Jonathan Frankle
Chief AI Scientist at Databricks
Leading Mosaic Research lab, advancing AI training efficiency and neural network learning.
Jonathan Frankle serves as Chief AI Scientist at Databricks, where he leads research projects on reinforcement learning, model training, and agent evaluation. He heads Mosaic Research—a lab of more than thirty research scientists focused on enhancing the efficiency of training modern generative AI models, including LLMs and diffusion models, through empirical studies on neural network learning.
Frankle joined Databricks via the company’s $1.3B acquisition of MosaicML, where he was a member of the founding team. He completed his PhD in computer science at MIT in 2023; his research contributions are available on Google Scholar. He is best known academically for the lottery ticket hypothesis, though he often cites policy work on police use of facial recognition as the most consequential thing he has done outside the lab.
Based in New York City, Frankle travels frequently to San Francisco and Washington, DC. He previously joined Invisible Machines in Season 2 (recorded at MosaicML, before the acquisition was public) to discuss efficient LLM training and the practical craft of building with generative AI.