many followers have correctly noticed that longtermist moral math doesn't survive an ordinary discount rate.

no macro-technology birthed by the bay area tech industry has been met with more hatred by bay area tech industry elites than frontier ai. many of those elites looked at the technology landscape of 2020/1, scoffed at the labs and their weird little hopes of ‘agi,’ and concluded that cryptocurrency would be the technology of the decade. now their businesses and worldviews are under fundamental threat from what the labs have achieved. they hate it. they beg for the labs to go away, to become commoditized, by America’s enemies if necessary. they’d love to see the US frontier labs immolated by the industrial strategy of America’s principal geostrategic rival, and they declare this proudly and in public. they were wrong about the defining technology of the decade, and now they are scared and they want to destroy the thing they were wrong about. perhaps now they are right and the labs will be rendered insolvent by commodification. I do believe this is possible. nonetheless there is something randian about it all, about their utter disdain for success and achievement and discovery and chutzpah.

The authors state that America should reduce fiscal deficits. This is classic IMF reasoning. I had like to ask: Why does the US run fiscal deficits? b/c the U.S. private sector often desires to net save, and b/c the U.S. absorbs imports from surplus countries - @TheEconomist

I wrote some thoughts on the Iran War, where I explain why I don't think will end soon, why it's a stupid war that will blowback spectacularly and why I nevertheless don't think Americans will learn anything from it. philippelemoine.com/p/a-few-…

White-collar professionals who looked to Miami for a lower-tax, cheaper way of life are now finding it's more expensive than New York. bloomberg.com/news/features/…

Detailed data on China's June trade is out. Gotta say the Economist blew this one China's trade surplus in manufactures continues to trend up (trailing 12m sums). Especially if imports of refined gold and jewelry are stripped out 1/2

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.