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230_029predictionAIAI-timing

Cognition is becoming a commodity — intelligence will flow like oil.

Predictor: Alex Wissner-Gross · ep#230 "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230" · source

Prior probability
50.0%
Current probability
43.5%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2026-01-01 – 2030-09-30
Edges in / out
7 / 5
Tickers exposed
33

Prediction text

Cognition is becoming a commodity — intelligence will flow like oil. | Right. So the thesis of the thesis is that a cognition is becoming a commodity like intelligence is just going to flow like oil does and we've made the point on the pod in the past that GP this is a bit of a cliche but admittedly GPUs are are the new oil so a cognition is becoming a commodity

Verbatim quote

From episode "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230"
Right. So the thesis of the thesis is that a cognition is becoming a commodity like intelligence is just going to flow like oil does and we've made the point on the pod in the past that GP this is a bit of a cliche but admittedly GPUs are are the new oil so a cognition is becoming a commodity

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

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

3 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-04-302026-05-03
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 43.5%

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: 6 fired ✓ · 3 pending
  1. 2026-01-31hitGPT-4-class inference cost falls 1000x to ~$0.40 per million tokens by early 2026
    How: Public benchmark inference cost for GPT-4-class capability tier reaches ~$0.40 per million tokens, vs ~$20/M tokens in late 2022
    Source: https://www.gpunex.com/blog/ai-inference-economics-2026/ — 1,000x cost collapse in three yearsconf 95%
    Notes: HIT — directly supports 'cognition becoming a commodity'. 1000x decline in 3y is utility-scale price collapse.
  2. 2026-03-31hitH100 cloud GPU pricing falls 64-75% from Q4 2024 to Q1 2026
    How: On-demand H100 SXM hourly rate at Lambda/RunPod/Jarvislabs reaches $2.99/hour or below, down from $8-10/hour Q4 2024
    Source: https://www.silicondata.com/blog/gpu-pricing-trends-2026-what-to-expect-in-the-year-aheadconf 95%
    Notes: HIT — GPU 'oil' commoditizing on supply side.
  3. 2026-01-01 → 2026-12-31pendingInference workload share of total AI compute crosses 66%
    How: Industry analysts (NVIDIA, hyperscaler reports) confirm inference accounts for ~2/3 of AI compute demand, up from ~1/3 in 2023
    Source: https://blogs.nvidia.com/blog/lowest-token-cost-ai-factories/conf 85%
    Notes: Inference utility usage replaces training as dominant compute mode — flow-like-oil signature.
  4. 2027-01-01 → 2028-12-31pendingNVIDIA inference market share falls below 50% as TPU/ASIC capture growing share
    How: Industry analysts report NVIDIA inference share below 50%, down from 90%+, as Google TPUs and specialized ASICs gain production share
    Source: https://www.gpunex.com/blog/ai-inference-economics-2026/ — projected NVIDIA fall to 20-30% by 2028conf 55%
    Notes: Multi-vendor commoditization is the canonical 'flow like oil' signal — multiple producers, fungible product.
  5. 2027-06-01 → 2029-12-31pendingSub-cent per million tokens inference price tier emerges for distilled models
    How: At least one production-grade distilled LLM achieves <$0.01 per million tokens inference cost on commodity infrastructure
    Source: Inference economics trajectory extrapolated from 2022-2026 1000x declineconf 50%
    Notes: Cascade — at sub-cent pricing, cognition truly becomes utility-priced like electricity.
  6. 2036-09-06pendingMoon base will exist in 10 years

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: 43%)

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
LBP2026-05-03T02:00:01Z43.5%-1.4pp
Network propagation: 44.8% → 43.5%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z44.8%-2.0pp
Network propagation: 46.8% → 44.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z46.8%-3.2pp
Network propagation: 50.0% → 46.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

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
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.5000.050-0.057
prereqSEM_012
Nvidia quadrupled chip production output while only doublingJensen Huang
75.0%0.5000.050-0.050
prereqSEM_008
Training runs costing $10 billion for a single model will coDario Amodei
76.9%0.5000.050-0.042
prereq238_009
Recursive self-improvement is already happening now (no longAlex Wissner-Gross
78.1%0.5000.050-0.037
killerTK14
Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
20.0%0.0500.500-0.025

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq246_016
Dragonfly nuclear-powered octicopter arrives at Titan in 203Peter Diamandis
35.6%0.6500.050-0.051
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050-0.045
prereq240_036
TEPCO's restarted reactor will support 20% of Japan's electrPeter Diamandis
34.3%0.6500.050-0.038
prereq239_008
Moon base will exist in 10 yearsElon Musk
28.8%0.5500.050-0.025
prereqSEM_034
True artificial general intelligence will be achieved betweeDemis Hassabis
28.7%0.5500.050-0.024

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (7)

Predictions that must hit first
TypePredTitleDomainLag
prereq238_009Recursive self-improvement is already happening now (no longer three years out)AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.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
killerTK14Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (5)

Predictions enabled by this
TypePredTitleDomainLag
prereq235_030Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 2033.Biotech/Longevity
prereq246_016Dragonfly nuclear-powered octicopter arrives at Titan in 2034.Space
prereq240_036TEPCO's restarted reactor will support 20% of Japan's electric needs by 2040Energy
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
prereq239_008Moon base will exist in 10 yearsSpace

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=6P0uTDGDr-I",
  "mode": "THESIS",
  "role": "Host",
  "context": "cognition is becoming a commodity like intelligence is just going to flow like oil does... GPUs are are the new oil so a cognition is becoming a commodity",
  "to_year": 2030,
  "verbatim": "Right. So the thesis of the thesis is that a cognition is becoming a commodity like intelligence is just going to flow like oil does and we've made the point on the pod in the past that GP this is a bit of a cliche but admittedly GPUs are are the new oil so a cognition is becoming a commodity",
  "conv_cues": "thesis",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "becoming / ongoing",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "GPT-4-class inference cost falls 1000x to ~$0.40 per million tokens by early 2026",
      "notes": "HIT — directly supports 'cognition becoming a commodity'. 1000x decline in 3y is utility-scale price collapse.",
      "source": "https://www.gpunex.com/blog/ai-inference-economics-2026/ — 1,000x cost collapse in three years",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -9,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://www.gpunex.com/blog/ai-inference-economics-2026/",
      "expected_date": "2026-01-31",
      "observed_date": "2026-01-31",
      "research_origin": "deep_research",
      "measurement_criterion": "Public benchmark inference cost for GPT-4-class capability tier reaches ~$0.40 per million tokens, vs ~$20/M tokens in late 2022"
    },
    {
      "kind": "llm_pre_event",
      "label": "H100 cloud GPU pricing falls 64-75% from Q4 2024 to Q1 2026",
      "notes": "HIT — GPU 'oil' commoditizing on supply side.",
      "source": "https://www.silicondata.com/blog/gpu-pricing-trends-2026-what-to-expect-in-the-year-ahead",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://www.silicondata.com/blog/gpu-pricing-trends-2026-what-to-expect-in-the-year-ahead",
      "expected_date": "2026-03-31",
      "observed_date": "2026-03-31",
      "research_origin": "deep_research",
      "measurement_criterion": "On-demand H100 SXM hourly rate at Lambda/RunPod/Jarvislabs reaches $2.99/hour or below, down from $8-10/hour Q4 2024"
    },
    {
      "kind": "prereq",
      "label": "Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) a",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -7,
      "source_id": "SEM_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Training runs costing $10 billion for a single model will commence sometime in 2025.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "SEM_008",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "2025 will be the definitive year that agentic systems finally hit the mainstream.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -5,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Recursive self-improvement is already happening now (no longer three years out)",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -4,
      "source_id": "238_009",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "Inference workload share of total AI compute crosses 66%",
      "notes": "Inference utility usage replaces training as dominant compute mode — flow-like-oil signature.",
      "source": "https://blogs.nvidia.com/blog/lowest-token-cost-ai-factories/",
 
... (truncated)