← Cockpit
247_050predictionBiotech/Longevitycrypto

Virtual cell achievable through classical scaling without quantum computing

Predictor: Alex Wissner-Gross · ep#247 "Elon Musk vs. Sam Altman, AI Job Loss, and OpenAI's $852B Valuation EP #247" · source

Prior probability
50.0%
Current probability
44.4%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2026-04-30 – 2030-12-31
Edges in / out
3 / 0
Tickers exposed
20

Prediction text

Virtual cell achievable through classical scaling without quantum computing | I would bet we don't actually need quantum computing at all to get to the virtual cell. We can we solved protein folding without quantum computing...I think we virtual cell just by existing scaling of of models

Verbatim quote

From episode "Elon Musk vs. Sam Altman, AI Job Loss, and OpenAI's $852B Valuation EP #247"
I would bet we don't actually need quantum computing at all to get to the virtual cell. We can we solved protein folding without quantum computing...I think we virtual cell just by existing scaling of of models

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

2 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-04-30
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 44.4%

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: 7 pending
  1. 2027-03-08pendingQ1 window check-in (25%)
  2. 2026-06-01 → 2028-06-30pendingArc Institute or CZI Virtual Cell program releases >=10x scaled multimodal cell foundation model
    How: Arc Institute, Chan Zuckerberg Initiative Virtual Cell program, or comparable consortium releases foundation model trained on >=10x more cells/modalities than current SOTA, no quantum component
    Source: https://www.biorxiv.org/content/10.64898/2026.04.11.717183v1conf 65%
  3. 2026-09-01 → 2028-06-30pendingFirst full-cell multimodal foundation model demonstrates causal-transport prediction across cell types in Nature/Science
    How: Top-tier journal publishes a foundation model (likely from Arc Institute, CZI Virtual Cell, Genentech-prescient, or DeepMind) that successfully predicts perturbation outcomes across previously unseen biological contexts using classical scaling architecture
    Source: https://www.nature.com/articles/s41586-025-08710-yconf 60%
  4. 2028-01-14pendingQ2 window check-in (50%)
  5. 2027-06-01 → 2029-12-31pendingAI-designed perturbation prediction reaches AlphaFold-tier benchmark accuracy via classical compute
    How: Published benchmark (analog of CASP for cell biology) shows classical-scaled model crossing accuracy threshold previously thought to require quantum-augmented methods
    Source: https://www.biorxiv.org/content/10.64898/2026.02.04.703804v1.fullconf 50%
  6. 2028-11-21pendingQ3 window check-in (75%)
  7. 2027-06-01 → 2030-06-30pendingMajor pharma signs >=$500M deal predicated on classical-scaled virtual-cell platform without quantum-computing dependency
    How: Top-15 pharma announces partnership or acquisition >=$500M whose technical thesis explicitly cites classical foundation-model scaling, no IBM/Google quantum dependence
    Source: https://www.cell.com/cell/fulltext/S0092-8674(24)01332-1conf 45%

No downstream cascades — this prediction is a leaf in the dependency graph.

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: 44%)

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
LBP2026-04-30T16:39:51Z44.4%-1.9pp
Network propagation: 46.3% → 44.4%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z46.3%-3.7pp
Network propagation: 50.0% → 46.3%
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
killerTK05
Rate Regime Persistence (10y > 5% through 2028)
30.0%0.0500.500-0.079
killerTK12
Crypto Regulatory Kill Shot (Stablecoin Ban / BTC ETF Revers
8.0%0.0500.500+0.020
killerTK10
$100T Sovereign Debt Crisis
12.0%0.0500.500+0.002

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

20 ticker(s) linked

Beneficiaries (17)

IONQTSEMMARAQUBTRGTIRIOTCRCLMASHOPAMZNCOINGOOGLHONHOODIBMKEYSXYZ

Adverse (2)

VMA

Prerequisites (3)

Predictions that must hit first
TypePredTitleDomainLag
killerTK05Rate Regime Persistence (10y > 5% through 2028)——
killerTK10$100T Sovereign Debt Crisis——
killerTK12Crypto Regulatory Kill Shot (Stablecoin Ban / BTC ETF Reversal)——

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Expected milestones (1)

From Sheet 17 Monitoring Triggers
Expected byDescriptionStatus
2031-03-31[Biology 2031-03] t readout (likely late 2026/early 2027) [247_050] Virtual cell achievable through classical scaling without quantum computingpending

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.673arxivHybrid Quantum-Classical Neural Architecture Search—mentionspending2026-05-18
0.673arxivQuantum-enhanced Large Language Models on Quantum Hardware via Cayley Unitary Adapters—mentionspending2026-05-07
0.651arxivComment on `On computing quantum waves exactly from classical action'—mentionspending2026-05-04
0.648arxivMagic-Informed Quantum Architecture Search—mentionspending2026-05-05
0.642arxivTowards Automated Discovery: A Review of Generative Models, Multimodal Learning and Closed-Loop Workflows in Inverse Materials Design—mentionspending2026-06-01
0.641arxivPerfect Parallelization in Mini-Batch SGD with Classical Momentum Acceleration—mentionspending2026-05-18
0.638arxivSOAR: Scale Optimization for Accurate Reconstruction in NVFP4 Quantization—mentionspending2026-05-12
0.637arxivQuantum Advantage in Multi Agent Reinforcement Learning—mentionspending2026-05-14
0.636arxivA-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion—mentionspending2026-05-05
0.636arxivDemystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling—mentionspending2026-06-01

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=5ak26W2YNRY",
  "mode": "BET",
  "role": "Host",
  "context": "I would bet we don't actually need quantum computing at all to get to the virtual cell",
  "verbatim": "I would bet we don't actually need quantum computing at all to get to the virtual cell. We can we solved protein folding without quantum computing...I think we virtual cell just by existing scaling of of models",
  "conv_cues": "I would bet",
  "direction": "HAPPEN",
  "timeframe": "Future",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -7,
      "source_id": null,
      "expected_date": "2027-03-08",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Arc Institute or CZI Virtual Cell program releases >=10x scaled multimodal cell foundation model",
      "source": "https://www.biorxiv.org/content/10.64898/2026.04.11.717183v1",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.65,
      "expected_date": "2027-06-16",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-06-30",
        "from": "2026-06-01"
      },
      "measurement_criterion": "Arc Institute, Chan Zuckerberg Initiative Virtual Cell program, or comparable consortium releases foundation model trained on >=10x more cells/modalities than current SOTA, no quantum component"
    },
    {
      "kind": "llm_pre_event",
      "label": "First full-cell multimodal foundation model demonstrates causal-transport prediction across cell types in Nature/Science",
      "source": "https://www.nature.com/articles/s41586-025-08710-y",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.6,
      "expected_date": "2027-08-01",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-06-30",
        "from": "2026-09-01"
      },
      "measurement_criterion": "Top-tier journal publishes a foundation model (likely from Arc Institute, CZI Virtual Cell, Genentech-prescient, or DeepMind) that successfully predicts perturbation outcomes across previously unseen biological contexts using classical scaling architecture"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2028-01-14",
      "observed_date": null
    },
    {
      "kind": "llm_post_event",
      "label": "AI-designed perturbation prediction reaches AlphaFold-tier benchmark accuracy via classical compute",
      "source": "https://www.biorxiv.org/content/10.64898/2026.02.04.703804v1.full",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.5,
      "expected_date": "2028-09-15",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2029-12-31",
        "from": "2027-06-01"
      },
      "measurement_criterion": "Published benchmark (analog of CASP for cell biology) shows classical-scaled model crossing accuracy threshold previously thought to require quantum-augmented methods"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2028-11-21",
      "observed_date": null
    },
    {
      "kind": "llm_post_event",
      "label": "Major pharma signs >=$500M deal predicated on classical-scaled virtual-cell platform without quantum-computing dependency",
      "source": "https://www.cell.com/cell/fulltext/S0092-8674(24)01332-1",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -1,
      "source_id": null,
   
... (truncated)