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Re:Forget ChatGPT: why researchers now run small AIs on thei... by amelius on Saturday September 21, 2024 @07:35PM (#41613447)
How do we rate whether the smaller models are any good? How many questions do we need to ask it to know that it can be trusted and we didn't waste our time on it?
Re:Forget ChatGPT: why researchers now run small AIs on thei... by mkl on Saturday September 21, 2024 @08:08PM (#41613585)
You should never completely trust any LLM. They all get things wrong, make things up, and have blind spots. They're any good if they help you for some of your particular uses (but may still fail badly for other uses).
Re:Forget ChatGPT: why researchers now run small AIs on thei... by amelius on Saturday September 21, 2024 @09:52PM (#41614058)
I think you didn't understand my question and maybe I phrased it poorly. The problem is not whether we should trust any deep learning model (the answer is indeed no). But the question is how we can find out if a model is any good before investing our time into that model. Each bad reply we get has a price, because it wastes our time. So, how can we compare models objectively without having to try them out ourselves first?
Re:Forget ChatGPT: why researchers now run small AIs on thei... by abdullahkhalids on Saturday September 21, 2024 @10:46PM (#41614273)
There are leaderboards [1] that can provide a rough estimate of the relative capabilities of different models.

[1] https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboar...