An AI leaderboard suggests the newest reasoning models used in chatbots are producing less accurate results because of higher hallucination rates. Experts say the problem is bigger than that
I can’t find any backing for the claim in the title “and they’re here to stay”. I think that’s just made up. Truth is, we found two ways which don’t work. And that’s making them larger and “think”. But that doesn’t really rule out anything. I agree that that’s a huge issue for AI applications. And so far we weren’t able to tackle it.
I get that. We want them to be creative and make up an eMail for us. Though I don’t think there is any fundamental barrier preventing us from guiding LLMs. Can’t we just make it aware whether the current task is reciting Wikipedia or creative storywriting? Or whether it’s supposed to focus on the input text or its background knowledge? Currently we don’t. But I don’t see how that would be theoretically impossible.
Isn’t that the two big strings to the bow of LLM development these days? If those don’t work, how isn’t it the case that hallucinations “are here to stay”?
Sure, it might theoretically happen that some new trick is devised that fixes the issue, and I’m sure that will happen eventually, but there’s no promise of it being anytime even remotely soon.
I’m not a machine learning expert at all. But I’d say we’re not set on the transformer architecture. Maybe just invent a different architecture which isn’t subject to that? Or maybe specifically factor this in. Isn’t the way we currently train LLM base models to just feed in all text they can get? From Wikipedia and research papers to all fictional books from Anna’s archive and weird Reddit and internet talk? I wouldn’t be surprised if they start to make things up since we train them on factual information and fiction and creative writing without any distinction… Maybe we should add something to the architecture to make it aware of the factuality of text, and guide this… Or: I’ve skimmed some papers a year or so ago, where they had a look at the activations. Maybe do some more research what parts of an LLM are concerned with “creativity” or “factuality” and expose that to the user. Or study how hallucinations work internally and then try to isolate this so it can be handled accordingly?
I can’t find any backing for the claim in the title “and they’re here to stay”. I think that’s just made up. Truth is, we found two ways which don’t work. And that’s making them larger and “think”. But that doesn’t really rule out anything. I agree that that’s a huge issue for AI applications. And so far we weren’t able to tackle it.
They don’t think. They use statistical models on massive data sets to achieve the statistically average result from the data set.
In order to have increased creativity, you need to increase the likelihood of it randomly inserting things outside that result: hallucinations.
You cannot have a creative “AI” without them with the current fundamental design.
I get that. We want them to be creative and make up an eMail for us. Though I don’t think there is any fundamental barrier preventing us from guiding LLMs. Can’t we just make it aware whether the current task is reciting Wikipedia or creative storywriting? Or whether it’s supposed to focus on the input text or its background knowledge? Currently we don’t. But I don’t see how that would be theoretically impossible.
Isn’t that the two big strings to the bow of LLM development these days? If those don’t work, how isn’t it the case that hallucinations “are here to stay”?
Sure, it might theoretically happen that some new trick is devised that fixes the issue, and I’m sure that will happen eventually, but there’s no promise of it being anytime even remotely soon.
I’m not a machine learning expert at all. But I’d say we’re not set on the transformer architecture. Maybe just invent a different architecture which isn’t subject to that? Or maybe specifically factor this in. Isn’t the way we currently train LLM base models to just feed in all text they can get? From Wikipedia and research papers to all fictional books from Anna’s archive and weird Reddit and internet talk? I wouldn’t be surprised if they start to make things up since we train them on factual information and fiction and creative writing without any distinction… Maybe we should add something to the architecture to make it aware of the factuality of text, and guide this… Or: I’ve skimmed some papers a year or so ago, where they had a look at the activations. Maybe do some more research what parts of an LLM are concerned with “creativity” or “factuality” and expose that to the user. Or study how hallucinations work internally and then try to isolate this so it can be handled accordingly?