Liberal thinker

If the U.S. loses the AI race to China, it will not be because of our immigration policy. 1) China is now an advanced country. Its best & brightest are not as drawn to making a future in the U.S. vs say 20 years ago. 2) American culture is not well suited for the AI race as it is fundamentally anti-academic competition & intellectual elitism. We do not revere STEM talent. Young talented men flock to fields that will reward them -not just financially- but via status, social prestige, respect. In China the STEM geniuses are demi gods, akin to how we treat pro athletes & top influencers. 3) The latter point was the central theme of Vivek Ramaswamy’s infamous Christmas tweet. Yes he should have been more tactful in how he expressed his view but it was indeed a salient one as it pertains to the current Sputnik moment. 4) The Right mistakenly thinks the solution is just “accept more Americans into STEM Phd programs.” But as I alluded to earlier, our best & the brightest don’t want to do it. This thus requires a fundamental reorientation of American culture, one that our society would reject as we are not a Confucian society.

Kimi K3 has received far more love than we expected, and our GPUs are feeling it. Over the past 48 hours, demand has pushed close to the limits of our current capacity. To protect the experience of existing subscribers, we're temporarily pausing new subscriptions and prioritizing compute for current members. Existing subscribed users are not affected. We're adding capacity as fast as we can and will reopen new subscription spots in batches. Going forward, we'll also split membership into two more focused plans: Kimi Membership for Kimi Web, App, and Work; and Kimi Code Membership for coding workflows. This will help us match compute more precisely and keep the experience stable. Thank you for your patience and understanding!

I think there's a lot of confusion and misinformation about Zhilin's visa, H1B lottery, immigration, and why he left the U.S. Zhilin had many opportunities to stay in the U.S. if he wanted to. In fact, I was on an email thread with a senior Apple exec (Tim Cook's reports) asking whether Zhilin would consider joining Apple. I said that he wanted to go back to his homeland. The response was, well, we have an office in Beijing if he'd like to join there. But Zhilin was quite determined to go back and build a startup. I remember him telling me that if he didn't at least try starting his own company, he would regret it for the rest of his life. I respect that, and he was right. Many of my international PhD students do choose to stay in the U.S. Of course the U.S. immigration process can be quite intimidating and uncertain, even for superstar PhD graduates from places like CMU.

kimi’s founder & ceo got his phd at cmu. why didn’t he stay in america?!

kimi’s founder & ceo got his phd at cmu. why didn’t he stay in america?!

kimi’s founder & ceo got his phd at cmu. why didn’t he stay in america?!

Some observations on Kimi: 1. It's a very good model! I don't think its performance can be explained away by distillation or anything like that. In agentic coding sessions, it seems pretty much on par with the best public models of Q1 2026. In my fairly limited use, it also seemed very token hungry. It's not obvious to me that this model is actually that cheap to run. 2. I am personally surprised the Chinese state continues to allow the open sourcing of models this good, given potential risks. To be clear, I *myself* might be fine with models presenting this level of marginal risk being open weight, but I am surprised that China is fine with it. I suspect the reason they are is 75% explained by strategic blindness/lack of AGI-pilledness (the CCP is very Yann Lecun-y in its views of AI). The other 25% or so is their lack of compute for customer inference (making China's open-weight strategy an unintended byproduct of US export controls) and the normal Chinese strategy of aggressive exports. For the companies, as opposed to the government, the decision to open source is partially ideological and partially because they are behind, and they know that very few people would pay for sub-frontier models from China. 3. Open-weight models are inherently decelerationist, and I'm continually surprised to see the so-called "accelerationists" so excited about open-weight models. I suspect the reason they are is that they know open-weight models are effectively ungovernable, and they simply like the overall cloak of ungovernability open-weight models create over the whole of AI. It's not a bad strategy; it reminds me of James Scott's recounting of the hill people in "the art of not being governed." Still, in the end, open-weight models deter further AI capex. 4. One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a "public good" which will ultimately be provided by the state as a kind of "digital public infrastructure." This future strikes me as a dystopian hellscape, but I've never met an open-weight models advocate who doesn't ultimately concede this is where things end. You'd be surprised how many 'accelerationists' lobbied me, while I was in government, to support an eleven or twelve-figure federally funded data center so that startups could train models at a subsidy and then give them away for free. There was no other way for AI to progress, they said. Perhaps this is the logical end state of things. Nonetheless, I find myself surprised to see supposed accelerationists excited about such an outcome. I think many of them just don't know what they're doing. Many accelerationists do not view the creation and serving of frontier models as a legitimate business. 5. I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don't need to "ban open source" (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. "A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models." It needn't be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don't want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There's a happy middle ground here. I'd assume they will do some version of this. 6. It's probably true that open-weight models of this capability make the world a bit more dangerous, but not so much more that you'll really notice. At some point the models will be capable enough that you will notice. "A nonliving, invisible, dangerous, and infinitely self-replicating agent escaped from a Chinese lab," you say? Color me shocked.

Why are Indian companies not developing frontier models? The answer is in economics, not talent. The biggest hurdle for an Indian company trying to develop frontier model is that right from the get go, it has to compete with Anthropic and OpenAI free plans + all Chinese open weight models. Chinese models mostly flourished due to the demand from their domestic market which OpenAI/Anthropic couldn’t meet as they’re unavailable in China. This unmet demand created space for innovation. China knows this story well, but here in India, we like unfettered, globalized free market, and that requires an upstart to compete with established companies from across the world. If India is serious about the AI race, it needs to create a massive guaranteed market for domestic AI or else it’ll be economically irrational for any funder to underwrite a product in a highly competitive, already established market.

Why don't we have the US Department of Recruiting that recruits the best engineers in the world to America? This has never made sense to me. Do we want to win or not?

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