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Comment by bayindirh

6 hours ago

It's already being trained on "public" (ethical or otherwise) data. So, it already has ingested that kind of "optimization" during pre-training and training.

I don't think you can fine-tune your way out of it.

People still think these things are smart. That if their word generator eats enough of the Internet, it will somehow give them the real information that's otherwise hidden. Or perhaps a better word; filter the bullshit.

To filter bullshit it would first have to understand bullshit, and it doesn't. That's why an LLM will tell you the solution to a problem that doesn't work, and argue with you when you correct it.

  • This is what bothers me a lot. For the people who doesn't know how it's made or want to believe, it's a miracle.

    For me, it's a resource wasting text generator. I'll not lie, I don't use OpenAI, Mistral or Anthropic's models, even for coding. I prefer to read my API docs and cry once.

    I used Gemini, five or six times in total. Twice I asked a couple of very specific things, and it unearthed them. Since they were not products, but information, that was helpful. Twice, it has given wrong information. When I "told" it, there was another way, it said "of course there are two ways", etc. Tasteless and time wasting.

    I don't like using an LLM all day long, or offload my thinking to them. It's the ultimate self-poisoning incident.

    And as you say, these algorithms can't know right/wrong/logical/bullshit, etc. They just spew out text.

    • Something I’ve also seen multiple times is an LLM giving wrong information, I tell it it’s not right, then it tells me I’m “absolutely right” and it provides the exact same answer and tells me that one will work.

This is far from widespread at the moment, so it'll be possible to at least use the current cutting-edge models locally in the future.