Distributed Learning: A Primer

Behind the algorithms that make Machine Learning models bigger, better, and faster

Image generated with Stable Diffusion

Distributed learning is one of the most critical components in the ML stack of modern tech companies: by parallelizing over a large number of machines, one can train bigger models on more data faster, unlocking higher-quality production models with more rapid iteration…