Computer Use at the Edge of the Statistical Precipice — Pierluca D'Oro, Programma Labs
- Source
- AI Engineer
- Author
- AI Engineer
- Date
- benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.
Anyone reading computer-use numbers is likely reading an artifact of deterministic environments and undersized confidence intervals, and this gives both the proof and the environment design that fixes it.
“A script under one megabyte that never looks at the screen matches or beats the frontier model it was copied from.”
AI Engineer
“The paper goes further and proves that pass@k on a deterministic environment is exactly the success rate of that replay script, so a metric the field leans on turns out to be a formal measure of the exploit.”
AI Engineer
“Environments get the PRISM principles: privileged verification, realism, integrity checked configurations, sandboxed execution, and multifactorial variation across data, theme, and starting screen.”
AI Engineer
“DIGIWORLD instantiates them in 15 sandboxed mobile apps and 3.2 million verified configurations, generated by a compiler that produces every combination and rejects the broken ones, because a coding agent emitting a lot of software is not the same thing as a good environment.”
AI Engineer
“Naive rollouts on a single base case yield confidence intervals that actually contain the true performance around 20% of the time rather than 95%, and he prices the consequence: a 4% gap between two models, hidden under intervals that look tight, costs hundreds of thousands of dollars a month across a million tasks.”
AI Engineer
videoHow I deleted 95% of my agent skills and got better results — Nick Nisi, WorkOSAI Engineer
videoTraining Frontier Models to Out-Think Hackers — Uri Rolls, Arithmetic & Thom Wolf, Hugging FaceAI Engineer
videoThe Dark Arts of Web Automation: Teaching Agents to Use Websites Like Humans — Corey Gallon, RexmoreAI Engineer
Checking sign-in…
Loading comments…