Modeling Data Growth
David discusses the concept of models that adapt and grow with data, touching on the challenges faced in merging NP Bayes models with modern GPU hardware. He explores the idea of squeezing maximum information from each data point without sacrificing scalability, drawing parallels to past neural network concepts that struggled to gain traction.In this clip
From this podcast
The Gradient
David Pfau: Manifold Factorization and AI for Science
Related Questions