intelligence-radar/SourceCatalog.md

Imported research draft. Benchmark versions, availability, and source claims require verification before operational use.

Intelligence Radar — Source Catalog

Status: Seed catalog 0.1
Date: 2026-09-13

1. Source policy

The monitoring system should aggressively discover information but conservatively promote claims.

Priority order for durable facts:

1. original research/data;
2. benchmark maintainers;
3. official model/system cards and provider documentation;
4. official standards/regulatory/legal sources;
5. independent evaluators and systematic syntheses;
6. expert interpretation;
7. journalism/social discussion for discovery.

A thinker being influential is a reason to monitor them, not a reason to accept their claims.

2. Scientific research streams

Monitor primary publications and proceedings in:

• machine learning and AI;
• cognitive science;
• neuroscience;
• psychology/psychometrics;
• robotics;
• complex systems;
• cybernetics/control;
• collective intelligence;
• computational biology;
• philosophy of mind where empirically relevant.

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.

3. AI labs and model providers — official sources

Seed set:

• OpenAI — releases, model/system cards, API/model docs, safety/deployment material.
• Anthropic — research, model releases, system cards, API docs, pricing.
• Google DeepMind / Google AI — research, model cards, Gemini API docs.
• Meta AI — model/research releases.
• xAI — model releases and technical documentation.
• DeepSeek — model/research releases.
• Alibaba/Qwen — model/research releases.
• Mistral AI — model/research releases.
• Cohere — model/research releases.
• NVIDIA — model, inference, accelerator, and serving research.
• major open-weight research organizations as they emerge.

4. Evaluation and benchmark maintainers

Seed set:

• SWE-bench
• Berkeley Function Calling Leaderboard (BFCL)
• METR
• ARC Prize / ARC-AGI
• OSWorld
• Sierra research / τ-bench family
• MLCommons / MLPerf
• SciCode
• Humanity's Last Exam maintainers
• major benchmark authors/repositories discovered through current research

Each benchmark needs its own version/change monitor.

5. Independent capability/economics measurement

Artificial Analysis

Useful for:

• cross-provider model measurements;
• benchmark results;
• cost per task;
• token use;
• speed/latency;
• provider comparisons;
• evolving aggregate and domain indices.

Treat its private tests and methodology as independent evidence, not fully reproducible primary benchmark truth.

Stanford HAI AI Index

Useful periodic synthesis of:

• capability trends;
• benchmark health;
• economics;
• adoption;
• social/policy trends.

Additional independent evaluators

Add only after documenting methodology, independence, update cadence, and data access.

6. Hardware and inference engineering

Seed primary sources:

• MLCommons / MLPerf;
• NVIDIA;
• AMD;
• Intel;
• Google Cloud/TPU material;
• AWS accelerator/inference infrastructure;
• Microsoft/Azure infrastructure;
• hyperscaler research and engineering publications;
• compiler/serving projects relevant to inference economics.

Track:

• throughput;
• latency;
• power;
• memory;
• interconnect;
• quantization;
• batching;
• speculative decoding;
• serving frameworks;
• price/performance.

7. Regulation, standards, and institutions

European Union

Monitor original European Commission / AI Office / EUR-Lex materials for AI Act implementation, delegated/implementing acts, codes, guidance, and enforcement milestones.

United States

Monitor relevant NIST, federal agency, legislative, standards, and official policy sources.

International

Monitor:

• OECD AI policy materials;
• ISO/IEC JTC 1/SC 42 where accessible;
• IEEE standards initiatives;
• Council of Europe AI convention implementation;
• other jurisdictions as capability or market relevance requires.

8. Thinker watchlist — seed, not canon

The watchlist should span disagreement.

Candidate clusters:

Foundations / learning / AI

• Geoffrey Hinton
• Yann LeCun
• Yoshua Bengio
• Richard Sutton
• Demis Hassabis
• Ilya Sutskever
• Dario Amodei
• François Chollet

Cognitive science / neuroscience / intelligence

• active researchers in psychometrics, cognitive architectures, predictive processing, memory, development, animal cognition, and computational neuroscience.

Systems / cybernetics lineage

Historical compendium coverage should include:

• Norbert Wiener
• W. Ross Ashby
• Stafford Beer
• Heinz von Foerster
• Humberto Maturana
• Francisco Varela

Current monitoring should focus on contemporary researchers extending relevant ideas rather than treating historical figures as news sources.

Critique / alternative interpretations

Monitor credible researchers who challenge:

• scaling narratives;
• benchmark validity;
• claims of generality;
• economic assumptions;
• safety assumptions;
• anthropomorphic interpretations.

The purpose is epistemic diversity, not artificial balance.

9. Source record schema

id: source-...
name: ...
kind: paper_feed|lab|benchmark|provider_docs|regulator|thinker|journal|evaluator
primary: true
trust_tier: A
topics: [...]
url: ...
retrieval:
  mode: rss|html|api|github|manual
  cadence: daily
importance: 0.9
last_reviewed: 2026-09-13
notes: ...

10. Source-health policy

Periodically score:

• authority for the claimed fact;
• independence;
• reproducibility;
• provenance quality;
• update timeliness;
• correction transparency;
• historical reliability;
• machine-retrieval stability.

A source can be excellent for one class of fact and weak for another.

Example:

A provider's API page is authoritative for its current list price, but not neutral evidence that its model is the world's best.