3 ms·
That is not correct. LLMs have no inventory of their input datasets. If you give it a billion reviews recommending Malbec, it does not know that many reviews re
by jncfhnb 3y ago
That is not correct. LLMs have no inventory of their input datasets. If you give it a billion reviews recommending Malbec, it does not know that many reviews recommend Malbec. It simply has a very good comprehension of what a Malbec review looks like.
In order to know that many reviews recommend Malbec, it needs to be taught this fact specifically, or infer it from context.
- TekMol 3y agoPrompt: Do more Wikipedia pages mention the word "blue" or do more Wikipedia pages mention the word "Accismus"? ChatGPT: To determine whether more Wikipedia pages mention the word "blue" or the word "Accismus," we can use a simple search on the Wikipedia website. Searching for the term "blue" on Wikipedia yields a large number of results, as the color blue is a common topic across various fields. On the other hand, "Accismus" is a relatively obscure term, and it is less likely to be mentioned in a significant number of Wikipedia pages. Therefore, it is highly probable that more Wikipedia pages mention the word "blue" compared to the word "Accismus."
- jncfhnb 3y agoThat is not relevant to what I said. The model can have knowledge about its corpus or tooling to ask questions about it. But the training process is not a library it can draw upon or answer questions about intrinsically.