial age permanently as recursive sePeter Diamandis
35.5%0.7000.050-0.041

Ticker exposure

37 ticker(s) linked

Beneficiaries (24)

MUWULFIRENEQIXALABAPLDASMIYASMLPLABNVDANBISCRWVAAPLAMTAMZNDELLGOOGLIRMLNVGYMETAMSFTORCLSFTBYSTX

Adverse (6)

ACNGENCHGGIBMWNSLRN

Prerequisites (11)

Predictions that must hit first
TypePredTitleDomainLag
prereqSEM_011Nvidia became the world's first $5 trillion company (late 2025), operating a near-monopoly on advanced AI chips.Capital Markets
prereqSEM_027Nvidia Data Center revenue +66% YoY, contributing ~90% of $57B fiscal Q3 revenue; >$4.5T market cap entirely underpinned by AI silicon.Capital Markets
prereqSEM_014Nvidia's Arizona-based TSMC factory successfully fabricated cutting-edge semiconductors on US soil for first time in decades (October 2025).Manufacturing
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
prereqSEM_015Nvidia agreed to remit 15% of China chip-sale revenue directly to US government in exchange for reversing specific AI chip export bans.Policy/Semis
correlateS_ASI_SLOW_2040PLUSASI slow: post-2040 / soft takeoffasi_recursive_self_improvement
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 (5)

Predictions enabled by this
TypePredTitleDomainLag
prereq244_019Peter's son won't need a driver's license in 2 yearsAuto/Transport
prereq247_023AI will be able to do everything a white collar worker does imminentlyAI
prereq232_055We're exiting the industrial age permanently as recursive self-improvement unfolds.AI
prereq242_031Most large companies' business models will be disrupted in 2-5 yearsMarkets/Stocks
prereq230_020Peter's 14-year-old son Milan will never get a driver's license.Auto/Transport

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.758manifoldWill AI continue to improve?84%mentionspending2026-06-01
0.726manifoldIs ai going to be self repairing?10%mentionspending2026-05-25
0.635arxivThree-Stage Learning Unlocks Strong Performance in Simple Models for Long-Term Time Series Forecastingmentionspending2026-05-13
0.630manifoldI go through the scaling book this week?32%mentionspending2026-05-04
0.621manifoldWhat goals will I achieve this week?mentionspending2026-05-10
0.607manifoldWhich of these will I achieve?mentionspending2026-04-24
0.591manifoldWhat goals will I achieve this week?mentionspending2026-05-18
0.591manifoldWhat goals will I achieve this week?mentionspending2026-05-25
0.591manifoldWhat goals will I achieve this week?mentionspending2026-06-01
0.589manifoldWill I speak to a human in the next week?72%mentionspending2026-05-04

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "orders of magnitude improvement in capability density by parameter",
  "url": "https://www.youtube.com/watch?v=dmtvGKuRE64",
  "mode": "PREDICTION",
  "role": "Host",
  "context": "we're starting even over the past week or two, we're getting into the era when you can get smarter, better, faster models by asking a previous model just emit the weights, the parameters directly for a successor model and you can get orders of magnitude improvement in terms of capability density by by parameter. So expect big things over the next few weeks.",
  "to_year": 2026,
  "verbatim": "So expect big things over the next few weeks. We're capability jumps in weeks not quarters.",
  "conv_cues": "expect big things",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "Next few weeks (March-April 2026)",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "OpenAI's GPT-5.5 trained at Stargate Abilene with internal AI assistance",
      "source": "https://openai.com/index/building-the-compute-infrastructure-for-the-intelligence-age/ — OpenAI infrastructure announcement",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -10,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://openai.com/index/building-the-compute-infrastructure-for-the-intelligence-age/",
      "expected_date": "2026-02-15",
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep",
      "research_origin": "deep_research",
      "measurement_criterion": "OpenAI publicly confirms GPT-5.5 was trained at the flagship Stargate Abilene site with significant AI-assisted training/debugging contributions, citing recursive self-improvement loop language"
    },
    {
      "kind": "llm_pre_event",
      "label": "Anthropic publicly states most code now written by AI",
      "source": "https://eu.36kr.com/en/p/3680937611062920 — Silicon Valley Article on AI Singularity",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -9,
      "source_id": null,
      "confidence": 0.8,
      "source_url": "https://eu.36kr.com/en/p/3680937611062920",
      "expected_date": "2026-02-28",
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep",
      "research_origin": "deep_research",
      "measurement_criterion": "Anthropic executive (CEO/CTO) publicly confirms majority of internal code generation is AI-driven, indicating recursive feedback loop in production"
    },
    {
      "kind": "llm_pre_event",
      "label": "Major frontier model release cluster (Feb-Mar 2026)",
      "source": "https://blog.mean.ceo/new-ai-model-releases-news-april-2026/ — AI model release roundup",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.92,
      "source_url": "https://blog.mean.ceo/new-ai-model-releases-news-april-2026/",
      "expected_date": "2026-03-02",
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-03-31",
        "from": "2026-02-01"
      },
      "measurement_criterion": "Google, Anthropic, OpenAI, xAI, and Alibaba all release significant model updates within 60-day window with measurable benchmark improvements >5pp on capability suites"
    },
    {
      "kind": "llm_pre_event",
      "label": "GPT-5.4 sets new computer-use benchmark record",
      "source": "https://kersai.com/ai-breakthroughs-in-2026-march-update/ — March 2026 AI breakthroughs",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.9,
      "source_url": "https://kersai.com/ai-breakthroughs-in-2026-march-update/",
      "expected_date": "2026-03-05",
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:
... (truncated)