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SECRETARY RUBIO: The ultimate question of our time is whether Americans have a moral right to exist as a distinct nation and a distinct people, and thus to demand a government that defends and pursues our interests above all else.

I have a major result to share. I’ve found conclusive forensic evidence that the top 4 Chinese AI labs—DeepSeek, Moonshot, MiniMax and Ant Group—have built their newest models on NVIDIA’s most advanced Blackwell chips, which are barred from export to China. This sounds insane, but I discovered that almost every AI model carries a hidden signature of the GPU that trained it. When a model is first set up, the starting values of its weights are laid out in a pattern that depends on the exact GPU. Each combination of GPU and seed number produces a unique pattern—a sort of fingerprint of the hardware used to create the model. Traces of that pattern survive training into the published model. Again, this evidence isn’t based on any insider information or leaking. It’s based on a forensic analysis of the model weights released by the companies themselves. I searched more than six trillion combinations of chip layout and seed number and matched them to open-weights models. In doing so, I found conclusive evidence that six Chinese AI models—including DeepSeek-V4-Pro, Kimi K3, and MiniMax-M3—were initialized on NVIDIA Blackwell systems. Four of the models match Grace Blackwell, the GB200 and GB300 parts in NVIDIA’s flagship liquid-cooled rack-scale systems. I then verified these results on real hardware. Running unmodified PyTorch with the seeds I’d recovered, a Blackwell B300 reproduced DeepSeek-V4-Flash’s untouched starting weights bit for bit, and a rented GB200 reproduced Kimi K3’s to a correlation of 0.999995. A Hopper H100 reproduced none of DeepSeek-V4-Flash’s, and changing the seed by one broke the match. (DeepSeek’s seed is 953049583 by the way.) The method also was verified to match 24 known open-weights models to the hardware that developers said they used. It is exceedingly unlikely that these results are a coincidence. Across six trillion combinations, the best accidental match should reach only about 8 sigma (i.e., eight standard deviations above what random chance would produce). The real matches range from 49 to 1,385 sigma, and even the weakest single test hits 20. These were data-center-scale training runs. With some analysis of release schedules and model details, I estimate that the largest, Kimi K3 and DeepSeek-V4-Pro, used 2,000 to 3,000 Blackwell GPUs each. Clusters of this size cost on the order of $150 to $200 million each to buy, and across these labs alone would add up to more than half a billion dollars of export-controlled GPUs, not counting experimental compute or otherwise. It’s quite likely that we see multi-billion dollar expenditure on export-controlled GPUs. I am highly confident in this result, and it has been independently verified by senior researchers at OpenAI and Anthropic. You can read the full report at There is much more I’ve identified about these models through other forms of checkpoint forensics like this, and will have more to share soon.

As all NVIDIA employees I guess, I am deeply concerned by the campaign against Jensen Huang. Removing him would be a disaster. Many have documented on X and elsewhere how this looks like a coordinated coup. I'd add only one thing. Look at who would benefit from a dramatic weakening of NVIDIA. It is not China. It is not about selling GPUs to China because that train has left. China authorities have pushed back on the H200 the Trump administration allowed NVIDIA to sell. Look at what Jensen pushed back on: - regulations that would make open source model training too expensive - regulations that would make closed model providers immune to liabilities caused by their models. He said "if your product is not ready, then don't ship it" - regulation against model distillation. He said "this is competition. People do it all the time with NVIDIA products, they try to reverse engineer them." The other side will do everything they can to get him fired. As a French, I can't care less about his private life. I get that the US is puritan and sees it otherwise. But frankly, isn't it something he and his family has to deal with? Why should all NVIDIA employees, partners, and investors be collateral damage? Disclaimer. As my bio says, the above are my views only. I do not represent NVIDIA by any means. I only commented on publicly available information.

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