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Comment by ChicagoBoy11 | Hacker News Reader

The whole "hallucination" business always seemed to me to be a marketing masterstroke -- the "wrong" output it produces is in no way more "wrong" or "right" than any other output given how LLMs are fundamentally operate, but we'll brand it in such terms to give the indication that it is a silly occasional blunder rather than an example of a fundamental limitation of the tech.

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Also, it gives the impression that these things are "bugs", which are "fixable"...as opposed to a fundamental part of the technology itself.

The more I use these things, the more I feel like they're I/O modalities, more like GUIs than like search engines or databases.

That's exactly how I like to see LLMs. They are NLUIs, Natural Language User Interfaces.

LLMs can be useful when used as a glorified version of printf and scanf.

I agree that classifying their mistakes as "hallucinations" is marketing masterstroke, but then again, marketing masterstrokes are hallucinations too.

In fact all human perception is merely glorified hallucination. Your brain is cleaning up the fuzzy upside-down noise your eyes are delivering to it, so much that that you can actually hallucinate "words" with meaning on the screen that you see, or that a flower or a person or a painting is "beautiful".

We have an extremely long way to go until LLM hallucinations are better than human hallucinations, and it's disingenuous to treat LLM hallucinations as a bug that can be fixed, instead of a fundamental core feature that's going to take a long time to improve to the human level, and then also admit that humans have a long way to go in evolutionary scales before our own perception isn't as hallucinatory and inaccurate as it is now.

It was only extremely recently in evolutionary scales that we invented science as a way to do that, and despite its problems and limitations and corruptions and detractors, it's worked out so well that it enabled us to invent LLMs, so at least we're moving in the right direction.

At least it's easier and faster for LLMs to evolve than humans, so they have a much better chance of hallucinating less a lot sooner than humans.

It is made to serve humans so pretty obvious what means what in this context. Oh but why not change the context just for the sake of some pedantic argument.

Treating hallucination as an error rather than a fundamental limitation is simply a practical way of thinking. It means that, depending on how it's handled, hallucination can be mitigated and improved upon. Conversely, if it's regarded as a fundamental limitation, it would mean that no matter what you do, it can't be improved, so you'd just have to twiddle your thumbs. But that doesn't align with actual reality.

Treating hallucinations as an error that can be corrected fights against the nature of the technology and is more hype than reality. LLMs are designed to be a bullshit generator and that’s what they are; it is a fundamental limitation. (“Bullshit” here used in the technical sense: not that it’s wrong, but that the truth value of the output is meaningless to the generator.) Thankfully the hype cycle seems to be on the down slope. Think about the term “generative AI” and what the models are meant to do: generate plausible-sounding somewhat creative text. They do that! Mission accomplished. If you think you can apply them outside that limited scope, the burden of proof is on you; skepticism is warranted.

Improving LLM's hallucinations is not a theory, it's a reality right now. In fact, developers do it all the time.

> the burden of proof is on you; skepticism is warranted.

I can prove it. You can test it too, try it: after LLM's answer, say 'please double-check if that answer is true'.

Now that I've proved it, right?

(I'm not saying it's perfect, I'm saying it can be improved. That alone makes it an engineering problem, just like any other engineering problem).

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