OpenAI's Science Chief Says LLMs Aren't Ready For Novel Discoveries and That's Fine (technologyreview.com)
- Reference: 0180665220
- News link: https://science.slashdot.org/story/26/01/27/1514246/openais-science-chief-says-llms-arent-ready-for-novel-discoveries-and-thats-fine
- Source link: https://www.technologyreview.com/2026/01/26/1131728/inside-openais-big-play-for-science/
UC Berkeley statistician Nikita Zhivotovskiy, who has used LLMs since the first ChatGPT, told the publication: "So far, they seem to mainly combine existing results, sometimes incorrectly, rather than produce genuinely new approaches."
"I don't think models are there yet," Weil admitted. "Maybe they'll get there. I'm optimistic that they will." The models excel at surfacing forgotten solutions and finding connections across fields, but Weil says the bar for accelerating science doesn't require "Einstein-level reimagining of an entire field."
GPT-5 has read substantially every paper written in the last 30 years, he says, and can bring together analogies from unrelated disciplines. That accumulation of existing knowledge -- helping scientists avoid struggling on problems already solved -- is itself an acceleration.
[1] https://www.technologyreview.com/2026/01/26/1131728/inside-openais-big-play-for-science/
A moment of honesty (Score:2)
Among so much hype, I almost can't believe he said the quiet part out loud: LLMs are not thinking creatures.
Any bets on if he keeps his job?
Re: (Score:2)
> Among so much hype, I almost can't believe he said the quiet part out loud: LLMs are not thinking creatures.
> Any bets on if he keeps his job?
He covered his ass. Further in he said he's pretty confident they'll get there, they just aren't there yet.
This is more a rippling pebble in the stream of bullshit, not a diversion.
Nope (Score:2)
[1]https://www.wired.com/story/ai... [wired.com]
TL:DR: the math shows they *can't* go beyond a certain complexity.
[1] https://www.wired.com/story/ai-agents-math-doesnt-add-up/
LLM's are prediction machines (Score:2)
They are a 'magic' mathematical box that will give you the most probable output based off of inputs that they have already seen. If they haven't seen something or something like it they aren't going to give you that output.
The real problem with the industry is they are working with a 'black box' that gives you output's from inputs, but they don't really know what is going on inside. Yes they are finding out more and more, but if you don't know how an engine works you certainly aren't going to be able to des
Re: (Score:1)
100% - LLMs don't do cognition and they never will. You can train a dog to sniff out drugs or fetch the paper - that doesn't mean it understands what drugs or papers are. LLMs will never understand cause and effect or be able to do human cognition things like apply knowledge from one context to another by mapping concepts - that's not what they do and it never will be. The tech fundamentally cannot do those things. I can't wait for the C-Suites to catch up so this "useless AI in everything" era can come to
Re: (Score:2)
I think the best outcome is to wait until the C-Suites are replaced by LLMs, they''ll be dragged screaming and kicking to the door: "B....B....But you need me!, who will bullshit the investors like we do." Whereupon, the Bullshit Bot will finally be revealed as a component of the LLM C-Executive Team.
A little while later, the investors will realize they've been had and drag the LLM C-Executive Team screaming and kicking to the door: "B....B....But you need me!, who will bullshit the investors like we do." W
Re: (Score:2)
Indeed. What is hilarious is that, apparently, many people are suffering from similar issues and cannot actually put the "general" in general intelligence in whatever thinking they are capable of. And hence the hype continues, despite very clear evidence that it cannot deliver.
As to "AGI", that is a "never" for LLMs. The approach cannot do it. We still have no credible practical mathematical models how AGI could be done.
I would submit that automated theorem proving or automated deduction (basically the same
Goalposts (Score:2)
Way over there somewhere
Re: (Score:2)
Obviously. Anything and any lie to keep the hype going.
This is a lie by misdirection. And he knows it. (Score:2)
The actual reality is that LLMs are not _capable_ of "novel" discoveries. All they can do, occasionally, is find something were everything is known, but there is a simplistic step missing to connect things. And that is it.
What this dishonest asshole implies is that this will change and LLMs may well get that capability. That will not happen. The Math used does not allow it.
Summary doesn't match TFA (Score:2)
The summary is missing some pretty important words in TFA. Here's the context of where he said the models aren't there yet:
> He plays down the idea that LLMs are about to come up with a game-changing new discovery. “I don’t think models are there yet,” he says. “Maybe they’ll get there. I’m optimistic that they will.” But, he insists, that’s not the mission: “Our mission is to accelerate science. And I don’t think the bar for the acceleration of science is, like, Einstein-level reimagining of an entire field.”
Notice the important part before the sentence; he's talking about "game-changing new discovery" not regular nuts and bolts of scientific work. And in at least some fields, we are seeing these used to accelerate work. He talks about in the article a bit. The article correctly notes that there's been inaccurate hype from his group in the past, including claiming to have solved open math p
Who deserves the credit? Who deserves the blame? (Score:2)
Okay, great. Have they told the marketing department?