4 ms·
Impressive feat. Honest question though — What are the reasons to pay attention to BERT, when there is GPT4 for various use cases? Does it come down to cost, la
by d4rkp4ttern 3y ago
Impressive feat. Honest question though —
What are the reasons to pay attention to BERT, when there is GPT4 for various use cases? Does it come down to cost, latency and privacy (vs using OpenAI API)?
Genuinely curious, if I am missing a compelling use case outside of those reasons.
- simonw 3y agoIf we want to learn to build something better than GPT-4, research that shows how to train older models like BERT using a fraction of the hardware that was used when that model was originally training is enormously valuable.
- d4rkp4ttern 3y agoOk yes totally agreed!
- rolisz 3y agoBERT is 500x smaller than GPT3, it doesn't hallucinate (it might make wrong predictions, but it won't make unexpectedly wrong predictions), it can run on a CPU in 500ms. I really like BERT style models (there are a couple newer models that better than BERT but are very similar)
- d4rkp4ttern 3y agoThis very interesting to know, thank you. I know there are some frameworks to easily switch between closed and open/local models, so I will have to compare how this does vs GPT-4
- rolisz 3y agoBERT is not a generative model (you might be able to force it to do that, but that's not what it's meant for). It's good for text classification tasks, for named entity recognition and other tasks like this