The introduction of the newest AI model from a Chinese firm — Moonshot AI’s Kimi — has sparked renewed discussions about American competitiveness and the contrast between open and proprietary AI.

While social media has seen abundant discourse, it appears this conversation is also taking place behind closed doors in Washington, D.C., where OpenAI and Anthropic have allegedly lobbied policymakers regarding concerns over open Chinese models.

In the recent episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I deliberated why this issue seems to provoke such strong reactions. Beyond the idea that some individuals should “touch grass” instead of spending weekends debating on X, Sean highlighted that, in many respects, this “feels like we’re witnessing echoes of past anxieties,” with many in Silicon Valley “anticipating that something is about to emerge and overshadow everything else.”

Kirsten observed that imposing strict limitations on Chinese AI models might primarily serve the interests of a select few companies: “Are we promoting and ensuring that Americans prevail in the AI race, or are we guaranteeing that specific frontier labs outperform others?

Continue reading for a snippet of our discussion, modified for brevity and clarity.

Anthony Ha: For those who have kept track of the conversations around Chinese AI, this will likely seem very familiar from the launch of DeepSeek, where essentially a Chinese model is released; on certain benchmarks, it appears to perform comparably with some of the frontier models; and a segment of the tech industry goes into a frenzy. 

Some of this [debate] received additional attention because one of the individuals commenting about it was [an executive] at OpenAI. However, there [is] this persistent question of: Can Chinese firms surpass US firms, at least in some facets, and do so much more affordably and transparently?

Sean O’Kane: Indeed, many aspects of this feel reminiscent of previous crises. One of my favorite instances is: Everyone is so prepared for and expects that something is going to emerge and overshadow everything else. My favorite illustration from this past week was people revealing that “Wow, Kimi completed an entire replication of macOS in 30 minutes.” Sure, it produced an impressive graphical imitation of macOS, but it’s not an operating system.

We continually see these occurrences where everyone in the tech sector is so on edge. Particularly with some of the Chinese models that surface, there’s this anticipation, and I think this gets to the heart of why people reacted so strongly last weekend. (Also, by the way: Go outside, connect with nature, it’s the weekend. Everyone in the industry was exchanging jabs on Twitter all weekend.) But this restlessness is quite intriguing to me because, a week later, I don’t sense that anyone is feeling as dire as they did a week ago.

Kirsten Korosec: We have an excellent piece by one of our reporters, Tim Fernholz, who endeavors to unpack the frenzy surrounding this in the United States. He identifies several factors, ultimately concluding — and I don’t want to preempt his conclusion, but I suspect one stands out more than others. 

There are worries that these Chinese open weight models may possess an inherent bias towards China, alongside other concerns regarding security and safeguards. However, a significant concept here is protectionism, and who is going to metaphorically “win the race”? Will it be the US or China? This appears to be fueling much of the anxiety. 

I’m curious if you concur with that, Anthony?

Anthony: I completely concur. I think the China element invariably injects a certain degree of hysteria. And I’m not implying that people shouldn’t be wary of how the U.S. measures up against China across various sectors. But the panic elevates so quickly.

This also reminds me of the discussions surrounding TikTok a few years back. It’s not that I believed the concerns surrounding TikTok were entirely unfounded, but the extent of the alarm was striking — it appears that as soon as the term China is added to any dialogue, the intensity escalates dramatically.  Moreover, in this instance, it’s tied to discussions about open [weights] and the notion that AI is so potent and potentially hazardous that the only way to manage it is through these proprietary models from American frontier firms. 

Naturally, most individuals asserting this [have] motivations behind their claims. David Sacks, who served as the AI czar for the Trump administration [and] now holds a different role within the Trump administration, was vocal on X about how, “I can’t believe individuals are opposing data centers, we’re complicating our position, there’s too much regulation.” Hence, it’s a method to advocate for the viewpoints they already hold regarding AI. “If China surpasses us, that’s unimaginable, so you must comply with what I advocate.”

Kirsten: Exactly, and if we were to impose universal bans on Chinese open weight models — I’m not suggesting that there aren’t legitimate concerns here, but let’s consider this scenario. Should we do so, it would favor models developed by OpenAI, for example, and compel businesses to utilize those instead of opting for models like Kimi.

Thus, we must truly ask: Are we promoting and ensuring that Americans outpace others in the AI race, or are we merely ensuring that particular frontier laboratories excel over the others?

Sean: At this juncture, it should be noted that a significant portion of this discussion was sparked by the head of strategic futures at OpenAI, Dean Ball, who was the first to publish an extensive post mentioning some of these apprehensions.

One part of me speculates that the backlash was due to disagreements with what Dean articulated. Another part believes the reaction stemmed from the fact that he simply voiced the concern aloud. He essentially posited that the US should create regulatory FUD — fear, uncertainty, and doubt — and complicate the capacity for these open weight models to compete with the US. [Ball subsequently distanced himself from this argument.]

To me, it seems you can interpret some responses from individuals, like, “You’re not meant to vocalize that, Dean.”