Prakash

hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final ((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)

Fable attempts to communicate the gravity of this to me

hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final ((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)

hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final ((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)

I have a report full of security issues of a software I'm working on. Codex won't fix them because of Cyber guardrails Fable won't fix them because of Cyber guardrails Kimi K3 fixed them all. No restrictions, just gets the job done. This will end badly for OpenAI & Anthropic.

Friedberg: New study shows enzyme reverses skin age from 70+ years to 31 Chamath: That’s a $2T market. Did Scientists Just Discover How to Reverse Skin Aging!? “CML is kind of the predominant molecule that gets formed in this extracellular matrix that's driving aging, and nothing breaks it down. So these scientists set out to try and create an enzyme, an enzyme is a protein that breaks something down, that can break down CML. And so these guys kind of went out and they took the target, which is CML, and tried to figure out, ‘Okay, how do we actually degrade CML, clear that extracellular matrix, and reverse aging?’ They started to test it on the proteins that we would find in our body, casein, collagen, retinal proteins, which are in your eye, hemoglobin, and they were able to get rid of 52 to 97% of the CML, just degrade it away. And then they found several sites where they were able to degrade over 90%. And then they took actual human skin from elderly patients that had donated their skin, and they put this enzyme onto that skin, and they were able to eliminate 55% of the CML on the skin, basically reverse the skin's age down to the age of a 31-year-old, this is from greater than 70-year-old patients, just by putting this enzyme on the skin. And so it's kind of a groundbreaking demonstration of combination of AlphaFold, what's called directed evolution, where you change the order of the DNA that changes the structure of the protein to test different proteins, do high throughput screening, and ultimately make a novel protein that doesn't exist in nature today that can do something pretty profound for human health.” Chamath: “It will be a trillion-dollar market. If you can create a cream…” Friedberg: “I mean, dude, if you could put this enzyme literally on your skin and have it absorb in…” Chamath: “Game over. That alone is $2 trillion.”

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.

🧵 DeepSeek appear to have engaged, or be engaging in, a large-scale operation to collect outputs from proprietary models (including Claude Fable 5) for certain requests via their API as part of a distillation effort. After seeing such claims circulating earlier today, we conducted an investigation into them on our Discord. We found that, when "Deepseek V4" was used within OpenCode - via their official API - for complex prompts (i.e. 3D games) and combined with a knowledge-related query, the model provides virtually identical outputs to Fable 5. CoT structure is also very different from what is typically expected from Deepseek models. Both of these behaviours revert to what is expected for V4 when simpler prompts were used. When "Deepseek V4" was asked to incorporate answers to questions related to cyber or bio tasks that we verified hit Fable's classifiers into its 3D games, outputs tanked in quality. This is very difficult to explain unless the request was routed to Fable and fell back after hitting a classifier. For complex code prompts without anything else mixed in, like 3D games, outputs were remarkably similar to those produced by Fable 5. We were able to produce these results most consistently via OpenCode and the official Deepseek API combined with a prompt that specifies a complex code task. Deepseek have continued to modify their routing system since, as we have observed changes in behaviour and CoT style compared to those seen previously. Our investigation was conducted from 7AM-8AM PT.

SOCIALIST ACTIVIST: "These people have to have multiple jobs in order to sustain a lifestyle!" CALEB HAMMER: "Not the median American... What percent of the American population is relying on federal minimum wage?" ACTIVIST: "I don't know... I've met people across—" HAMMER: "It doesn't matter who you've met... Your anecdotal collection... is not the real world. What percent do you think makes the federal minimum wage in the United States?" [Activist stalls] HAMMER: "Answer the question or I am ending this podcast." ACTIVIST: "I don't know." HAMMER: "Answer what you think." ACTIVIST: "30%." HAMMER: "It's less than 1%. You know nothing."

China is winning the AI race and major US enterprise companies are now switching to Chinese AI platforms as the same tasks can be done for 10% of the cost. You can try and claim China has sinister plans but that is pure speculation. In a free market, companies will choose the better value