Jonathan Frankle
Chief AI Scientist at Databricks; first author of the lottery ticket hypothesis paper; MosaicML founding team
- Chief AI Scientist, Databricks123
Jonathan Frankle is Chief AI Scientist at Databricks, where Frankle leads research projects on reinforcement learning, model training and agent evaluation; Frankle arrived through Databricks' acquisition of MosaicML, where Frankle was a member of the founding team. Frankle completed a PhD in computer science at MIT in 2023, and the main line of that research was the lottery ticket hypothesis, introduced in a 2018 paper with Michael Carbin, which studies how small neural networks can be during training. Frankle is a bylined author of Databricks' March 2024 post announcing the DBRX model and a co-author of the MosaicBERT paper on fast pretraining of a bidirectional encoder.13456
Work
The Lottery Ticket Hypothesis (external site: arxiv.org)Published research
First author, with Michael Carbin, of "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" (2018); Frankle's homepage describes this line of work as the main research of Frankle's PhD.41
DBRX (external site: databricks.com)
First-listed of six bylined authors of Databricks' March 2024 post announcing DBRX, a mixture-of-experts language model built on the MegaBlocks research and open-source project.5
MosaicBERT (external site: arxiv.org)Published research
Co-author of "MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining" (2023).6
Other documented roles
Roles the sources document but that are not confirmed as current.
- Member of the founding team, MosaicML13
- PhD student in computer science (completed 2023), Massachusetts Institute of Technology1
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