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

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

  • @[email protected]English
    1•6 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.

    • BalderEnglish
      2•6 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.