Signal
8 articles covering "ai-research"
OpenAI created a Princeton-hosted advisory group of nine named mathematicians after its unreleased model, begun training August 28, resolved 100+ open math problems.
UC Berkeley and MIT researchers, with Databricks co-founders Matei Zaharia and Ion Stoica, released an open-source engine that serves up to 753-billion-parameter MoE models on a single workstation GPU.
A new empirical study finds 248,641 AI-authored GitHub pull requests have already received an AI-generated review, with distinct patterns by agent pairing.
A new empirical study finds coding agents overwhelmingly read and write their own instruction files, rarely touch classical documentation, and almost never use docs to recover from failures.
A George Mason University study finds a software task's difficulty for AI coding agents can be predicted from patch and repository structure before the agent ever runs.
A study spanning seven AI models and five coding-agent harnesses finds they fail identically when a required repository fact is unavailable, and fabricate rather than stop.
A DeepMind preprint reports an LLM-and-Lean agent that autonomously solved 9 of 353 open Erdős problems and proved 44 of 492 OEIS conjectures for a few hundred dollars each.
Physical Intelligence released π0.7, a generalist robot model that lifts air fryer task success from 5 to 95 percent through plain-language coaching and matches specialist RL models on laundry, espresso, and box assembly.