AI will compress decades of research into years, months, weeks
Predictor: Salim Ismail · ep#240 "NVIDIA's $1 Trillion Prediction, Anthropic Beats OpenAI, Tesla vs. TSMC & The CS Job Collapse" · source
Prediction text
AI will compress decades of research into years, months, weeks | this is going to compress like decades of research into years, months, weeks.
Verbatim quote
this is going to compress like decades of research into years, months, weeks.
Predictor: Salim Ismail
Calibration plot (stated vs observed)
Evidence about this node from Salim Ismail 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
This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.
Probability over time
Milestone chain
- 2024-04-01overdueAlphaFold-class breakthrough in second scientific domain (materials/chem)How: DeepMind GNoME or equivalent compresses materials discovery — 380K+ stable materials predicted, ~8x historical human catalogSource: https://deepmind.google/blog/alphafold-using-ai-for-scientific-discovery-2020/conf 95%Notes: GNoME shipped Nov 2023; AlphaFold 3 (May 2024) extended to ligand/DNA. Already validated as compression precedent.
- 2026-01-01 → 2027-06-30pendingFirst clinical trial for AlphaFold-derived drug enters Phase 1How: FDA IND filing for AI-designed drug citing AlphaFold structure prediction as load-bearing in designSource: FDA IND filings, Isomorphic Labs pipelineconf 65%
- 2026-10-23pendingQ1 window check-in (25%)
- 2026-04-01 → 2027-12-31pendingDOE Genesis or equivalent national-AI-for-science program operationalHow: US DOE Genesis mission with DeepMind partnership reaches operational milestones — exascale simulation runs, materials/energy outputs publishedSource: https://www.bnl.gov/newsroom/news.php?a=222774conf 70%
- 2027-04-17pendingQ2 window check-in (50%)
- 2027-10-10pendingQ3 window check-in (75%)
- 2026-10-01 → 2028-12-31pendingNobel Prize awarded to AI-led research workflowHow: Nobel Prize (Chemistry/Physics/Medicine) awarded for discovery where AI tool was load-bearing — beyond Hassabis/Jumper 2024Source: Nobel Committee announcementsconf 40%
- 2027-01-01 → 2029-03-31pendingTime-to-discovery in major journal cohort drops measurablyHow: Bibliometric study shows median hypothesis-to-publication time in computational biology / materials drops by >=30% vs 2024 baselineSource: Nature / Science bibliometric analysesconf 50%
No downstream cascades — this prediction is a leaf in the dependency graph.
What if this resolves?
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
Raw metadata
{
"trf": 0.9972591226262507,
"kappa": 0.6429,
"base_rate": null,
"predictor": "Salim Ismail",
"total_llr": -0.4054651081081644,
"grace_days": 7,
"bayesian_v2": true,
"prior_logit": -0.020254659005855134,
"bayes_factor": "1.3:1 against",
"blend_reason": "no reference_class linked",
"inside_prior": 0.49493650835598435,
"kappa_source": "predictor_table",
"n_milestones": 1,
"blend_applied": false,
"contributions": [
{
"llr": -0.4054651081081644,
"kind": "llm_pre_event",
"kappa": 0.610755,
"label": "AlphaFold-class breakthrough in second scientific domain (materials/chem)",
"weight": 0.4,
"strength": "weak",
"confidence": 0.95,
"source_url": "https://deepmind.google/blog/alphafold-using-ai-for-scientific-discovery-2020/",
"adjusted_llr": -0.24763984210260195,
"expected_date": "2024-04-01",
"measurement_criterion": "DeepMind GNoME or equivalent compresses materials discovery — 380K+ stable materials predicted, ~8x historical human catalog"
}
],
"evidence_kind": "metadata_milestone_miss_sweep",
"inside_source": "history_v2",
"inside_weight": 0.30191861416162447,
"outside_weight": 0.6980813858383755,
"posterior_prob": 0.4334240647810704,
"posterior_logit": -0.2678945011084571,
"predictor_brier": 0.01445,
"inside_posterior": 0.4334240647810704,
"blended_posterior": 0.4334240647810704,
"reference_class_id": null,
"total_adjusted_llr": -0.24763984210260195,
"predictor_n_resolved": 2
}Network propagation neighbors
Top incoming (parents)
Edges that influence THIS node's belief
| Kind | Node | Their prob | P(c|s=T) | P(c|s=F) | Δ implied |
|---|---|---|---|---|---|
| prereq | S_AGI_MID_2029 AGI mid: Kurzweil 2029 path | 35.0% | 0.550 | 0.050 | -0.194 |
| killer | TK03 AI Regulatory Moratorium (EU/US Capability Freeze) | 10.0% | 0.050 | 0.550 | +0.081 |
| killer | TK01 AGI Capability Plateau (2026-27 Training Stall) | 15.0% | 0.050 | 0.550 | +0.056 |
| killer | TK14 Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates) | 20.0% | 0.050 | 0.550 | +0.031 |
Top outgoing (children)
Predictions THIS node influences
No outgoing edges.
Ticker exposure
Beneficiaries (23)
Adverse (6)
Prerequisites (5)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| prereq | S_AGI_MID_2029 | AGI mid: Kurzweil 2029 path | agi_general_capability | — |
| correlate | S_AGI_SLOW_2031 | AGI slow: Schmidt/Hassabis 5-10 year path | agi_general_capability | — |
| killer | TK14 | Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates) | — | — |
| killer | TK01 | AGI Capability Plateau (2026-27 Training Stall) | — | — |
| killer | TK03 | AI Regulatory Moratorium (EU/US Capability Freeze) | — | — |
Dependents (0)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| No dependents | ||||
Linked documents (10)
Raw metadata
{
"nia": false,
"qty": "decades into weeks",
"url": "https://www.youtube.com/watch?v=uOGHXAfvK8w",
"mode": "THESIS",
"role": "Host",
"context": "this is going to compress like decades of research into years, months, weeks.",
"verbatim": "this is going to compress like decades of research into years, months, weeks.",
"conv_cues": "going to",
"direction": "HAPPEN",
"timeframe": "Future",
"conv_level": "HIGH",
"milestones": [
{
"kind": "llm_pre_event",
"label": "AlphaFold-class breakthrough in second scientific domain (materials/chem)",
"notes": "GNoME shipped Nov 2023; AlphaFold 3 (May 2024) extended to ligand/DNA. Already validated as compression precedent.",
"source": "https://deepmind.google/blog/alphafold-using-ai-for-scientific-discovery-2020/",
"status": "overdue",
"weight": 0.4,
"ordinal": -8,
"source_id": null,
"confidence": 0.95,
"source_url": "https://deepmind.google/blog/alphafold-using-ai-for-scientific-discovery-2020/",
"expected_date": "2024-04-01",
"miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
"miss_emitted_by": "metadata_milestone_sweep",
"research_origin": "deep_research",
"measurement_criterion": "DeepMind GNoME or equivalent compresses materials discovery — 380K+ stable materials predicted, ~8x historical human catalog"
},
{
"kind": "llm_pre_event",
"label": "First clinical trial for AlphaFold-derived drug enters Phase 1",
"source": "FDA IND filings, Isomorphic Labs pipeline",
"status": "pending",
"weight": 0.4,
"ordinal": -7,
"source_id": null,
"confidence": 0.65,
"expected_date": "2026-09-30",
"research_origin": "training",
"expected_date_range": {
"to": "2027-06-30",
"from": "2026-01-01"
},
"measurement_criterion": "FDA IND filing for AI-designed drug citing AlphaFold structure prediction as load-bearing in design"
},
{
"kind": "quartile_checkpoint",
"label": "Q1 window check-in (25%)",
"status": "pending",
"weight": 0.05,
"ordinal": -6,
"source_id": null,
"expected_date": "2026-10-23",
"observed_date": null
},
{
"kind": "llm_pre_event",
"label": "DOE Genesis or equivalent national-AI-for-science program operational",
"source": "https://www.bnl.gov/newsroom/news.php?a=222774",
"status": "pending",
"weight": 0.4,
"ordinal": -5,
"source_id": null,
"confidence": 0.7,
"source_url": "https://www.bnl.gov/newsroom/news.php?a=222774",
"expected_date": "2027-02-14",
"research_origin": "deep_research",
"expected_date_range": {
"to": "2027-12-31",
"from": "2026-04-01"
},
"measurement_criterion": "US DOE Genesis mission with DeepMind partnership reaches operational milestones — exascale simulation runs, materials/energy outputs published"
},
{
"kind": "quartile_checkpoint",
"label": "Q2 window check-in (50%)",
"status": "pending",
"weight": 0.05,
"ordinal": -4,
"source_id": null,
"expected_date": "2027-04-17",
"observed_date": null
},
{
"kind": "quartile_checkpoint",
"label": "Q3 window check-in (75%)",
"status": "pending",
"weight": 0.05,
"ordinal": -3,
"source_id": null,
"expected_date": "2027-10-10",
"observed_date": null
},
{
"kind": "llm_post_event",
"label": "Nobel Prize awarded to AI-led research workflow",
"source": "Nobel Committee announcements",
"status": "pending",
"weight": 0.4,
"ordinal": -2,
"source_id": null,
"confidence": 0.4,
"expected_date": "2027-11-16",
"research_origin": "training",
"expected_date_range": {
"to": "2028-12-31",
"from": "2026-10-01"
},
"measurement_criterion": "Nobel Prize (Chemistry/Phy
... (truncated)