I have to agree with the parent. LLMs are excellent at a large range of NLP tasks. Of course they are not going to replace all ML models, but when it comes to NLP they are clearly better than lots of trained models (e.g. https://arxiv.org/pdf/2310.18025).
LLMs are general purpose tools and absolutely are not better than trained models (using the latest techniques) for a specific task. I mean, that's obviously true if you think about it.
You can use similar datasets and the latest model architectures and if you train a model purely for sentiment analysis it will be better than frontier general purpose LLMs for sentiment analysis.
It's really mind-boggling that so many people disagree via downvotes that you compare models and choose the best performing one, independent of the hype ...
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I have to agree with the parent. LLMs are excellent at a large range of NLP tasks. Of course they are not going to replace all ML models, but when it comes to NLP they are clearly better than lots of trained models (e.g. https://arxiv.org/pdf/2310.18025).
LLMs are general purpose tools and absolutely are not better than trained models (using the latest techniques) for a specific task. I mean, that's obviously true if you think about it.
You can use similar datasets and the latest model architectures and if you train a model purely for sentiment analysis it will be better than frontier general purpose LLMs for sentiment analysis.
It's really mind-boggling that so many people disagree via downvotes that you compare models and choose the best performing one, independent of the hype ...