Research / Scientific Discovery
A deterministic Python project for empirical law discovery in elementary cellular automata, with simulation, discovery, reproducibility guides, and published preprints.
The page clearly presents a real AI-adjacent research tool with a defined purpose, visible usage commands, installation steps, reproducibility notes, and multiple releases. It is useful for researchers or builders working on cellular automata, empirical discovery, or deterministic agent workflows.
The snapshot does not show the internal architecture, what the seven cycle laws are in detail, or how the discovery loop chooses worlds beyond the high-level description. It also does not provide concrete output examples or a simple end-to-end walkthrough from install to results.
Last evaluated 63 days ago. Current rank #530. Up 2 spots in the rankings.
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.
