OpenAI Puzzled as New Models Show Rising Hallucination Rates
- Reference: 0177063017
- News link: https://slashdot.org/story/25/04/18/2323216/openai-puzzled-as-new-models-show-rising-hallucination-rates
- Source link:
OpenAI says in its technical report that "more research is needed" to understand why hallucinations worsen as reasoning models scale up.
[1] https://slashdot.org/story/25/04/16/1925253/openai-unveils-o3-and-o4-mini-models
[2] https://techcrunch.com/2025/04/18/openais-new-reasoning-ai-models-hallucinate-more/
The line between a genius and a madman is thin. (Score:2)
The AIs have to evolve more and also when they do they end up becoming more prone to the mental diseases humans have.
Re:The line between a genius and a madman is thin. (Score:4, Insightful)
The line is thin when clouded by ambition, greed and incitement.
AI has no intelligence at all. There is science and engineering. The science is still shit, and the engineering is wasted money.
Re: (Score:3)
That's a complete misunderstanding of "AIs" (really language learning models). They don't "evolve". The engineers merely add more hardware and/or tweak the algorithms, often with other priorities than the strength of the model. The models are not responding to any kind of "evolutionary" pressure. If anything they develop in an opposite manner. AI companies introduce more artificial inefficiencies as they respond to market concerns, public pressure, publicity, etc.
It's as if a committee was designing a lion:
Reasoning? (Score:5, Insightful)
Labels that make it sound like it exhibits an intelligence doesn't make so.
All this money is such a waste when the science just isn't there yet. There's no Manhattan Project in the wings when they just have no clue at all.
Re: Reasoning? (Score:5, Insightful)
I don't think there's even currently a valid theory about how AI "reasoning" could possibly one day work as intended. Such a strange investment strategy.
Re: (Score:2)
The reasoning since about a decade ago has been something like "we see jumps in the way this 70s shit works as we increase the size, so whoever hits the smallest size that has true intelligence wins".
And the bet is on reaching that "size" first, because the prize will be "everything".
Anything else is just a distraction.
It is like a Bond movie, really, with villains that are about as moronic and delusional as the cinema characters.
Re: (Score:2)
It already works as intended. The intention of "reasoning" is to get more money. Because "feedback" sounds like old technology.
Just in time to replace all thought workers (Score:2)
It's getting close to human quality with the hallucination rate. I can't wait to not have to work!
plus ca change... (Score:3)
"Don't eat the Brown Acid!"
Re: plus ca change... (Score:2)
What color is a go?
Model Collapse (Score:3)
Today's hallucinations become tomorrow's training set, eventually resulting in model collapse. Supposedly they take measures in their pipeline to mitigate that, but it's obviously not working. Get ready for a different kind of truth.
Re: (Score:2)
This is exactly correct, and it also furnishes a rebuttal against the claim that AI generated "art" is not theft any more than it would be theft for a human to study, learn from, and draw upon the works of other humans. If that were true, these models would not need to be trained on original, real-world data--it could simply train itself. But model collapse is very real, and the desire of companies to steal original content from its creators by any means possible amounts to a tacit admission that the outp
They're ingesting more slop (Score:4, Funny)
We were told what would happen once the models are trained on ai slop... They're going to get worse. The fact that they're puzzled by this means they are charlatans.
Hallucinations are a misnomer (Score:5, Informative)
The idea that LLMs do "hallucinations" as if they were human is silly.
Human "hallucinations" are abnormal occurrences that usually appear as a symptom of something wrong.
AI "hallucinations" are normal. It's the way these systems work. LLM "hallucinations" ARE the mechanism by which sentences are created. It's the "generative" part in "generative models". It's the random choices that have no connection with reality but bridge the likelihood gap to produce plausible interactions. It's the "stochastic" in "stochastic parrot". It's the "interpolation" in "training data interpolation".
The reason the word "hallucination" is used by AI companies and hopeful CS researchers is to make investors think of the human equivalent rather than the AI reality. When an investor thinks that randomly generated AI responses are minor problems that can be fixed in the next version, they are happy to keep investing. When an investor is told these randomly generated AI responses are intrinsic and can never be solved, they start thinking of the risks with retain business models.
Caveat emptor.
Re: (Score:2)
s/retain/certain/
Re: (Score:2)
LOL, starting with AI itself, add it to the ever growing list of inappropriate AI based hype.
Re: (Score:2)
Yes, and using the term both gives AI researchers a bogeyman to blame, an opportunity to imply there is real intelligence, and to grift off of a solution to a problem they have created and don't understand. A hallucination is merely a result that is not liked, it is normal behavior.
Re: (Score:2)
Are AI hallucinations that different than how people misremember things?
Sophisticated models needs a narrative (Score:3, Interesting)
If you don't control the narrative, and outline what's fact and what's fiction, then EVERYTHING can be perceived as fact. It's not a hallucination. It's a byproduct of model censorship without a controlled narrative and established timeline. Something we dealt with at the NSA some 21 years ago.
more fraud (Score:2)
"OpenAI says in its technical report that "more research is needed" to understand why hallucinations worsen as reasoning models scale up."
These people are such frauds. They are the self-proclaimed smartest people in the world yet they have no idea how their own products work AND they release them on the world with gigantic flaws they don't understand, all under the guise of anthropomorphizing deterministic computer software. When will VC wise up?
AI scanning AI, who knew? (Score:3)
It's recursively copied turtles all the way down
Simple (Score:2)
The more complicated the model and the larger the data set, the more false links are created. I would project that a sufficiently large LLM would produce output with virtually 100% inaccuracy.
Under the hood of generative AI are two things (Score:2)
One is a random number generator. The second is a feedback loop wherein the prior output is reingested as "context."
On the very micro scale you can recreate this with a speaker and a microphone. There are places where the speaker will squeal with static and places where it will merely amplify what is spoken into the microphone. Finding the location of the microphone that does the latter is somewhat of a science but since it depends on the geometry of the room a little bit, it's also part art.
This is on the
Been isolated and solved. (Score:1)
Database hallucination is as old as the idea of network application or rather, networks and applications. Data streams sessions just pointed at a network, nowadays just say the web and it's exponentially worse, will always be flakey. At least there is memory safe languages that don't expect anything but random noise across a session...... Wait up.....
Garbage in, garbage out. (Score:2)
Maybe it's not such a good idea to just automatically hoover up 100% of the exposed internet and all user input and feed it all back through the machine on a feedback loop?
Re: (Score:3)
I read an article not long ago, right here on Slashdot, in which some group of "industry experts" who were not financially tied to any of the companies selling AI models stated that, based on their analysis, we have already hit peak AI by current methods. They had some data comparing the quality of the prior gen LLMs to the next gen LLMs that were built at much greater expense over a much huger training set, and found the gains to be marginal.
So this news would seem to accord with their prediction. Just t
Re:Garbage in, garbage out. (Score:4, Insightful)
To try new things most likely requires another AI winter.
The humongous amount of investment into transformers and deep neural nets as well as GPU production has created an ultra specialized infrastructure in both software and hardware. This lets researchers do many things on the margins, as long as they fit into the kind of models that this infrastructure supports.
In this environment, radically new approaches are not going to be tried at anywhere near the rate of conventional approaches aiming for modest epsilon improvements. Furthermore, the investors looking for above average returns will insist on companies exploiting these conventional approaches to the fullest.
Re: (Score:2)
It's not merely diminishing returns, it's shocking regression. Because it's not "artificial intelligence" it's a poorly understood lossy search engine.