[allears]

Of course they're here to stay. LLMs aren't designed to tell the truth, or to be able to separate fact from fiction. How could they, given that their training data includes both, and there's no "understanding" there in the first place? Naturally, the most straightforward solution is to redefine "intelligence" and "truth," and they're working on that.

[kazinator]

Even if training data contains nothing but truths, you cannot always numerically interpolate among truths.

[nickpsecurity]

Our brain does it better. That tells you AI models could do it better. I'll note five things the brain has or might which helps:

1. Information is often grounded in the senses whichh process real data. The brain can tell if new data is like what's actually real.

2. The brain has a multi-part, memory subsystem that's tied into its other subsystems. Only a few, artificial architectures had both neural networks and a memory system. One claims low hallucinations.

3. There's a part of the brain that's damaged in many delusional people. It might be an anti-hallucination mechanism.

4. We learn to trust specific people, like our parents, early on. Then, we believe more strongly what they teach us than what random people say.

5. We have some ability to focus on and integrate the information that's more important to us. We let go of or barely use the rest.

I think hallucinations are the weaknesses of man's architectural choices. Some might be built into the pretraining data. We wont know until the artificial, neural networks achieve parity in features I mentioned to God's neural network. The remaining differences in performance might be pretraining or other missing features.

[rsynnott]

> Our brain does it better. That tells you AI models could do it better.

... I mean, this is likely strictly true, if you define 'AI model' to mean 'any conceivable AI model'. If you're talking about LLMs, though, it's not a reasonable conclusion; LLMs do not work at all like a human brain. LLM 'hallucinations' are nothing like human hallucinations, and the term is really very unhelpful.

[nickpsecurity]

Have you seen what a human subsystem, like the visual context, does when it operates without a memory and without what mitigates hallucinations? If not, how could you make the claim that they don't similarly make false predictions? Or have preventable error in internal models?

You're right that they don't work like the brain, though.

[etaioinshrdlu]

The creators are definitely trying to make them tell the truth. They optimize for benchmarks where truthful answering gets a higher score. All the big LLM vendors now have APIs that can ground their answers in search results.

Just because it's a hard unsolved problem, I don't understand the impulse to assert the AI industry is on a war with truth!