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I am a Director at Cohere and I lead Cohere For AI, a research lab that seeks to solve complex machine learning problems. We support fundamental research that explores the unknown. I lead a team of researchers and engineers working on making large language models more efficient, safe and grounded.
Prior to Cohere, I was a research scientist Google Brain doing work on training models that go beyond test-set accuracy to fulfill multiple desired criteria -- interpretable, compact, fair and robust. I enjoy working on research problems where progress translates to reliable and accessible machine learning in the real-world. I founded a local Bay Area non-profit called Delta Analytics that works with non-profits and communities all over the world to build technical capacity and empower others to use data. I remain an advisor on the Delta Analytics board. I am one of the co-founders of the Trustworthy ML Initiative, a forum and seminar series related to Trustworthy ML. I believe in open research and collaborating widely. I am on the advisory board of Patterns and on Kaggle's ML Advisory Research Board. I am on the World Economic Forum council on the Future of Artificial Intelligence. Amongst other efforts, I am an active member of the MLC research group which has a focus on making participation in machine learning research more accessible. If you made it this far -- Listen to underrated ml -- a podcast where Sean Hooker and I discuss underrated ideas in machine learning. Other writing: The Hardware Lottery Why data for good lacks precision. Research Papers |
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