2 ms·
Yeah I think you couldn't train GPT-3 on this. You need something incredibly compute and memory bandwidth intensive, but with relatively few parameters. But the
by modeless 6y ago
Yeah I think you couldn't train GPT-3 on this. You need something incredibly compute and memory bandwidth intensive, but with relatively few parameters. But there ought to be some interesting architectures to discover in that direction. If nothing else you could do crazy fast hyperparameter optimization on smaller architectures and get much better performance out of them.
The architectures we have are shaped by the hardware they run on, I think more than people realize. Different hardware will need different architectures to be fully utilized. Unfortunately there are so few of these chips in existence that it will be hard to get enough people using them to really discover how to best use them.
- mark_l_watson 6y agoI agree, but consider this: there will hopefully be a new paradigm that uses fewer parameters but some mechanism like transfer learning to allow more modular training and composition of models. In an old job, I wrote many US patents and if I still worked there, then I would persue this idea. Now, I am just throwing this idea up in the air hoping it may be useful.