Episode 13: Jonathan Frankle, MIT, on the lottery ticket hypothesis and the science of deep learning

Jonathan Frankle (Google Scholar) (Website) is finishing his PhD at MIT, advised by Michael Carbin. His main research interest is using experimental methods to understand the behavior of neural networks. His current work focuses on finding sparse, trainable neural networks. **Highlights from our conversation:**  🕸  "Why is sparsity everywhere? This isn't an accident." 🤖  "If I gave you 500 GPUs, could you actually keep those GPUs busy?" 📊  "In general, I think we have a crisis of science in ML."