← Cockpit
248_007predictionAIAI-timing

We will see an explosion of AI-driven pop-up shops, retail venues, and malls orchestrated by AI.

Predictor: Alex Wissner-Gross · ep#248 "Sam Altman's Attack, Amazon vs. Starlink, and What Opus 4.7 Actually Means | #248" · source

Prior probability
45.0%
Current probability
36.6%
evolves via intake + LBP
Conviction
3/5
Signal quality
C
Resolution
pending
Window
2027-06-01 – 2027-06-30
Edges in / out
8 / 5
Tickers exposed
33

Prediction text

We will see an explosion of AI-driven pop-up shops, retail venues, and malls orchestrated by AI. | I I think we're going to see more and more pop-up shops, retail venues, maybe even malls in the short term or medium term that are run, orchestrated, managed by AIS on behalf of humans. This is like a preview of the future.

Verbatim quote

From episode "Sam Altman's Attack, Amazon vs. Starlink, and What Opus 4.7 Actually Means | #248"
I I think we're going to see more and more pop-up shops, retail venues, maybe even malls in the short term or medium term that are run, orchestrated, managed by AIS on behalf of humans. This is like a preview of the future.

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 45%2026-04-302026-04-302026-05-02
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 36.6%

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: 5 fired ✓ · 1 overdue ⏱ · 3 pending
  1. 2025-11-01 → 2026-06-30overdueFirst AI-orchestrated pop-up retail launch by major brand
    How: Public announcement or press coverage of a brand using AI agents end-to-end (location, inventory, staffing, pricing) for a temporary retail venue.
    Source: deep_research_enrichedconf 45%
  2. 2026-01-01 → 2026-12-31pendingRetail-AI venture funding round >$50M
    How: Series B+ funding for an AI-retail orchestration startup (Crunchbase / PitchBook) above $50M.
    Source: deep_research_enrichedconf 55%
  3. 2026-06-01 → 2027-03-31pendingAI-orchestrated mall or multi-tenant venue announced
    How: REIT or developer announces a mall pilot using AI agents to manage tenant mix, dynamic leases, or pop-up rotation.
    Source: deep_research_enrichedconf 35%
  4. 2027-01-01 → 2027-06-30pendingCoverage cluster: 5+ articles on AI pop-up retail explosion
    How: WSJ/Bloomberg/Reuters/FT/CNBC tier publish 5+ stories in a 90-day window framing AI-orchestrated retail as a category trend.
    Source: deep_research_enrichedconf 40%
  5. 2027-06-16pendingCategory data validates explosion (active venues count)
    How: Industry tracker (Coresight, ICSC, or trade press tally) reports >100 AI-orchestrated pop-ups/venues active in US within trailing 12 months.
    Source: deep_research_enrichedconf 35%

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: 37%)

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
metadata_milestone_miss_sweep2026-05-02T22:07:21Z36.6%-3.6pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.366 blend=0.366 LLR=-0.154 κ=0.84 no_blend
Raw metadata
{
  "trf": 1,
  "kappa": 0.8438,
  "base_rate": null,
  "predictor": "Alex Wissner-Gross",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": -0.39366560199387524,
  "bayes_factor": "1.2:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.4028351939614072,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.37971,
      "label": "First AI-orchestrated pop-up retail launch by major brand",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.45,
      "source_url": null,
      "adjusted_llr": -0.1539591561997511,
      "expected_date": "2026-03-01",
      "measurement_criterion": "Public announcement or press coverage of a brand using AI agents end-to-end (location, inventory, staffing, pricing) for a temporary retail venue."
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.3,
  "outside_weight": 0.7,
  "posterior_prob": 0.3664156586142059,
  "posterior_logit": -0.5476247581936263,
  "predictor_brier": 0.03413,
  "inside_posterior": 0.3664156586142059,
  "blended_posterior": 0.3664156586142059,
  "reference_class_id": null,
  "total_adjusted_llr": -0.1539591561997511,
  "predictor_n_resolved": 11
}
LBP2026-04-30T16:39:51Z40.3%-1.9pp
Network propagation: 42.2% → 40.3%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z42.2%-2.8pp
Network propagation: 45.0% → 42.2%
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
prereq234_012
Anthropic revenue will cross OpenAI revenue in middle of 202Peter Diamandis
67.1%0.4500.050-0.051
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.450+0.044
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.4500.050-0.025
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.450+0.024
prereq235_002
Anthropic will exceed OpenAI in revenue this year (2026).Dave Blundin
74.6%0.4500.050-0.022

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq241_043
ASI will arrive within 2 years to 5 years to this next decadPeter Diamandis
35.9%0.6500.050-0.088
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050-0.086
prereqCMQ_002
By 2028, AI systems will reach 'independent researcher' leveSam Altman
31.4%0.5500.050-0.080
prereq232_055
We're exiting the industrial age permanently as recursive sePeter Diamandis
35.5%0.7000.050-0.066
prereqSEM_034
True artificial general intelligence will be achieved betweeDemis Hassabis
28.7%0.5500.050-0.054

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (8)

Predictions that must hit first
TypePredTitleDomainLag
prereq235_002Anthropic will exceed OpenAI in revenue this year (2026).AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereq234_012Anthropic revenue will cross OpenAI revenue in middle of 2026Markets/Stocks
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_0422025 will be the definitive year that agentic systems finally hit the mainstream.AI/Agents
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
prereq232_055We're exiting the industrial age permanently as recursive self-improvement unfolds.AI
prereq241_043ASI will arrive within 2 years to 5 years to this next decadeAI
prereqCMQ_002By 2028, AI systems will reach 'independent researcher' level — driving autonomous scientific discoveries without human intervention.AI
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

Linked documents (1)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.567manifoldWill Hack Club Stardance add a gambling/feature that resembles probability-based games6%mentionspending2026-06-04

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=LVvleNtllPk",
  "mode": "PREDICTION",
  "role": "Host",
  "context": "we're going to see more and more pop-up shops, retail venues, maybe even malls in the short term or medium term that are run, orchestrated, managed by AIS on behalf of humans.",
  "to_year": 2028,
  "verbatim": "I I think we're going to see more and more pop-up shops, retail venues, maybe even malls in the short term or medium term that are run, orchestrated, managed by AIS on behalf of humans. This is like a preview of the future.",
  "conv_cues": "I think",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "short to medium term",
  "conv_level": "MEDIUM",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "First AI-orchestrated pop-up retail launch by major brand",
      "source": "deep_research_enriched",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -9,
      "source_id": null,
      "confidence": 0.45,
      "expected_date": "2026-03-01",
      "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": "2026-06-30",
        "from": "2025-11-01"
      },
      "measurement_criterion": "Public announcement or press coverage of a brand using AI agents end-to-end (location, inventory, staffing, pricing) for a temporary retail venue."
    },
    {
      "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": -8,
      "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": -7,
      "source_id": "SEM_008",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic revenue will cross OpenAI revenue in middle of 2026",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "234_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic will exceed OpenAI in revenue this year (2026).",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -5,
      "source_id": "235_002",
      "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": -4,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "Retail-AI venture funding round >$50M",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2026-07-02",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2026-12-31",
        "from": "2026-01-01"
      },
      "measurement_criterion": "Series B+ funding for an AI-retail orchestration startup (Crunchbase / PitchBook) above $50M."
    },
    {
      "kind": "llm_pre_event",
      "label": "AI-orchestrated mall or multi-tenant venue announced",
      "source": "deep_research_enriched",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.35,
      "expected_date": "2026-10-30",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2027-03-31",
        "from": "20
... (truncated)