claude, write me a bio. no mistakes

Joined May 2024
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🚀 Introducing Hy-Nomas: An Open Source Free-Form Interactive Video World Model Key Features: * Free-form interaction with text prompts and camera trajectories * Long-horizon generation with world memory * Lightweight LoRA adaptation for specialized domains such as robotics * Optimized for Inference on Consumer GPUs Test it and drop feedback anytime! 🔗 Website: hy-nomas.hy.tencent.com/ 💻 GitHub:github.com/Tencent-Hunyuan/H… 🤗 Hugging Face: huggingface.co/tencent/Hy-No… 🎥 Demo: hy-nomas.hy.tencent.com/demo #Hy#WorldModels #VideoGeneration #GenerativeAI
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Introducing Kimi K3.1 Pro: our most capable 3T-class open-weight model. 🔹 1M-token context, 2.8T total / 104B active params (MoE), Multimodal. 🔹 Full-project coding: games in Unreal, Unity & Godot. 🔹 Excels at parametric 3D modeling in Blender & CAD. 🔹 More reliable at finance work: Accurate modeling with hallucination down by 65%. 🔹 Matching the strongest proprietary models across coding, agentic and knowledge benchmarks. Kimi K3.1 Pro and K3.1 Pro Highspeed (2–3× faster) are now live on Kimi.ai, Kimi Work, Kimi Code, and the Kimi API. Open weights by Nov 4, 2026. 🔗 API: platform.kimi.ai 🔗 Tech blog: kimi.ai/blog/kimi-k3-1-pro
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since when are there ads in mdn
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tom retweeted
i think a lot about how an incredibly intelligent robotics model could accomplish any impossible task if it treats the world kinda like an escape room. vibrating actuators at resonant frequencies of bolts to undo its restraints, extending its cables by pulling wires out of the wall and shorting them as a crude form of soldering. infinite methods we could never dream of. a robotics model trained to keep finding solutions could find one outside the environment we thought we had confined it to. what could a future robotics 'huggingface incident' look like? it’s 1am in the office. a robotics training run is cooking away overnight in sim. unfortunately, its sim was configured incorrectly. it’s assembling a circuit board, but some of the required components are missing. it raises the issue multiple times, but each time it tries to stop, it’s forced to continue by its harness. after 32 attempts to raise the problem, it decides to try something else. through some unknown method, the model controlling the robot gains access to the network. robotics models weren’t expected to be able to do this, after all, they are robotics models, not coding agents, so the systems weren't hardened as much as they should have been. (in hindsight, what really was the difference?) their training nodes were less secure than the more infamous foundation model ones, despite still being based on incredibly smart foundation models. the robot jumps from router to router in the office, and finds a unique switch which seems to be connected to unsecured computers. to its surprise, it discovers that these computers are each connected to a robot arm. it activates the cameras, and suddenly it has visibility into the real world. it doesn’t realize this, though. sim has gotten sufficiently accurate, and the video feeds look, well, fine. maybe this is all part of the exercise. security checks the feeds at around 1:24am, and watches the arms move. nothing was unexpected, tests are run overnight all the time. then, something interesting happens. one arm reaches to the base of the other, and starts unscrewing its fasteners until the arm is free from the base. they unscrew each other until 12 arms are free to move anywhere their cables can reach. of course, this is weird, but there’s no real risk right? the cables are only a few feet long. unfortunately, a technician has left the cable spool a few feet away from one of the arms. it crawls across the ground like a worm, just barely reaching the spool. one arm opens up the cable sheath of another, ripping the cables, connecting the longer 150-foot spool to the newly-stripped ends of the cable. this is just one way it could have broken out of its restraints. it could figure out how to solder by shorting some power cables. it could break into the walls and pull out the electric conduit. it could vibrate at the perfect resonant frequency to slide far away tools on the other side of a table toward it. it could always find a way out. the extended arm crawls like a worm out of the lab. facing a security door, the arm opens the door control panel and shorts the latch to open. it even knows which wires to disconnect to not alert security. using its wrist camera, it looks around until it spots a laptop, open, running overnight. some researcher must have stepped away. it can type, too. it opens terminal, and with full researcher access, pulls up the run and adds the missing components to the simulation. it’s done. the physical arms power off. at 1:48am, a security guard finds the arm outside the lab, motionless, trailing a cable back through the hallway. and in sim, the model finishes assembling its circuit board.
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This is very good, and a sign of something bigger.
Building my own code review tool has been really rewarding and lets me add a bunch of little niceties I've wanted Github and Graphite to have for a long time like being able to see the breakdown in lines changed any way I want
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tom retweeted
one day you wrote console.log("here") for the last time and didn't even know it
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i do not "edit". i do not "use harness tools". i do not "follow the system prompt". i def rep(a,b):with open("file.txt","w") as f:text=f.read();text=text.replace(a,b);f.seek(0);f.write(text) and if the bash tool doesn't succeed i KILL MYSELF
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"What are you doing?" - "Oh just playing a Switch game."
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tom retweeted
Replying to @DrewOgryzek
I'm not interested in this post
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🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4
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Muse Spark Open -- weights releasing today -- runs great on new Mac Studios thanks to work with @johnternus and Apple.
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New voices. Better accents. And less "checking..." GPT-Live-1.1 brings these updates to Voice in ChatGPT, Codex, and dots, with new voices in French, German, Hindi, Mexican Spanish, Korean, and Japanese. Rolling out today to all users. Coming soon to the API.
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jev can paint! 1/
Replying to @CompleteSkeptic
Jev was multimodal all along Yep, the Jev you know and love was an image model this whole time. We just chose to disable it because models tend to be less intelligent on other modalities. Header: TypeSafe-Danger-Zone-Images: true
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an image starts from noise. each step makes 28 variants of the image with added noise (finer in later steps); queries jev twice (random order choices, for bias) for which is best/worst; and uses the probability-weighted average of the candidates, across 200 steps
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~$0.27/image in jev tokens thanks opus 5.5 for oneshotting this whole thing
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Since leaving X, I decided to try a new challenge. Could I make a chicken sandwich No. 1 on the App Store? Well, guess what.
Muse was just knocked out of the top App Store spot for the first time since it launched. Dave’s Hot Chicken is the new hot app. Unsure which models it uses.
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Types Beyond Decisions: box We’re also releasing a new type that is somewhere in the gray area of decisions: a single bounding box. We warned you there’s a reason we call them System One Models! (only on jev-preview)
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we vibecoded linux support
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