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I’ve decided to leave NVIDIA. There are a few things I want to say. As a robotics engineer at NVIDIA, I have seen Jensen as much more than the company’s CEO. I admire his willingness to invest in a future that was not yet obvious. He committed to CUDA long before the deep learning boom and positioned NVIDIA for AI before it became everyone’s priority. Those decisions helped build the infrastructure that powers today’s AI. I have seen that same vision in physical AI: investing in robotics, sharing open-source tools and projects, and building computing platforms that bring AI into the physical world. This is the work I do every day—and a future I believe in. But what matters most to me is the culture he helped build. Engineers are encouraged to explore, take risks, and learn from mistakes. Jensen reads employees’ Top 5 emails, follows their work, and engages directly. In a company this large, that connection matters. It makes an individual engineer feel that their ideas can still be heard. That is why this has been so disappointing. I do not have all the facts surrounding the allegations, and I cannot prejudge the investigation. My admiration for Jensen does not put him above scrutiny. What I find difficult to accept is having to come to terms with his departure before receiving an explanation that helps me understand it. What this means for our direction, our culture, and the people doing the work remains unclear to me. I have felt that engineers’ perspectives matter here. On this decision, I have not felt heard. That gap has been more painful than I expected. I understand that some information cannot be shared immediately. But that does not erase the feeling of being left outside a decision that affects the company we help build every day. A company’s greatness comes from its leadership, its governance, and the people who turn its ambitions into reality. Employees’ trust and sense of belonging are part of that, too. Jensen’s vision and the engineering culture he shaped were important reasons I wanted to stay. His departure led me to decide that my own chapter here should also come to a close. I leave with sadness and gratitude. The colleagues I have worked with, and the work we believed in together, will always matter to me. These are my personal views.

The Evolution of SGLang, 2024 → ∞: from a caching trick to the inference engine behind 330+ organizations | 2026 Under three years, twenty milestones: from RadixAttention (Jan 2024) to SGLang v1.0 and the SGLang Consortium (Nov 2026). Today SGLang is used by 330+ organizations, supported 217 models on day 0, and runs on hundreds of thousands of GPUs. Music only. Every frame and every note generated in code. Sources: LMSYS blog and @sgl_project (Nov 12, 2026), @lmsysorg (Nov 11, 2026), @radixark (Nov 12, 2026), SGLang Summit 2026 timeline wall and keynote slides. AI-generated content (视频由 AI 生成).

Young people in China are, without a doubt, some of the hardest-working and most resilient people in the world. The economy has been driven into this fucking mess, yet people aren’t even taking to the streets to protest. They just quietly get on with their lives. If they find a job, they go out and work, even if it probably means working 996 hours, just enough to survive, but with little or no money left to save. If they can’t find a job, they stay home and lie flat. They’re not hurting anyone. What the hell have they done wrong? You have to understand that choosing to lie flat is also a personal freedom! And yet, even that isn’t good enough for some people…

Built at NEAR HACKATHON: X3 Force Field — a typed .x3 language + compiler for AI-agent spending rules. A NEAR Guard checks signed terms, not model promises. 25 USDC moved Solana→NEAR on mainnet under owner-approved limits. @NEARProtocol #NEARHackathon#

My Watchlist got smaller this week, and that felt like progress. @GeckoTerminal shows me the list I actually use, not the list I wish I had, and keeping it short is the whole point for me. Every pool on there has a reason I can say out loud: what I am trying to learn from it, or what question it helps me answer. If I cannot say that reason clearly, it comes off. If I can, it stays, even when nothing is happening with it, because I am tracking to learn, not to chase movement. I check it the same way I tidy a desk. I look at what is still earning its place, I ask what has changed since I added it, and I let go of those that no longer teach me anything. That keeps my research honest, and it keeps my attention on the pools I already understand best. That is only how I keep mine, not advice for anyone else. My setup is here if you want a look: [your Watchlist link] What did you last take off your Watchlist, and why did it lose its place?

Having multiple research tools is useful, but the experience becomes much better when users can access them without constantly switching between different platforms. Consider how a Solana trader researches a new token. They might start by checking its market activity, investigate the wallets involved, examine token distribution and look for possible risks before making a decision. Each step provides a different piece of information, but they all contribute to the same research process. This is where @StonkwatcherSF’s planned website restructure becomes interesting. The team is working on improving the website’s navigation and making its features easier to discover. The new landing page is also expected to showcase the broader Stonk Watcher ecosystem, including its products and mobile application. I think this is a meaningful direction because Stonk Watcher is aiming to bring different parts of crypto research closer together. Token discovery helps users find opportunities. Wallet tracing provides more context about the people and addresses behind transactions. Market analysis and risk indicators help users examine what is happening before deciding where to focus their attention. These tools become more useful when they fit into one connected workflow. The mobile app adds another layer by making research and safety features more accessible beyond the desktop experience. Of course, a redesigned website alone doesn’t guarantee a better product. Navigation needs to be intuitive, information needs to be reliable and the different features need to work smoothly together. That’s what will determine whether this restructure makes a real difference. I believe good product development is not just about adding more features. It’s also about making existing tools easier to find, understand and use. The goal should be simple: less friction, better access to information and a smoother research experience. That’s the progress I’ll be watching from @StonkwatcherSF. @StonkwatcherSF $STWC

In 2015, AI hallucinating was the whole point. 🌀 This is DeepDream, running on VGG16. You hand a neural network an image and tell it to exaggerate whatever it thinks it sees. Then you make it do that over and over, each pass building on the last. 🔁 It finds eyes and creatures everywhere 👁️ because it learned to see from ImageNet, a dataset of 1,000 categories packed with animals (about 120 are dog breeds alone 🐕). Ten years later, the same behavior has a less fun name: hallucination. And we spend a lot of engineering effort stopping it. 🛠️ Same thing underneath, just a different job.

For the first time in my life, I'm making real progress on my projects. I've been running a team of Grok Bots on the Ultra plan (X Premium comes with it), and it works the way I wanted. Nothing is perfect on complex projects, but it keeps getting better at understanding me. The team behind it ships new features and improvements almost daily. Unbelievable pace. Special thanks to @elonmusk for the personal support, @poteto, @mattyp, and the whole engineering team. You're all brilliant. 🙏 My main project right now: writing a long Chinese novel and producing a series of short ink animations alongside it on Rednote, all with a team of bots that gets me. More on how it works soon. 🧵