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LLMs are conversation engines (hopefully that’s not controversial).
Imagine if Google was a conversation engine instead of a search engine. You could enter your query and it would essentially describe, in conversation to you, the first search result. It would basically be like searching Google and using the “I’m feeling lucky” button all the time.
Google, even in its best days, would be a horrible search engine by the “I’m feeling lucky” standard, assuming you wanted an accurate result and accurate means “the system understood me and provided real information useful to me”. Google instead return(ed)s(?) millions or billions of results in response to your query, and we’ve become accustomed to finding what we want within the first 10 results back or, we tweak the search.
I don’t know if LLMs are really less accurate than a search engine from that standpoint. They “know” many things, but a lot of it needs to be verified. It might not be right on the first or 2nd pass. It might require tweaking your parameters to get better output. It has billions of parameters but regresses to some common mean.
If an LLM returned results back like a search engine instead of a conversation engine, I guess I mean it might return billions of results and probably most of them would be nonsense (but generally easily human-detectable) and you’d probably still get what you want within the first 10 results, or you’d tweak your parameters.
(Accordingly I don’t really see LLMs saving all that much practical time either since they can process data differently and parse requests differently but the need to verify their output means that this method still results in a lot of back and forth that we would have had before. It’s just different.)
(BTW this is exactly how Stable Diffusion and Midjourney work if you think of them as searching the latent space of the model and the prompt as the search query.)
edit: oh look, a troll appeared and immediately disappeared. nothing of value was lost.
What a load of BS hahahaha. LLMs are not conversation engines (wtf is that lol, more PR bullshit hahahaha). LLMs are just statistical autocomplete machine. Literally, they just predict the next token based on previous tokens and their training data. Stop trying to make them more than they are.
You can make them autocomplete a conversation and use them as chatbots, but they are not designed to be conversation engines hahahaha. You literally have to provide everything in the conversation, including the LLM previous outputs to the LLM, to get them to autocomplete a coherent conversation. And it's just coherent if you only care about shape. When you care about content they are pathetically wrong all the time. It's just a hack to create smoke and mirrors, and it only works because humans are great at anthropomorphizing machines, and objects, and ...
Then you go to compare chatgpt to literally the worst search feature in google. Like, have you ever met someone using the I'm feeling lucky button in Google in the last 10 years? Don't get me wrong, fuck google and their abysmal search quality. But chatgpt is not even close to be comparable to that, which is pathetic.
And then you handwave the real issue with these stupid models when it comes to search results. Like getting 10 or so equally convincing, equally good looking, equally full of bullshit answers from an LLM is equivalent to getting 10 links in a search engine hahahaha. Come on man, the way I filter the search engine results is by reputation of the linked sites, by looking at the content surrounding the "matched" text that google/bing/whatever shows, etc. None of that is available in an LLM output. You would just get 10 equally plausible answers, good luck telling them apart.
I'm stopping here, but jesus christ. What a bunch of BS you are saying.