Welcome to Eye on AI. Beatrice Nolan here. In today’s issue:
- Some people think OpenAI’s Hugging Face hack is a PR stunt.
- White House accuses Moonshot of distilling Anthropic’s Fable.
- Alphabet profit quadruples on AI gains, but cash vaporizes.
- And investors say Kimi K3 might just be another “DeepSeek moment.”
OpenAI has found itself at the center of a viral news story.
In an incident some news commentators are likening to the plot of the 1984 film The Terminator, two of OpenAI’s AI models broke out of a supervised test, got themselves online, and used that access to hack into rival company Hugging Face’s systems. Notably, OpenAI says the models weren’t being malicious; instead, they were just trying to complete a task they had been given and found a way to cheat. Both companies say they’ve since worked together to fix the security holes involved.
For safety researchers, the incident was one of the clearest examples of the risks they’d spent years warning about. But for others, it was suspiciously “good” PR for OpenAI.
To be clear, there is no evidence that the incident was fake. Hugging Face also confirmed the hack was real, and both companies published a report on the incident.
Still, social media was rife with theories about the hack being OpenAI’s attempt to get its “Mythos” moment. Even many within the AI industry responded with a collective eye-roll. “The entire blog piece reads as a marketing gimmick that OAI ripped off from Anthropic,” one X user wrote.
“Not sure if this is by far the most significant real-world AI safety event to date, or by far the most cynical marketing stunt I’ve seen in a while,” another AI researcher wrote on LinkedIn. Several engineers within Big Tech companies I’ve spoken with also told me their first instinct was to assume the hack was some kind of advertising.
While it’s true that the hack did generate global headlines, crashing a rival company’s servers is not typically considered good marketing. However, critics have charged leading AI firms with engaging in this kind of “dark marketing” for years. From warnings that AI could wipe out entire categories of jobs, to Anthropic’s own decision to withhold Mythos from public release because it was “too dangerous,” to claims from lab leaders that out-of-control models might just kill everyone on the planet, the very companies selling AI have also been among the loudest warning about AI’s many dangers.
While some of these concerns may be legitimate, it’s also been a good way to stir up headlines and keep attention on their products. Others argue that it’s also been a way for leading tech companies to exert more control over advanced AI development by arguing that models are becoming so dangerous that only a select few should be trusted with them.
However, the public and the industry seem to have wised up to this strategy. AI labs now appear to be in a situation where they have spent so long playing up doomsday scenarios and warning that their own models are so dangerously powerful that when something genuinely alarming happens, the instinct from a lot of people is to assume it’s spin.
“I see a lot of people saying this must be not completely true, there’s some lies, or just a PR stunt,” Charlie Eriksen, a security researcher at Aikido Security, told me. “That suggests the frontier labs are inherently untrustworthy, as it makes no sense that they’d make up stuff without any clear sensible incentive in this case.”
Who’s checking the labs’ homework?
This lack of trust presents a problem because a lot of what the industry knows about AI safety and performance comes from the labs themselves. Models are typically deployed internally first and tested by safety teams before they are released. If nobody believes these companies when real dangers emerge, or worse, if they genuinely can’t be trusted, it limits what governments, business, and the public know about potentially dangerous models in development.
One issue pointed out by safety experts is that there’s no way to independently verify claims of things happening with the labs. Labs don’t have to hand over incident logs or submit to any kind of independent audit to prove that what they say about their models’ capabilities is actually true.
In this case, it is also convenient that this whole episode hypes up perceptions of OpenAI’s models, especially the still-unreleased one that might become GPT-6 if the rumors are right, while also giving Hugging Face a chance to push its own case for more powerful, American-made open source in the hands of defenders. It’s a win-win for two companies that, on paper, have opposite incentives. None of this is to say it’s fake, but it’s also true that there’s no way to rule it out, which is its own problem.
Ultimately, there’s no question that AI models can go rogue in this way—this week proved that much, and there have been similar examples of this kind of misalignment before. But what this has shown is that the labs building them have eroded the public’s ability to take their word for it, even when they’re telling the truth, and that might just be a bigger issue.
With that, here’s more AI news.
Beatrice Nolan
beatrice.nolan@fortune.com
@beafreyanolan
This story was originally featured on Fortune.com
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