Google rolled out AI overviews across the United States this month, exposing its flagship product to the hallucinations of large language models.

  • @[email protected]
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    17 months ago

    I understand the gist but I don’t mean that it’s actively like looking up facts. I mean that it is using bad information to give a result (as in the information it was trained on says 1+1 =5 and so it is giving that result because that’s what the training data had as a result. The hallucinations as they are called by the people studying them aren’t that. They are when the training data doesn’t have an answer for 1+1 so then the LLM can’t do math to say that the next likely word is 2. So it doesn’t have a result at all but it is programmed to give a result so it gives nonsense.

    • Balder
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      7 months ago

      Yeah, I think the problem is really that language is ambiguous and the LLMs can get confused about certain features of it.

      For example, I often ask different models when was the Go programming language created just to compare them. Some say 2007 most of the time and some say 2009 — which isn’t all that wrong, as 2009 is when it was officially announced.

      This gives me a hint that LLMs can mix up things that are “close enough” to the concept we’re looking for.