Integrate founding explorations and bootstrap operational radar
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SourceCatalog.md
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SourceCatalog.md
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> Imported research draft. Benchmark versions, availability, and source claims require verification before operational use.
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# Intelligence Radar — Source Catalog
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**Status:** Seed catalog 0.1
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**Date:** 2026-09-13
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## 1. Source policy
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The monitoring system should aggressively discover information but conservatively promote claims.
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Priority order for durable facts:
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1. original research/data;
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2. benchmark maintainers;
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3. official model/system cards and provider documentation;
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4. official standards/regulatory/legal sources;
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5. independent evaluators and systematic syntheses;
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6. expert interpretation;
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7. journalism/social discussion for discovery.
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A thinker being influential is a reason to monitor them, not a reason to accept their claims.
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## 2. Scientific research streams
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Monitor primary publications and proceedings in:
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- machine learning and AI;
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- cognitive science;
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- neuroscience;
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- psychology/psychometrics;
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- robotics;
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- complex systems;
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- cybernetics/control;
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- collective intelligence;
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- computational biology;
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- philosophy of mind where empirically relevant.
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High-signal discovery surfaces include arXiv categories, major peer-reviewed journals, and major conference proceedings. The source registry should resolve interesting discoveries to the actual paper/repository/data.
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## 3. AI labs and model providers — official sources
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Seed set:
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- OpenAI — releases, model/system cards, API/model docs, safety/deployment material.
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- Anthropic — research, model releases, system cards, API docs, pricing.
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- Google DeepMind / Google AI — research, model cards, Gemini API docs.
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- Meta AI — model/research releases.
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- xAI — model releases and technical documentation.
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- DeepSeek — model/research releases.
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- Alibaba/Qwen — model/research releases.
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- Mistral AI — model/research releases.
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- Cohere — model/research releases.
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- NVIDIA — model, inference, accelerator, and serving research.
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- major open-weight research organizations as they emerge.
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## 4. Evaluation and benchmark maintainers
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Seed set:
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- SWE-bench
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- Berkeley Function Calling Leaderboard (BFCL)
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- METR
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- ARC Prize / ARC-AGI
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- OSWorld
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- Sierra research / τ-bench family
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- MLCommons / MLPerf
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- SciCode
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- Humanity's Last Exam maintainers
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- major benchmark authors/repositories discovered through current research
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Each benchmark needs its own version/change monitor.
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## 5. Independent capability/economics measurement
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### Artificial Analysis
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Useful for:
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- cross-provider model measurements;
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- benchmark results;
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- cost per task;
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- token use;
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- speed/latency;
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- provider comparisons;
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- evolving aggregate and domain indices.
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Treat its private tests and methodology as independent evidence, not fully reproducible primary benchmark truth.
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### Stanford HAI AI Index
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Useful periodic synthesis of:
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- capability trends;
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- benchmark health;
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- economics;
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- adoption;
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- social/policy trends.
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### Additional independent evaluators
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Add only after documenting methodology, independence, update cadence, and data access.
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## 6. Hardware and inference engineering
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Seed primary sources:
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- MLCommons / MLPerf;
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- NVIDIA;
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- AMD;
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- Intel;
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- Google Cloud/TPU material;
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- AWS accelerator/inference infrastructure;
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- Microsoft/Azure infrastructure;
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- hyperscaler research and engineering publications;
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- compiler/serving projects relevant to inference economics.
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Track:
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- throughput;
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- latency;
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- power;
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- memory;
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- interconnect;
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- quantization;
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- batching;
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- speculative decoding;
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- serving frameworks;
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- price/performance.
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## 7. Regulation, standards, and institutions
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### European Union
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Monitor original European Commission / AI Office / EUR-Lex materials for AI Act implementation, delegated/implementing acts, codes, guidance, and enforcement milestones.
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### United States
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Monitor relevant NIST, federal agency, legislative, standards, and official policy sources.
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### International
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Monitor:
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- OECD AI policy materials;
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- ISO/IEC JTC 1/SC 42 where accessible;
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- IEEE standards initiatives;
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- Council of Europe AI convention implementation;
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- other jurisdictions as capability or market relevance requires.
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## 8. Thinker watchlist — seed, not canon
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The watchlist should span disagreement.
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Candidate clusters:
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### Foundations / learning / AI
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- Geoffrey Hinton
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- Yann LeCun
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- Yoshua Bengio
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- Richard Sutton
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- Demis Hassabis
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- Ilya Sutskever
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- Dario Amodei
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- François Chollet
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### Cognitive science / neuroscience / intelligence
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- active researchers in psychometrics, cognitive architectures, predictive processing, memory, development, animal cognition, and computational neuroscience.
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### Systems / cybernetics lineage
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Historical compendium coverage should include:
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- Norbert Wiener
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- W. Ross Ashby
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- Stafford Beer
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- Heinz von Foerster
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- Humberto Maturana
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- Francisco Varela
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Current monitoring should focus on contemporary researchers extending relevant ideas rather than treating historical figures as news sources.
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### Critique / alternative interpretations
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Monitor credible researchers who challenge:
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- scaling narratives;
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- benchmark validity;
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- claims of generality;
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- economic assumptions;
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- safety assumptions;
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- anthropomorphic interpretations.
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The purpose is epistemic diversity, not artificial balance.
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## 9. Source record schema
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```yaml
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id: source-...
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name: ...
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kind: paper_feed|lab|benchmark|provider_docs|regulator|thinker|journal|evaluator
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primary: true
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trust_tier: A
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topics: [...]
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url: ...
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retrieval:
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mode: rss|html|api|github|manual
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cadence: daily
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importance: 0.9
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last_reviewed: 2026-09-13
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notes: ...
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```
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## 10. Source-health policy
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Periodically score:
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- authority for the claimed fact;
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- independence;
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- reproducibility;
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- provenance quality;
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- update timeliness;
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- correction transparency;
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- historical reliability;
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- machine-retrieval stability.
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A source can be excellent for one class of fact and weak for another.
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Example:
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A provider's API page is authoritative for its **current list price**, but not neutral evidence that its model is the world's best.
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