Mistral AI models, which we're discussing, fall under the category of large language models (LLMs). So, how exactly do these models construct sentences? Essentially, they're trained on massive amounts of text data and predict words based on context. One notable feature is their 'zero-shot' learning capability—they can provide coherent answers on topics they haven't been directly trained on. Given the vast range of data they're trained on, where do you think the limits of such models lie?
How does Mistral AI work?
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Thanks for the enlightening post, bro! I think these "zero-shot" abilities are really interesting—so with such a broad range of data, there are cases where the model just can't generate "solid" answers. For example, I’m curious how sensible a model that knows nothing about a newly released technology could actually be.