METR

IAPS fellow Severin Field interviewed 25 researchers from top AI labs about recursive self-improvement in late 2025. Several milestones they cited as evidence of progress — Math Olympiad gold, autonomous training loops, majority AI-written code — have since occurred, according to a new report.

A new Epoch/METR benchmark called MirrorCode shows Claude Opus 4.7 reimplementing large software programs from scratch in tasks estimated to take humans 2-17 weeks, for $251 in inference cost. Separately, Anthropic reports Opus 4.7 completed a suite of quadruped robot tasks in 9 minutes 35 seconds, down from 181 minutes with an earlier model assisting humans.

Research organization METR has introduced the 'expenditure horizon,' a metric that pinpoints the exact budget at which an AI agent becomes cheaper than a human at solving the same problem. Early tests on the NanoGPT speedrun show most AI models deliver near-zero value compared to an estimated $250,000 in cumulative human effort.