#evolutionary-search

1 articles

01 ·Agents·FREE·PAPER·11 min read Paper Deep-Dive: Frontis-MA1 — Training the AI That Builds AI: One Step Toward Recursive Self-Improvement in ML Engineering Instead of training a model to solve tasks, train the operations that improve solutions — then run evolutionary search with those trained operations. A walkthrough of the OpenMLE stack and the 35B Frontis-MA1 model, straight from the paper: what's behind the 39.39%→71.21% jump on MLE-Bench Lite, how the search got cheaper and better at once, and the limits the authors themselves spell out.