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245_002predictionAIAI-timing

Every company should or will be an AI company

Predictor: Ben Lamm · ep#245 "AI + Synthetic Biology: The Most Transformative Technology in Human History | Ben Lamm (Colossal)" · source

Prior probability
45.0%
Current probability
35.1%
evolves via intake + LBP
Conviction
3/5
Signal quality
C
Resolution
pending
Window
2026-04-30 – 2029-03-31
Edges in / out
4 / 0
Tickers exposed
33

Prediction text

Every company should or will be an AI company | I think every company is should be an AI company or is an AI company.

Verbatim quote

From episode "AI + Synthetic Biology: The Most Transformative Technology in Human History | Ben Lamm (Colossal)"
I think every company is should be an AI company or is an AI company.

Predictor: Ben Lamm

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0043
excellent
Hits / Misses
2 / 0
of 3 resolved
Hit rate
66.7%
Calibration plot (stated vs observed)

Evidence about this node from Ben Lamm 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

4 prob_history rows
0%25%50%75%100%prior 45%2026-04-302026-05-032026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 35.1%

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: 2 fired ✓ · 6 pending
  1. 2026-04-15hitDeloitte 2026 enterprise AI report: 64% of orgs actively using AI in operations
    How: Deloitte/PwC/McKinsey global enterprise AI report shows >=60% of surveyed orgs actively using AI in operations (vs <30% in 2023)
    Source: https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.htmlconf 90%
  2. 2026-04-30hitAI revenue impact: 88% of enterprise respondents report AI-driven revenue uplift
    How: Major enterprise survey (Deloitte/NVIDIA/PwC) confirms >=80% of respondents report measurable AI revenue impact, with >=25% reporting >10% revenue increase
    Source: https://blogs.nvidia.com/blog/state-of-ai-report-2026/conf 85%
  3. 2026-10-24pendingQ1 window check-in (25%)
  4. 2027-04-20pendingQ2 window check-in (50%)
  5. 2027-01-01 → 2027-12-31pendingEnterprise AI 'reimagine' threshold: >=50% of Fortune 500 publish AI-first strategy
    How: By count of public 10-K/annual report filings or CEO letters, >=50% of Fortune 500 companies explicitly position the firm as 'AI-first' or 'AI-native' with a CAIO/Chief AI Officer in C-suite
    Source: https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.htmlconf 60%
  6. 2027-10-15pendingQ3 window check-in (75%)
  7. 2027-06-01 → 2028-03-31pendingS&P 500 IT spend on AI tooling exceeds 25% of total IT budget
    How: Gartner / IDC surveys of S&P 500 CIOs show median AI/ML line-items >=25% of total IT spending (up from ~10% in 2025)
    Source: https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.htmlconf 55%
  8. 2027-06-01 → 2028-12-31pendingCascade: AI-native startups capture >=20% of new B2B SaaS market share
    How: CB Insights / Crunchbase: >=20% of net-new B2B SaaS revenue (annualized) attributed to AI-native firms founded post-2023, displacing incumbent SaaS
    Source: https://writer.com/blog/enterprise-ai-adoption-2026/conf 50%
  9. 2027-12-01 → 2028-09-30pendingCascade: BLS labor data shows >=10% headcount reduction in 'traditional knowledge work' categories
    How: US Bureau of Labor Statistics employment data shows >=10% YoY decline in selected white-collar OEUS occupational categories (paralegals, junior accountants, customer service reps) attributable to AI substitution
    Source: https://news.sap.com/2026/04/five-make-or-break-moments-2026-ai-ambitions/conf 45%

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: 35%)

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
LBP2026-05-10T02:00:02Z35.1%-1.8pp
Network propagation: 36.9% → 35.1%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z36.9%-3.7pp
Network propagation: 40.6% → 36.9%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z40.6%-1.5pp
Network propagation: 42.1% → 40.6%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z42.1%-2.9pp
Network propagation: 45.0% → 42.1%
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
prereqS_AGI_MID_2029
AGI mid: Kurzweil 2029 path
35.0%0.4500.050-0.161
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.450+0.059
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.450+0.039
killerTK14
Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
20.0%0.0500.450+0.019

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (4)

Predictions that must hit first
TypePredTitleDomainLag
prereqS_AGI_MID_2029AGI mid: Kurzweil 2029 pathagi_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 (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Linked documents (2)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.519edgar_8kDuolingo, Inc. (DUOL) (CIK 0001562088)mentionspending2026-05-04
0.519edgar_8kDuolingo, Inc. (DUOL) (CIK 0001562088)mentionspending2026-06-05

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=Goa6c6Qz__I",
  "mode": "THESIS",
  "role": "Guest-CEO",
  "context": "We I think every company is should be an AI company or is an AI company. Uh so we feel like the synthetic biology part of our work is really interesting.",
  "verbatim": "I think every company is should be an AI company or is an AI company.",
  "conv_cues": "should be; is",
  "direction": "HAPPEN",
  "timeframe": "Present/near future",
  "conv_level": "MEDIUM",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Deloitte 2026 enterprise AI report: 64% of orgs actively using AI in operations",
      "source": "https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.9,
      "expected_date": "2026-04-15",
      "observed_date": "2026-04-15",
      "research_origin": "deep_research",
      "measurement_criterion": "Deloitte/PwC/McKinsey global enterprise AI report shows >=60% of surveyed orgs actively using AI in operations (vs <30% in 2023)"
    },
    {
      "kind": "llm_pre_event",
      "label": "AI revenue impact: 88% of enterprise respondents report AI-driven revenue uplift",
      "source": "https://blogs.nvidia.com/blog/state-of-ai-report-2026/",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.85,
      "expected_date": "2026-04-30",
      "observed_date": "2026-04-30",
      "research_origin": "deep_research",
      "measurement_criterion": "Major enterprise survey (Deloitte/NVIDIA/PwC) confirms >=80% of respondents report measurable AI revenue impact, with >=25% reporting >10% revenue increase"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -6,
      "source_id": null,
      "expected_date": "2026-10-24",
      "observed_date": null
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -5,
      "source_id": null,
      "expected_date": "2027-04-20",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Enterprise AI 'reimagine' threshold: >=50% of Fortune 500 publish AI-first strategy",
      "source": "https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.6,
      "expected_date": "2027-07-02",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2027-12-31",
        "from": "2027-01-01"
      },
      "measurement_criterion": "By count of public 10-K/annual report filings or CEO letters, >=50% of Fortune 500 companies explicitly position the firm as 'AI-first' or 'AI-native' with a CAIO/Chief AI Officer in C-suite"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2027-10-15",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "S&P 500 IT spend on AI tooling exceeds 25% of total IT budget",
      "source": "https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2027-10-31",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2028-03-31",
        "from": "2027-06-01"
      },
      "measurement_criterion": "Gartner / IDC surveys of S&P 500 CIOs show median AI/ML l
... (truncated)