Diverse ML Perspectives
Tim, Max, and Sarah discuss the divide in machine learning philosophies, from the focus on massive compute and data to the importance of building better models with strong priors. They delve into the inefficiencies of neural networks and the need to optimize for the long tail of data distribution.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Sara Hooker - The Hardware Lottery, Sparsity and Fairness
Related Questions
What are the limitations of deep learning according to François Chollet's book as mentioned by Tim Scarfe in the episode #51 Francois Chollet - Intelligence and Generalisation and the clip Francois Cholet's Influence?
What are the limitations of deep learning according to François Chollet's book as mentioned by Tim Scarfe in the episode #51 Francois Chollet - Intelligence and Generalisation and the clip Francois Chollet's Influence?