We release a database of over 1,100 biological AI models across nine categories. We analyze their safeguards, accessibility, training data sources, and the foundation models they build on.
These benchmarks track a wide range of digital work. Progress will correlate with economic utility, but tasks are too self-contained to indicate full automation.
We assess the current state of autonomous robotics by evaluating robot performance on concrete tasks across industrial, household, and navigation domains.
In 2025, Epoch AI published over a hundred outputs, more than doubled its reach and raised over ten million dollars.
We announce our new AI Chip Sales data explorer, which uses financial reports, company disclosures, and more to estimate compute, power usage, and spending over time for a wide variety of AI chips.
In 2025 we released over 70 short form investigations of AI. We review the 10 most popular ones on our website.
Most benchmarks saturate too quickly to study long-run AI trends. We solve this using a statistical framework that stitches benchmarks together, with big implications for algorithmic progress and AI forecasting.
We announce our new Frontier Data Centers Hub, a database tracking large AI data centers using satellite and permit data to show compute, power use, and construction timelines.
AI companies are planning a buildout of data centers that will rank among the largest infrastructure projects in history. We examine their power demands, what makes AI data centers special, and what all this means for AI policy and the future of AI.
We review OSWorld, a prominent computer use benchmark. Its tasks are relatively simple, many don’t require GUIs, and success often hinges on interpreting ambiguous instructions. It is also not stable over time.
