Vox reports that o3 weights have been transported in a suitcase to an air-gapped supercomputer to help with nuclear weapons research.
This has seemingly gone unnoticed in the broader AI safety community.
Although I do not know how to update based on Vox’s article, it seems like information that more people should know because it is important information about the integration of (frontier) AI into the US military.
At least some of the people who work there do not seem concerned with catastrophic AI risk.
Relevant quotes from when the journalist Joshua Keating was there in January this year:
Geoff Fairchild, deputy director for the National Security AI Office, volunteered that he does not have a “p(doom),” the Silicon Valley shorthand for how likely one believes it is that AI will lead to globally catastrophic outcomes, and doesn’t believe most of his colleagues do either. “We don’t talk about [p(doom)]. I don’t think I’ve ever had that conversation,” he added.
AI risk does not have a good reputation it seems:
Lang felt it was a mistake to characterize AI as a weapon, or frame development as an arms race, with China the main competitor this time instead of Germany. He preferred to think of today’s research as continuing the Manhattan Project’s model of “giving a bunch of multidisciplined scientists a goal to really go after and try to make progress on.” Others pointed to the scientists who were concerned at the time about the risk of a nuclear explosion igniting the earth’s atmosphere as somewhat equivalent to today’s AI “doomers.”
Side note: it seems odd to imply the motivation for the Manhattan project was not started as a race.
Here are further quotes that I found interesting (emphasis mine)
This should allow you to get most of the information without reading the full article.
Last May, [an] OpenAI representative, accompanied by armed security, arrived at Los Alamos bearing locked metal briefcases containing the “model weights” — the parameters used by AI systems to process training data — for its ChatGPT 03[sic] model, for installation on Venado.
People seem to like it:
Grider says demand for the new tool was immediately overwhelming. “I was surprised how fast people became dependent on it,” he told me.
More integration is coming up:
Initially, the system was used for a wide array of scientific research, but in August, Venado was moved onto a secure network so it could be used on weapons research, in the hope that it can become an invaluable part of the effort to maintain America’s nuclear arsenal.
What the supercomputer does:
Venado is effectively a massive simulation machine to test how a weapon would respond to being put under unique forms of stress in real-world conditions.
What o3 might actually be working on:
“Could we make a new high explosive that is less reactive, so you can drop it, and nothing happens? [Or] that’s not made with toxic chemicals, so people handling it would be safer from exposures? We can go through and look at some of the components of our nuclear deterrence, and see how we can make it cheaper to manufacture, easier to manufacture, safer to manufacture.”
Tool-framing of AI:
For Alex Scheinker, a physicist who uses AI for the maintenance and operation of LANL’s massive particle accelerator, AI is an extraordinarily useful tool, but a tool nonetheless. “It’s just more math,” he said. “I don’t like to think about it like it’s magic.”
Although the majority of the budget is for weapons research, other research happens too:
Officials at Los Alamos are quick to point out that despite what the lab is best known for, scientists there are working on more than just weapons of mass destruction. During my tour, I met with chemists using AI to design new targeted radiation therapies to improve cancer treatment and visited the Los Alamos Neutron Science Center, a kilometer-long particle accelerator that, in addition to weapons research, produces isotopes for medical research and pure physics experiments.
More AI is coming to the US military:
When the decision was made to move Venado onto a secure network, it cut off a number of ongoing scientific research projects, which is one big reason why two new supercomputers, known as Mission and Vision, are planned to debut this summer. Both are designed specifically for AI applications — one for weapons research, one for less classified scientific work.
Thanks to Bronson Schoen for sharing the article with me, and Alex Lloyd for feedback.
FWIW LANL’s nuclear weapons work nowadays primarily lies in ”stockpile stewardship” or basically running simulations of how weapons / material stockpiles might degrade over time, and what maintenance needs to be done.
And it seems somewhat unlikely that o3 is powerful enough to take it over in an evil way?
Is your concern more about the principle? Like this seems awfully convenient if there’s some super powerful model in the near future that’s given access?
I agree that o3 is unlikely to cause catastrophy. I think mostly the point regarding the integration of AI into the military is interesting + the attitudes of staff.
It seems to me that having specific versions of eg Claude/GPT integrated into the US military is maybe an especially easy way for AI to gain a lot of power.
Wow that’s scary. Not even for any loss-of-control risks, but because of o3′s catastrophic willingness to bluff about almost anything. I hope it was only ever used for verifiable tasks...
I would expect most of the relevant information to be classified. If there’s a public accounting for like this, we have to ask why people decided to tell the public about it and not just take the facts that are told the public at face value.
The journalists who wrote the article does speak about visiting the lab in January and the article is written is published second of April.
On reason is that the military wanted to renegotiate their contracts about limits where Antrophic had the Exceptions to our Usage Policy:
For example, with carefully selected government entities, we may allow foreign intelligence analysis in accordance with applicable law. All other use restrictions in our Usage Policy, including those prohibiting use for disinformation campaigns, the design or use of weapons, censorship, domestic surveillance, and malicious cyber operations, remain.
Ah dang, guess my proposal to try for a born classified model has already been considered. I’m updating off this that we might not be able to point counterproliferation infrastructure at AI datacenters.
76% of AAAI survey respondents believe scaling current approaches is “unlikely” or “very unlikely” to achieve AGI.
I haven’t seen this AAAI 2025 report + survey posted anywhere. On the survey:
475 respondents, primarily academic (67%) and corporate (19%).
It has some other bits on hype, paradigm diversity, academia’s role, and geopolitical aspects.
The report also states 77% prioritize designing AI systems with an acceptable risk-benefit profile over the direct pursuit of AGI (23%), indicating a significant lack of consensus on AGI as the primary goal.
o3 has been used for nuclear weapons research
Vox reports that o3 weights have been transported in a suitcase to an air-gapped supercomputer to help with nuclear weapons research.
This has seemingly gone unnoticed in the broader AI safety community.
Although I do not know how to update based on Vox’s article, it seems like information that more people should know because it is important information about the integration of (frontier) AI into the US military.
At least some of the people who work there do not seem concerned with catastrophic AI risk.
Relevant quotes from when the journalist Joshua Keating was there in January this year:
AI risk does not have a good reputation it seems:
Side note: it seems odd to imply the motivation for the Manhattan project was not started as a race.
Here are further quotes that I found interesting (emphasis mine)
This should allow you to get most of the information without reading the full article.
People seem to like it:
More integration is coming up:
What the supercomputer does:
What o3 might actually be working on:
Tool-framing of AI:
Although the majority of the budget is for weapons research, other research happens too:
More AI is coming to the US military:
Thanks to Bronson Schoen for sharing the article with me, and Alex Lloyd for feedback.
FWIW LANL’s nuclear weapons work nowadays primarily lies in ”stockpile stewardship” or basically running simulations of how weapons / material stockpiles might degrade over time, and what maintenance needs to be done.
And it seems somewhat unlikely that o3 is powerful enough to take it over in an evil way?
Is your concern more about the principle? Like this seems awfully convenient if there’s some super powerful model in the near future that’s given access?
I agree that o3 is unlikely to cause catastrophy. I think mostly the point regarding the integration of AI into the military is interesting + the attitudes of staff.
It seems to me that having specific versions of eg Claude/GPT integrated into the US military is maybe an especially easy way for AI to gain a lot of power.
Wow that’s scary. Not even for any loss-of-control risks, but because of o3′s catastrophic willingness to bluff about almost anything. I hope it was only ever used for verifiable tasks...
I would expect most of the relevant information to be classified. If there’s a public accounting for like this, we have to ask why people decided to tell the public about it and not just take the facts that are told the public at face value.
The journalists who wrote the article does speak about visiting the lab in January and the article is written is published second of April.
On reason is that the military wanted to renegotiate their contracts about limits where Antrophic had the Exceptions to our Usage Policy:
See my other comment for an article that the Los Alamos facility itself in Jan 2025.
Update: Jenny shared that there is an article from January 2025 on broadly on this topic from the Los Alamos National Laboratory: https://www.lanl.gov/media/news/0130-open-ai
Ah dang, guess my proposal to try for a born classified model has already been considered. I’m updating off this that we might not be able to point counterproliferation infrastructure at AI datacenters.
76% of AAAI survey respondents believe scaling current approaches is “unlikely” or “very unlikely” to achieve AGI.
I haven’t seen this AAAI 2025 report + survey posted anywhere. On the survey: 475 respondents, primarily academic (67%) and corporate (19%).
It has some other bits on hype, paradigm diversity, academia’s role, and geopolitical aspects.
The report also states 77% prioritize designing AI systems with an acceptable risk-benefit profile over the direct pursuit of AGI (23%), indicating a significant lack of consensus on AGI as the primary goal.