Thursday Nights in AI: Jonathan Frankle, MosaicML (by application only)
Join us for a fireside chat with Jonathan Frankle, Chief Scientist, MosaicML
About Jonathan Frankle: Jonathan is the Chief Scientist at MosaicML, leading the company’s research team toward developing more efficient algorithms for training neural networks.
When the Databricks acquisition closes, Jonathan will be joining Databricks as Chief Neural Network Scientist, where he will be doing exactly what he's been doing at Mosaic, except bigger and better than ever before.
Jonathan previously earned his bachelor's and master's at Princeton, and worked at Google, Google Brain, and Facebook AI Research. He completed his PhD at MIT, where he focused on using experimental methods to understand the behavior of neural networks. There he published his Lottery Ticket Hypothesis, which showed that neural network pruning could preserve accuracy while reducing the parameter counts of trained networks by over 90% — winning best paper at ICLR 2019.
Jonathan currently works with the OECD to implement the set of AI Principles he helped develop back in 2019. He also previously served as the inaugural Staff Technologist at the Center on Privacy and Technology at Georgetown Law, where he contributed to a landmark report on police use of face recognition technology, and co-developed a course on Computer Programming for Lawyers (earning himself the title “Adjunct Professor of Law”). That course is now an annual offering at Georgetown Law, with more than 15% of all Georgetown JDs taking the class before they graduate.
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