A Field Guide to AI Market Freakouts

**Nathaniel Whittemore** (0:01)
Today on the AI Daily Brief, a field guide to AI market freakouts. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Airtable, Retool, and Blitzi. To get an ad-free version of the show, go to patreon.com/aidailybrief, or you can subscribe on Apple Podcasts. To learn more about sponsoring the show, send us a note at sponsors at aidailybrief.ai.
Now, one other quick note, a couple of people have asked me recently if there are better ways that they can support the show. First of all, you listening is all the support I need. I appreciate you being here and diving deep with me in this incredibly fascinating and important AI world. Second, already one of the things that you guys do very frequently, which is incredibly helpful for the show, is just sharing it. For those who don't know, I recently updated the aidailybrief.ai website to turn every episode into a set of shareable cards. Some of them are quotes, some of them are themes, some of them are statistics, and each of them can be shared directly to various social media platforms or as an image that you can put anywhere you want. The most valuable way the show grows is when you share it with new listeners, so that is always appreciated. Lastly, for whatever reason, Apple and Spotify both very highly reward ratings and reviews. So if you have not at this point left a five-star rating on those platforms, that is helpful as well. Mostly though, like I said, I'm just excited to have you here as we explore this insane world. The one other note today is that it was one of those days where even all of the headlines fit inside the main theme. So we just have one extended theme for the entire episode. Tomorrow, we will be back with our normal division between headlines and main. But for now, let's talk about the patternicity in AI market freakouts and what they mean for the future of AI.
Welcome back to the AI Daily Brief. We are in the midst right now of our latest round of AI FUD and concern. Now this one specifically is about Chinese AI and how it might impact the revenue potential of companies like OpenAI and Anthropic, especially as they position to go public later this year or early next year. Having watched this very closely now for the last few years, I think there are some pretty clear patterns in the specific ways in which investors get stressed about AI. And so that's what we're going to talk about today. However, to get into it, we first need to do an update in this particular round of concern as the Trump administration levies new allegations against Moonshot. Earlier this week, Treasury Secretary Scott Besson proposed that Chinese AI companies could face sanctions as a response to distillation attacks. And while model distillation has been a hot topic for over a year when it comes to Chinese model performance, this was the first time a member of the executive suggested the government might do something about it.
Besson doubled down on his policy view on Wednesday, writing in a post on X, We support open source AI and the innovation it unlocks. But open source is not open season on American IP. When PRC firms conduct covert industrial scale distillation attacks that cross the line into IP theft, sanctions and entity list designations will be on the table. Now that post came hours after White House Office of Science and Technology Policy Director Michael Kratzios made specific allegations against Moonshot, the creators of KimiK3, wrote Kratzios, We have information that Moonshot AI distilled Anthropix Fable for the development of its K3 model. To do this, they developed a sophisticated internal platform to conduct large scale distillation against US models, allowing them to quickly switch between multiple methods of access to avoid detection. Moonshot AI has also acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models. The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open source frameworks and open weight models. Legitimate AI distillation used to create smaller, more efficient models plays a vital role in this open innovation ecosystem. However, large scale covert industrial distillation aimed at stealing proprietary US technology and undermining American research is unacceptable.
Now, here once again, while there have long been whispers of Chinese labs getting access to NVIDIA GPUs through illicit pathways across Southeast Asia, this is the first time a government official has made specific claims about the practice. Anthropic head of public policy and former State Department official Sarah Heck confirmed that Anthropic is working with the administration on this matter, with Heck writing, Elicit adversarial distillation is IP theft and industrial espionage that supports adversary military and intelligence capabilities. It is a national challenge that creates serious national security risks for the United States and Democratic allies. Following the posts, the information reported that the Commerce Department has an active investigation into Moonshot and other Chinese labs for circumventing export controls to access NVIDIA GPUs. Signal summed up the feeling of many when they wrote, Wow, am I understanding this correctly? One, put Chinese models on the entity list. Two, force American companies to buy more expensive AI from American labs. Three, watch the rest of the world use cheaper models with equal or better intelligence. Four, discover that distillation did not magically stop because Washington published a list. Five, make American businesses less competitive globally while raising prices for ordinary Americans. Six, meanwhile, none of this stops Chinese AI labs from becoming better and better. Congratulations, you protected domestic AI companies by taxing the competitiveness of the entire country. What a colossal mess.