this post was submitted on 23 May 2024
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Due to the nature of our work, my firm has had early access to most LLMs including Bard (now Gemini). I might be short on imagination but I honestly cannot see how LLM general search implementations can ever be fixed. There is too much garbage data for any system to be able to intelligently parse and the results of our tests were laughable. Now, if you offer LLM search that is restricted to curated datasets like "The Library of Congress" or peer reviewed scientific papers, I can see the value in that. You'll probably still have to triple check your results, but at least it can get you 80% of the way there rather than sending you in the wrong direction.
EDIT: For context, our clientele are all enterprises with very large, mission critical systems. They are not the type to use some buggy trinket just because it's new and cool.
Exactly this. We need to figure out making machines that can reason first and then we can have THEM sort the data and figure out what to feed the data pool.
But if we have a computer that can reason, we don't need LLMs at all.