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SPC_030predictionEducationEureka-teacher-AI-symbiosis

Eureka Labs vision: 'teacher + AI symbiosis' that scales human expertise infinitely — generating hyper-capable problem-solvers aligned with the space-colonization-workforce demand of the 2030s.

Predictor: Andrej Karpathy

Prior probability
60.0%
Current probability
55.2%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
in_progress
Window
2026-01-01 – 2030-05-31
Edges in / out
1 / 0
Tickers exposed
0

Prediction text

Eureka Labs vision: 'teacher + AI symbiosis' that scales human expertise infinitely — generating hyper-capable problem-solvers aligned with the space-colonization-workforce demand of the 2030s. | Eureka Labs LLM101n first public cohort

Key catalyst: Eureka Labs LLM101n first public cohort

Watch events: Eureka Labs first course launch; student outcome data

Resolution evidence

Status: in_progress

Eureka Labs launched 2024; LLM101n course in development; teacher-AI copilot model prototyped.

Predictor: Andrej Karpathy

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0067
excellent
Hits / Misses
3 / 0
of 3 resolved
Hit rate
100.0%
Calibration plot (stated vs observed)

Evidence about this node from Andrej Karpathy 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 60%2026-04-302026-04-30
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 55.2%

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: 1 fired ✓ · 5 pending
  1. 2025-10-13hitKarpathy releases nanochat open-source LLM training pipeline (LLM101n capstone)
    How: Andrej Karpathy publishes nanochat repo on GitHub as the capstone codebase for the upcoming Eureka Labs LLM101n course; ~7,000+ stars within 24 hours
    Source: https://github.com/karpathy/nanochatconf 97%
    Notes: HIT — nanochat publicly released as the explicit capstone for LLM101n; precondition for cohort launch.
  2. 2026-10-10pendingQ1 window check-in (25%)
  3. 2026-06-01 → 2027-06-30pendingEureka Labs LLM101n first public cohort enrolls
    How: Eureka Labs publicly opens enrollment for LLM101n with a defined start date for digital and/or physical cohort, per eurekalabs.ai or Karpathy X account
    Source: https://eurekalabs.ai/ — Eureka Labs site listing LLM101n as flagship courseconf 65%
    Notes: Karpathy founded Eureka Labs July 2024, capstone (nanochat) shipped Oct 2025. Public cohort timing not yet confirmed — best estimate mid-2026 to mid-2027.
  4. 2027-07-19pendingQ2 window check-in (50%)
  5. 2027-01-01 → 2028-12-31pendingAI-tutor + teacher pairing format adopted by ≥3 mainstream education institutions
    How: ≥3 universities or major K-12 districts pilot AI-tutor + human-teacher hybrid programs explicitly modeled on Eureka Labs / similar AI-native pedagogy
    Source: Higher-ed press, EdTech industry coverageconf 55%
    Notes: Cascade — diffusion of teacher+AI-symbiosis model beyond Karpathy's startup.
  6. 2028-04-26pendingQ3 window check-in (75%)
  7. 2028-01-01 → 2030-05-31pendingEureka Labs / nanochat-derived alumni produce notable space-related contributions
    How: Public reporting identifies LLM101n alumni working at SpaceX, Blue Origin, NASA, or similar space-workforce employers in technical roles
    Source: Industry profile reportingconf 35%
    Notes: Cascade — speculative bridge between Karpathy education vision and the prediction's space-workforce angle.

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: 55%)

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
LBP2026-04-30T16:39:51Z55.2%-1.7pp
Network propagation: 56.8% → 55.2%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z56.8%-3.2pp
Network propagation: 60.0% → 56.8%
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
killerTK15
SpaceX Starship Catastrophic Failure
12.0%0.0500.600-0.018

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Prerequisites (1)

Predictions that must hit first
TypePredTitleDomainLag
killerTK15SpaceX Starship Catastrophic Failure

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Validations (1)

Resolution events
Observed atStatusByNotes
2026-04-29partialthesis_timeline_v1.0_importEureka Labs launched 2024; LLM101n course in development; teacher-AI copilot model prototyped.

Linked documents (1)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.649arxivTeamUp: Semantic Project Matching and Team Formation for Learning at Scalementionspending2026-05-05

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "mode": "FORECAST",
  "role": "Cited-Other",
  "context": "Second Karpathy-related education entry extending INF_041 (AI-native schools), AI_033 (Alpha 2.3x), AI_034 (global adoption 5yrs). Eureka Labs distinct from Alpha School.",
  "to_year": 2030,
  "conv_cues": "founder FIRST_PERSON; specific venture",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "2026-2030",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Karpathy releases nanochat open-source LLM training pipeline (LLM101n capstone)",
      "notes": "HIT — nanochat publicly released as the explicit capstone for LLM101n; precondition for cohort launch.",
      "source": "https://github.com/karpathy/nanochat",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -6,
      "source_id": null,
      "confidence": 0.97,
      "source_url": "https://github.com/karpathy/nanochat",
      "expected_date": "2025-10-13",
      "observed_date": "2025-10-13",
      "research_origin": "deep_research",
      "measurement_criterion": "Andrej Karpathy publishes nanochat repo on GitHub as the capstone codebase for the upcoming Eureka Labs LLM101n course; ~7,000+ stars within 24 hours"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -5,
      "source_id": null,
      "expected_date": "2026-10-10",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Eureka Labs LLM101n first public cohort enrolls",
      "notes": "Karpathy founded Eureka Labs July 2024, capstone (nanochat) shipped Oct 2025. Public cohort timing not yet confirmed — best estimate mid-2026 to mid-2027.",
      "source": "https://eurekalabs.ai/ — Eureka Labs site listing LLM101n as flagship course",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.65,
      "source_url": "https://eurekalabs.ai/",
      "expected_date": "2026-12-15",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2027-06-30",
        "from": "2026-06-01"
      },
      "measurement_criterion": "Eureka Labs publicly opens enrollment for LLM101n with a defined start date for digital and/or physical cohort, per eurekalabs.ai or Karpathy X account"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2027-07-19",
      "observed_date": null
    },
    {
      "kind": "llm_post_event",
      "label": "AI-tutor + teacher pairing format adopted by ≥3 mainstream education institutions",
      "notes": "Cascade — diffusion of teacher+AI-symbiosis model beyond Karpathy's startup.",
      "source": "Higher-ed press, EdTech industry coverage",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2028-01-01",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2027-01-01"
      },
      "measurement_criterion": "≥3 universities or major K-12 districts pilot AI-tutor + human-teacher hybrid programs explicitly modeled on Eureka Labs / similar AI-native pedagogy"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -1,
      "source_id": null,
      "expected_date": "2028-04-26",
      "observed_date": null
    },
    {
      "kind": "event",
      "label": "Eureka Labs vision: 'teacher + AI symbiosis' that scales human expertise infinitely — generating hyper-capable problem-solvers aligned with ",
      "status": "pending",
      "weight": 1,
      "ordinal": 0,
      "source_id": "SPC_030",
      "expected_date": "2029-02-03",
 
... (truncated)