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f_max t1_j3eagrm wrote

Reply to comment by singularpanda in [D] Will NLP Researchers Lose Our Jobs after ChatGPT? by singularpanda

Right. So if you’d rather not shoot to join a big company, there’s still work that can be done in academia with say a single A100. Might be a bit constrained at pushing the bleeding edge of capability. But there’s much to do to characterize LLMs. They’re black boxes we don’t understand in a bigger way than maybe any previous machine learning model.

Edit: there are also open source weights for gpt3 type models w similar performance. Ie huggingface BLOOM or Meta OPT.

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singularpanda OP t1_j3elwu4 wrote

Seems recently, not too much paper are doing on them. Don't look at details. Maybe models like OPT is still too large?

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f_max t1_j3frqfb wrote

They have a sequence of models ranging from 6B params up to 175B largest, so you can work on smaller variants if you don’t have gpus. There’s def some papers working on inference efficiency and benchmarking their failure modes if you look around.

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Think_Olive_1000 t1_j3tnkld wrote

Dude that's why you ought to put everything into NLP find a way of producing better results for cheaper on less expensive hardware and you'll be the talk of the town. I think everyone would love to have an unrestricted local version of chatgpt on their phones. Do the research!

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