Efficient AI Computing,
Transforming the Future.

Jack Cook

Ph.D

(Graduated)

Jack is a first-year PhD student advised by Prof. Song Han. He previously studied at the University of Oxford while supported by a Rhodes Scholarship, and he’s worked on LLMs at Modal, The New York Times, and NVIDIA. Jack holds master’s degrees in computer science, neuroscience, and social science, and as an undergraduate at MIT, he was previously the director of HackMIT. His research interests involve making LLMs more efficient, with a focus on low-bit quantization.

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Open source projects with over 1K GitHub stars

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