Re:Why the deep learning boom caught almost everyone by surp...
by valzam on Thursday November 07, 2024 @01:34AM
(#42074043)
When it comes to ML there is no such distinction though. Bigger models == more capable models and for bigger models you need scalability of the algorithm. It's like asking if going to 2nm fabs has any benefit other than putting more transistors in a chip. It's the entire point.
I though the main insights were embeddings, positional encoding and shortcuts through layers to improve back propagation.