Percy Liang
Director of Stanford CRFM
Associate professor of Computer Science at Stanford and director of the Center for Research on Foundation Models (CRFM), which studies large AI models and built the HELM evaluation benchmark.
Key arguments & positions
- Argues foundation models should be evaluated transparently and holistically, and built the HELM benchmark to make model capabilities and risks comparable across labs.
- Advocates for open research on foundation models so the scientific community, not only the labs building them, can study how they work.
Accomplishments
- Associate professor of Computer Science at Stanford and director of the Center for Research on Foundation Models (CRFM).
- Led the creation of HELM (Holistic Evaluation of Language Models), a widely cited benchmark for comparing large models.
Papers & key writings
Links
In the library
Nothing of theirs is filed in the hub yet. Browse the full library.
Recommended next
Hand-picked from the hub based on what Percy Liang covers.
Snorkel AI Research & Blog
The free research library and blog of Snorkel AI, the company spun out of Stanford's Snorkel project on programmatic labelling. The papers and posts explain how training data for AI models is actually built — labelling, evaluation sets, and the 'environments' used to train agents. Useful if you want to understand the unglamorous data work behind model quality, which is where a lot of the real jobs are.
Why this: Covers ai research and evaluation too
Two Minute Papers (YouTube)
This YouTube channel offers simple video breakdowns of artificial intelligence and machine learning research papers. You can watch these quick guides to stay informed about new AI developments and understand how the technology is evolving.
Why this: Also about ai research
Natural General Intelligence
An essay arguing for building a large model of the natural world — weather, oceans, ecosystems — as its own kind of general intelligence, separate from language models.
Why this: Also about ai research
Fei-Fei Li
Stanford professor who built ImageNet, co-directs Stanford's Human-Centered AI institute and co-founded the AI4ALL diversity pipeline program. Her faculty page collects the work; her Google Scholar list has the papers themselves.
Why this: Also about ai research