S_AGI_WINTER_2036PLUSscenarioagi_general_capability
AGI delayed: capability plateau or AI winter
Prior probability
10.0%
Current probability
10.0%
evolves via intake + LBP
Conviction
—
Signal quality
—
Resolution
pending
Window
2026-04-30 – 2036-12-31
Edges in / out
0 / 66
Tickers exposed
0
Prediction text
AGI does not occur within 5-year horizon. Reasons could include compute scaling diminishing returns, alignment / regulatory constraints, capability winter 2027-2030. Resolution: Dec 2036 (out-of-horizon, flagged for review).
Predictor calibration
Not assigned
This node has no predictor assigned. Default κ=0.5 applies to any intake evidence about it.
Reference class
Not linked
This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.
Probability over time
0 prob_history rows
No probability history yet.
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.
No milestone chain derived yet. Run scripts/ops/derive_milestones.py to populate from prereq edges + window checkpoints.
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: 10%)
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
No probability history yet. The first evidence will arrive via /api/intake or the daily milestone sweep / weekly LBP run.
Network propagation neighbors
Top edges sorted by latest LBP cross-impact
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 (0)
Predictions that must hit first
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| No prerequisites | ||||
Dependents (66)
Predictions enabled by this
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| correlate | 234_012 | Anthropic revenue will cross OpenAI revenue in middle of 2026 | Markets/Stocks | — |
| correlate | 248_040 | Pausing AI will fail and only accelerate race dynamics. | AI | — |
| correlate | 232_014 | Recursive self-improvement is already here, not 12 months away. | AI | — |
| correlate | 232_021 | No chance AI will be paused in the next three years given current administration and China competition. | Geopolitics | — |
| correlate | 238_010 | AI takeoff/inflection is happening now | AI | — |
| correlate | 229_013 | The next 12-18 months will be the largest AI transformation ever seen. | AI | — |
| correlate | INF_016 | Power generation is the 'innermost loop' and absolute limiting factor on AI expansion; any AI capability scaling ultimately routes through the speed at which new generation can be brought online. | Energy | — |
| correlate | SPC_025 | Critical misalignment in the AI industry: approximately 300 AI capabilities researchers for every one AGI safety researcher — extreme systemic risk as these autonomous systems are deployed into physical domains like space and embodied robotics. | AI | — |
| correlate | CYB_012 | 'Recommendation poisoning' — deliberate corruption of the data lakes, training sets, and persistent memory banks that agents rely on for purchase/action decisions — emerges as the primary new cybersecurity-marketing vector, blurring the line between di... | AI | — |
| correlate | AUT_021 | Defining software movement of 2026: startups building autonomous platforms specifically designed to clean/structure/continuously validate multimodal data — unstructured corporate sludge (PDFs, logs, videos, emails) causes autonomous agentic workflows t... | AI | — |
| correlate | SEM_002 | By 2025-2026, AI model outputs will outpace the cognitive capabilities of college graduates (driven by hundreds of millions of GPUs). | AI | — |
| correlate | SPC_027 | A 'trillion-dollar agent economy' driven by hyper-deflation of intelligence — AI intelligence becoming 100x cheaper every two years; in aerospace this enables mission planning, orbital trajectory calculation, and CAD modeling to be executed autonomousl... | AI | — |
| correlate | AUT_002 | Models excelling at highly structured mathematical benchmarks exhibit a 'unified capability substrate' enabling dominance in seemingly unrelated fields (coding, logical reasoning, scientific discovery) — the 'mathematical skeleton' of the technological... | AI | — |
| correlate | 231_050 | New economy built with AI agents will work around old economy rather than through it. | Macro/Economy | — |
| correlate | SEM_023 | No AI bubble — semiconductor positive trend will remain robust through 2026 with 'crystal clear' growth visibility into 2027. | Semis/Markets | — |
| correlate | AUT_001 | The HIM platform has demonstrated commercial viability of autonomous multi-agent corporate execution — 5-agent organizational structures running continuously from a single node, with product applications generating substantial revenue within minutes of... | AI | — |
| correlate | 238_013 | Frontier labs will increasingly keep their most capable models secret to self-advance | AI | — |
| correlate | CYB_011 | Consumer commerce shifts from 'search and click' to 'ask and buy' — persistent AI agents with hyper-personalized memory navigate budgetary limits, ethical brand preferences, dietary restrictions, and logistical requirements with absolute precision, sev... | Consumer | — |
| correlate | INF_001 | Reaching AGI by 2027 will require deployment of hundreds of millions of AI GPUs — forcing total mobilization of US industrial capacity for semiconductor fab and data-center shell construction. | AI | — |
| correlate | 248_016 | ASI is imminent; access to top AI models will be closed down in a couple of years. | AI | — |
| correlate | 237_026 | The cadence of AI breakthroughs and Moonshot episodes will keep picking up as we are in the singularity. | AI | — |
| correlate | 235_007 | AI regulation window is this calendar year 2026 before chaos breaks out. | Geopolitics | — |
| correlate | CMQ_004 | AGI-like models matching or outperforming human experts across most professional domains could arrive as early as 2026-2027. | AI | — |
| correlate | 239_003 | We are currently in AI hard takeoff | AI | — |
| correlate | 235_005 | AI capability will grow 100x this year in raw parameter count as lower bound. | AI | — |
| correlate | 246_006 | OpenAI will IPO by end of 2026, Anthropic early-to-mid 2027 (may try end of 2026). | Markets/Stocks | — |
| correlate | 248_013 | Model transparency decline will not reverse; US labs will keep going internal. | AI | — |
| correlate | 241_038 | Chinese AI strategy is edge computing focused vs US AGI/ASI centered | AI | — |
| correlate | 241_037 | Chinese AI strategy will stay open source / open weights | AI | — |
| correlate | 235_001 | Anthropic will be first company to hit $1 trillion in revenue by 2029-2030. | AI | — |
| correlate | 247_010 | Anthropic will beat OpenAI in valuation trajectory | AI | — |
| correlate | 232_009 | Startups will continue to deploy dangerous AI tech even after hyperscalers voluntarily pause it. | AI | — |
| correlate | 235_046 | Window of global AI regulation is a few months before capabilities proliferate widely. | Geopolitics | — |
| correlate | 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 | — |
| correlate | FUT_002 | Mean expert estimate for AGI collapsed from 50-year horizon to ~5 years over a 4-year window leading to mid-2020s — placing expected AGI arrival firmly in 2029-2031 window per Metaculus + 80000 Hours aggregate tracking; quantitative forecasters now ali... | AI | — |
| correlate | CMQ_013 | A 5-OOM (100,000x) effective-compute leap will occur between 2024-2027 — bridging GPT-4 high-schooler to fully automated AI researcher. | AI | — |
| correlate | 239_032 | Progress in AI will continue as series of overlapping S-curves | AI | — |
| correlate | INF_072 | There is approximately a 50/50 chance that simply scaling existing methodologies (transformer architecture + more data + more compute) will be enough to reach AGI — though "nowhere near" human-level AGI currently. | AI | — |
| correlate | CMQ_022 | AGI will arrive within a decade (by 2030) — driven primarily by massive raw compute deployment and neural-network scaling. | AI | — |
| correlate | CMQ_012 | AGI by 2027; superintelligence by 2030 — full automation of AI researchers in 2027 triggers post-AGI intelligence explosion. | AI | — |
| correlate | 229_026 | By next year (2027), Figure expects to show real general purpose capability inside the robot; possibly within months. | Robotics | — |
| correlate | 239_002 | AI recursive self-improvement will be fully automated by end of 2026 or 2027 at latest | AI | — |
| correlate | 229_044 | Positive transfer learning will continue to emerge, meaning more diverse data makes Figure robots broadly better at many tasks. | AI | — |
| correlate | 234_050 | Open-source maintainers will be overwhelmed by AI-discovered software vulnerabilities | AI | — |
| correlate | 238_022 | From here forward, training data will be synthetic (pre-training era of human internet data is over) | AI | — |
| correlate | 238_026 | Every attempt to pause frontier AI capabilities ends up being a net accelerant | AI | — |
| correlate | 247_057 | Parameter scaling race is over; frontier labs plateauing at 10T parameters | AI | — |
| correlate | IND_004 | True AGI remains approximately a decade away (circa 2034) — AGI will NOT manifest as sudden uncontrollable explosion; will smoothly 'blend into the previous ~2.5 centuries of 2% GDP growth'. Labor markets will adapt through traditional economic absorpt... | AI | — |
| correlate | CMQ_011 | AGI is plausible within 10 years, BUT alignment and safety must be solved BEFORE reaching AGI — not concurrently, and not after. | AI | — |
| correlate | INF_071 | Artificial General Intelligence will be achieved by 2029; humans will begin to merge with AI; computational intelligence will multiply a thousandfold, triggering a technological singularity where growth becomes uncontrollable and irreversible. | AI | — |
| correlate | 233_021 | AI learning will improve via closed-loop reinforcement learning cycle making results keep increasing. | AI | — |
| correlate | 242_047 | Frontier AI may solve most diseases in 5 years | Biotech/Longevity | — |
| correlate | AI_006 | True autonomous agents are 'not anywhere close' — AGI and reliable long-horizon agents will require a full decade (2034 or beyond) to develop the holistic contextual reasoning and robust world models needed for unconstrained physical and digital enviro... | AI | — |
| correlate | AUT_012 | True AGI arrives 2030-2035 (5-10 years from 2026) based on advanced 'world model systems' — current LLM architecture insufficient for generalized autonomy due to lack of temporal consistency and deep reasoning; world models inherently understand/simula... | AI | — |
| correlate | CMQ_007 | Anthropic corporate revenue will reach trillions of dollars before 2030. | AI | — |
| correlate | CMQ_018 | By 2027-2028, the strategic value of superintelligence + impossible trillion-dollar infrastructure cost will trigger government consolidation of AGI development — 'The Project'. | Geopolitics | — |
| correlate | 237_019 | Code generation models are pushing development in the direction of TypeScript instead of Rust for memory safety. | AI | — |
| correlate | IND_007 | Massive 'Corporate Collapse' 2026 as legacy businesses fail to integrate GPT-5 level capabilities — specifically predicting a 1.1 million job loss event tied to this transition. AI intelligence growth by end-2026 comparable to evolutionary leap 'from a... | Labor/Jobs | — |
| correlate | 248_010 | AI capabilities will advance 100x in 2026 (by summer, potentially more). | AI | — |
| correlate | AI_002 | Models matching the collective cognitive capacity of 'a country of geniuses in a datacenter' — acting simultaneously across all domains — could arrive as early as 2026 or 2027. | AI | — |
| correlate | CMQ_003 | By 2030, AI models will surpass peak human expert levels across virtually all cognitive domains — onset of true superintelligence. | AI | — |
| correlate | AI_001 | AI will surpass peak human intelligence across ALL economically valuable domains by 2030, extending the sequential maturation roadmap beyond 'independent researcher' (2028) into full-domain superintelligence. | AI | — |
| correlate | CMQ_016 | Post-AGI (2027+), a decade of human-led algorithmic progress will be compressed into ~1 year or less as AGIs automate AI research. | AI | — |
| correlate | AI_008 | Once 2027 AGI arrives (AI researchers capable of autonomous research), the intelligence explosion begins — compressing roughly a decade of human-led algorithmic progress into a single year and culminating in Superintelligence by 2030. | AI | — |
| correlate | ROB_001 | If hundreds of millions of AGI instances are deployed simultaneously by 2027 to automate the algorithms governing their own architectures, the industry will compress a decade of human-led algorithmic progress into less than a year — culminating in 'run... | AI | — |
| correlate | IND_022 | AGI arrives before 2029 (Turing test); true Singularity (ASI) occurs in 2040s — total human-machine convergence enabling: mental transfer from brain to brain, integration of nanobots into human bloodstream for perfect biological health maintenance, ach... | Biotech/Longevity | — |
Linked documents (10)
Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
Raw metadata
From Thesis_Timeline_v1.0_FINAL workbook
{
"fork_key": "agi",
"dimension": "agi_general_capability",
"family_type": "mutually_exclusive",
"family_label": "AGI",
"family_order": 4,
"beyond_horizon": true,
"predictor_profile": [
"AI safety community",
"skeptics"
],
"exclusive_within_dimension": true
}