Forecasting the Remote Labor Index
Can we forecast when AI agents will complete real-world work? New methods for predicting performance on the Remote Labor Index.
Can we forecast when AI agents will complete real-world work? New methods for predicting performance on the Remote Labor Index.
With a larger inference budget, GLM-5.3-Flash matched Mythos Preview on ExploitBench at about 6% of the cost.
Flawed tasks and grading errors conceal how well agents perform. Correcting them raises measured performance by up to 42 percentage points.
We're an R&D lab that solves practical challenges facing AI safety organisations, focusing on AI evaluation.
For organisations that want on-demand access to AI evaluation expertise.
Expand access to high-quality data and measurement tools.
We actively maintain 100+ eval implementations in the Inspect Evals repository. They've been used in dozens of research projects and testing exercises.
We recently built the Inspect Evals Register, making it easier than ever to find and share Inspect Tasks.
With AI safety orgs scaling up and moving fast, it's important to maintain the highest possible standards when measuring and reporting risks.
We provide 3rd-party audits for evals, helping research teams catch issues early and maintain trust.