AI recursive self-improvement will be fully automated by end of 2026 or 2027 at latest
Predictor: Elon Musk · ep#239 "Elon Musk: The Economy Will Be 10x the Size in 10 Years | #239" · source
Prediction text
AI recursive self-improvement will be fully automated by end of 2026 or 2027 at latest | every successive model uh is is built by the one before it. So that that that is happening to a large degree, but it's it's not yet fully automated. Um it may be there end of this year, but not later than next year.
Verbatim quote
every successive model uh is is built by the one before it. So that that that is happening to a large degree, but it's it's not yet fully automated. Um it may be there end of this year, but not later than next year.
Predictor: Elon Musk
Calibration plot (stated vs observed)
Evidence about this node from Elon Musk 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
Major capability discontinuity (e.g. AGI by named target year, 5-year horizon)
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
Milestone chain
- 2026-04-20overdueQ1 window check-in (25%)
- 2026-04-27hitICLR 2026 Workshop on AI with Recursive Self-Improvement convened in Rio (community legitimization)How: ICLR 2026 workshop proceedings confirm RSI workshop took place; first dedicated academic venue for RSISource: deep_research_enrichedconf 95%
- 2026-08-07pendingQ2 window check-in (50%)
- 2026-04-01 → 2027-04-30pendingAlphaEvolve-class system autonomously discovers novel SOTA algorithm in published paperHow: Peer-reviewed publication or DeepMind blog confirming an AI system autonomously generated and validated an algorithm that exceeds prior human SOTA on a recognized benchmarkSource: deep_research_enrichedconf 55%
- 2026-08-01 → 2026-12-31pendingOpenAI ships intern-level AI research agent (publicly demonstrated or deployed)How: OpenAI announces or demos intern-level AI research agent capable of running independent ML experiments end-to-end — explicit company target by Sep 2026Source: deep_research_enrichedconf 55%
- 2026-11-24pendingQ3 window check-in (75%)
- 2026-09-01 → 2027-09-30pendingFrontier lab "effective workforce" disclosure shows >10x ratio of AI agents to human researchersHow: OpenAI / Anthropic / DeepMind public statement or 10-K equivalent disclosing AI-agent research workforce >10x human staffSource: deep_research_enrichedconf 35%
- 2027-01-01 → 2027-10-31pendingAnthropic / OpenAI public claim of "fully automated AI research" pipelineHow: Anthropic or OpenAI publishes claim that end-to-end AI research (idea → experiment → paper → deployed model) runs without human-in-the-loop, matching prediction's "fully automated" thresholdSource: deep_research_enrichedconf 30%
What if this resolves?
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
Raw metadata
{
"trf": 0.8174823723347057,
"kappa": 0.6429,
"base_rate": 0.2,
"predictor": "Elon Musk",
"total_llr": -0.4054651081081644,
"grace_days": 7,
"bayesian_v2": true,
"prior_logit": -0.527677440995565,
"bayes_factor": "1.3:1 against",
"blend_reason": "blend 42% inside / 57% outside (TRF=0.817, base_rate=0.200 from agi_breakthrough_5y)",
"inside_prior": 0.3710587507587537,
"kappa_source": "predictor_table",
"n_milestones": 1,
"blend_applied": true,
"contributions": [
{
"llr": -0.4054651081081644,
"kind": "quartile_checkpoint",
"kappa": 0.6429,
"label": "Q1 window check-in (25%)",
"weight": 0.05,
"strength": "weak",
"confidence": null,
"source_url": null,
"adjusted_llr": -0.2606735180027389,
"expected_date": "2026-04-20",
"measurement_criterion": null
}
],
"evidence_kind": "metadata_milestone_miss_sweep",
"inside_source": "history_v2",
"inside_weight": 0.427762339365706,
"outside_weight": 0.572237660634294,
"posterior_prob": 0.24406575971772326,
"posterior_logit": -0.788350958998304,
"predictor_brier": 0.01,
"inside_posterior": 0.312522860124513,
"blended_posterior": 0.24406575971772326,
"reference_class_id": "agi_breakthrough_5y",
"total_adjusted_llr": -0.2606735180027389,
"predictor_n_resolved": 2
}Network propagation neighbors
Top incoming (parents)
Edges that influence THIS node's belief
| Kind | Node | Their prob | P(c|s=T) | P(c|s=F) | Δ implied |
|---|---|---|---|---|---|
| prereq | 238_009 Recursive self-improvement is already happening now (no long — Alex Wissner-Gross | 78.1% | 0.500 | 0.050 | -0.039 |
| killer | TK03 AI Regulatory Moratorium (EU/US Capability Freeze) | 10.0% | 0.050 | 0.500 | +0.019 |
| killer | TK01 AGI Capability Plateau (2026-27 Training Stall) | 15.0% | 0.050 | 0.500 | -0.004 |
Top outgoing (children)
Predictions THIS node influences
| Kind | Node | Their prob | P(c|s=T) | P(c|s=F) | Δ implied |
|---|---|---|---|---|---|
| prereq | 239_001 Global economy will be 10x its current size in 10 years — Elon Musk | 37.7% | 0.600 | 0.050 | -0.083 |
| prereq | CMQ_003 By 2030, AI models will surpass peak human expert levels acr — Sam Altman | 22.8% | 0.350 | 0.050 | -0.045 |
| prereq | 241_043 ASI will arrive within 2 years to 5 years to this next decad — Peter Diamandis | 35.9% | 0.650 | 0.050 | -0.042 |
| prereq | 235_030 Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203 — Ray Kurzweil | 39.2% | 0.750 | 0.050 | -0.032 |
| prereq | SEM_034 True artificial general intelligence will be achieved betwee — Demis Hassabis | 28.7% | 0.550 | 0.050 | -0.015 |
Ticker exposure
Beneficiaries (14)
Adverse (7)
Prerequisites (7)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| prereq | 238_009 | Recursive self-improvement is already happening now (no longer three years out) | AI | — |
| correlate | S_ASI_SLOW_2040PLUS | ASI slow: post-2040 / soft takeoff | asi_recursive_self_improvement | — |
| correlate | S_AGI_MID_2029 | AGI mid: Kurzweil 2029 path | agi_general_capability | — |
| correlate | S_AI_PAUSE_2027 | AI pause beginning 2027 | ai_regulatory_pause | — |
| correlate | S_AGI_WINTER_2036PLUS | AGI delayed: capability plateau or AI winter | agi_general_capability | — |
| killer | TK01 | AGI Capability Plateau (2026-27 Training Stall) | — | — |
| killer | TK03 | AI Regulatory Moratorium (EU/US Capability Freeze) | — | — |
Dependents (5)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| prereq | 235_030 | Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 2033. | Biotech/Longevity | — |
| prereq | 241_043 | ASI will arrive within 2 years to 5 years to this next decade | AI | — |
| prereq | 239_001 | Global economy will be 10x its current size in 10 years | Macro/Economy | — |
| prereq | SEM_034 | True artificial general intelligence will be achieved between 2032 and 2042 — 'first we solve AI, then use AI to solve everything else'. | AI/AGI | — |
| prereq | CMQ_003 | By 2030, AI models will surpass peak human expert levels across virtually all cognitive domains — onset of true superintelligence. | AI | — |
Linked documents (10)
Raw metadata
{
"nia": false,
"url": "https://www.youtube.com/watch?v=N5KCm_55xeQ",
"mode": "PREDICTION",
"role": "Guest-CEO",
"context": "humans are gradually getting less and less in the loop on the recursive self-improvement... It may be there end of this year, but not later than next year.",
"to_year": 2027,
"verbatim": "every successive model uh is is built by the one before it. So that that that is happening to a large degree, but it's it's not yet fully automated. Um it may be there end of this year, but not later than next year.",
"conv_cues": "may be; not later than",
"direction": "HAPPEN",
"from_year": 2026,
"timeframe": "end of 2026 to 2027",
"conv_level": "MEDIUM",
"milestones": [
{
"kind": "quartile_checkpoint",
"label": "Q1 window check-in (25%)",
"status": "overdue",
"weight": 0.05,
"ordinal": -7,
"source_id": null,
"expected_date": "2026-04-20",
"observed_date": null,
"miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
"miss_emitted_by": "metadata_milestone_sweep"
},
{
"kind": "llm_pre_event",
"label": "ICLR 2026 Workshop on AI with Recursive Self-Improvement convened in Rio (community legitimization)",
"source": "deep_research_enriched",
"status": "hit",
"weight": 0.4,
"ordinal": -6,
"source_id": null,
"confidence": 0.95,
"source_url": "https://iclr.cc/virtual/2026/workshop/10000796",
"expected_date": "2026-04-27",
"observed_date": "2026-04-27",
"research_origin": "deep_research",
"measurement_criterion": "ICLR 2026 workshop proceedings confirm RSI workshop took place; first dedicated academic venue for RSI"
},
{
"kind": "prereq",
"label": "Recursive self-improvement is already happening now (no longer three years out)",
"status": "hit",
"weight": 0.5,
"ordinal": -5,
"source_id": "238_009",
"expected_date": "2026-04-29",
"observed_date": "2026-04-29"
},
{
"kind": "quartile_checkpoint",
"label": "Q2 window check-in (50%)",
"status": "pending",
"weight": 0.05,
"ordinal": -4,
"source_id": null,
"expected_date": "2026-08-07",
"observed_date": null
},
{
"kind": "llm_pre_event",
"label": "AlphaEvolve-class system autonomously discovers novel SOTA algorithm in published paper",
"source": "deep_research_enriched",
"status": "pending",
"weight": 0.4,
"ordinal": -3,
"source_id": null,
"confidence": 0.55,
"source_url": "https://itcanthink.substack.com/p/how-close-are-we-to-self-improving",
"expected_date": "2026-10-15",
"research_origin": "deep_research",
"expected_date_range": {
"to": "2027-04-30",
"from": "2026-04-01"
},
"measurement_criterion": "Peer-reviewed publication or DeepMind blog confirming an AI system autonomously generated and validated an algorithm that exceeds prior human SOTA on a recognized benchmark"
},
{
"kind": "llm_pre_event",
"label": "OpenAI ships intern-level AI research agent (publicly demonstrated or deployed)",
"source": "deep_research_enriched",
"status": "pending",
"weight": 0.4,
"ordinal": -2,
"source_id": null,
"confidence": 0.55,
"source_url": "https://www.hyperdimensional.co/p/on-recursive-self-improvement-part",
"expected_date": "2026-10-16",
"research_origin": "deep_research",
"expected_date_range": {
"to": "2026-12-31",
"from": "2026-08-01"
},
"measurement_criterion": "OpenAI announces or demos intern-level AI research agent capable of running independent ML experiments end-to-end — explicit company target by Sep 2026"
},
{
"kind": "quartile_checkpoint",
"label": "Q3 window check-in (75%)",
"status": "pending",
"weight": 0.05,
"ordinal": -1,
"source_id": nul
... (truncated)