Research / AI Safety
A DeepMind technical report PDF about double-blind AI evaluations and confidentiality issues in AI safety research.
The crawl snapshot shows a substantive DeepMind technical report with a specific AI-safety focus. Even though the PDF text is not extracted cleanly, the URL, source path, and supplied title clearly indicate a real research document on double-blind evaluations and confidentiality, which is useful for AI safety readers and builders.
The crawl does not expose the report’s abstract, authors, findings, or section structure, so a visitor cannot tell the main method or conclusions without opening the PDF.
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Primus is an autonomous AI researcher that hypothesizes, reads papers, writes code, runs experiments on compute, and drafts research papers. The page shows example tasks, published-paper claims, waitlist access, and positioning for ML research workflows.
An interactive dashboard that analyzes New York Times coverage since 2000 using the NYT Archive API, with views for reporters, beats, sections, subjects, geography, obituaries, and corrections.
An open benchmark and leaderboard for AI CAD agents, with 308 prompts across 20 categories and layered scoring for geometry, engineering, manufacturability, and cognition.
A research article from Applied Compute on how agentic, tool-using workloads differ from traditional LLM benchmarks, with production observations, workload profiles, and an open-source harness for replaying traces.
