GenTT (@gen_tt) profile picture

OpenUSD, UGC, graphics, topology, shader, interaction

Joined March 2019
Photo by GenTT (@gen_tt)Photo by GenTT (@gen_tt)Photo by GenTT (@gen_tt)Photo by GenTT (@gen_tt)Photo by GenTT (@gen_tt)Photo by GenTT (@gen_tt)
最近刷到有人说把 FDE 做成了网管的问题,帮忙解决网络、配环境、教员工用工具等等。这让我联想到了农业的发展。 在日本逛超市的时候就注意到北海道产的土豆要便宜得多,据说一个重要原因是北海道已经有比较成熟的规模化、机械化种植,而日本中部很多地方依然是农民自己经营的小块土地。中国也是一样,明明现代农业技术早就有了,家里长辈还是坚持在自己种,近两年倒是出现了一些承包农村土地的。 所以现在想想这可能不只是技术普及的问题而是生产组织问题。给每个农户配一台先进的农机,反而说不定共享农机更合理。
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MIRRORのちょっとしたメイキング作りました。 今回の手法を簡単に説明すると、撮影した映像を好きなようにレイアウトしたり、カメラワークを変更することができます。 使ったツールはvista4D、meridian、MiniMax H3、comfyUI、seedance2.5、blender、flameです。
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GenTT retweeted
Lightmaps on the web usually meant an offline Blender bake. @threejs r187 bakes them live with @BenHouston3D's new LightMapper + unwrapUVs. So we are making a game: move a wall and the GI re-bakes in ~0.8 s, even on a phone. Try the demo here : oddjolt.itch.io/bounce
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GenTT retweeted
Neuralink’s first product is called Telepathy. It enables high-speed communication with computers or humans simply by thinking. Output bandwidth will vastly exceed the fastest human speech or typing in a few years. Read that sentence again.
Our engineers recently visited one of our speech restoration study participants for a 72-hour hackathon. The goal: rapidly prototype as many features as possible to enhance the experience of using Neuralink to communicate with thought. Here are some of the things we built 🧵
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木のコンベアを作成中! アートを大刷新するにあたって、メカはちゃんと動く仕組みで作りたいと思ってます こういうちゃんと理屈が通っているシステムも簡単に作れるようになって本当にありがたい 空港のベルトコンベアとか、内部が見えるエスカレーターとか、こういうのずっと見てられる
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感觉现在有点像是工业革命之前的蒸汽机时代,任何人都可以在家里发明出一个之前的所有人都没见过的新玩意儿
Last month, we demonstrated high-rate alchemy: turning mercury into real, stable gold, beating CERN’s record by a factor of 10. Last week, we enriched isotopes in the world’s most powerful plasma centrifuge, beating the Soviet record that stood for 40 years. Now, we’re building a fusion reactor in San Francisco to achieve record power density.
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GenTT retweeted
Another polish thing for @bot: More bots to love and make your own. We also cleaned up their animation states. my new personal faves are the heart and flower 🥺 🫰to @lukebvrker and @kenneth_kuh for the most delightful work on these
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When I was writing Unreal Engine 1, my time was divided as follows: - Around 30% went to seriously deep coding on hard problems: assembly language texture mappers, C++ BSP trees, data persistence, object oriented systems design, and networking. - Around 70% was just typing and refactoring large bodies of code needed for a complete engine feature set. This was not hard, and while I was doing it my mind was mostly on the deeper coding topics, thinking and planning for what's next. It didn't feel much different from vibe coding today, except that it was just me typing code on an IBM Model M keyboard rather than prompting it and reviewing the results. So, it has always seemed perfectly logical that we would rely on AI for that 70%, once the AI could do it with a similar quality standard as we could, which has never been perfection. It came as no surprise that, after a few years of AI model evolution, it was able to take the reigns on that 70% and free up programmers' time for more valuable tasks. What's more of a surprise is the emergence of AI as a sort of insta-Carmack able to solve hard technical problems quite cleverly and often cleanly, and that it's able to reason about and work in complex 3D scenes both by operating the tools and by directly understanding the raw data files. I abandoned assembly language in 1998 when out-of-order CPUs made much simpler C/C++ code faster, and never I missed it. If prompting through architectural documents, concept art, and design plans can transcend typing code and tweaking vertices, that will enable developers to spend their time on higher-level, higher value technical and creative tasks. What matters is the end product, whether it's a game or an engine. Anything developers can do to try out more ideas and make better software and games faster is a win for everyone.
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if you’re gonna explore the worlds, what’s best than a little companion friend? updates below 👇
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I built it instead 😁 Introducing LeanCIL - formal semantics for .NET CIL in Lean 4, with machine-checked proofs against actual compiled assemblies Not just C# - a foundation for verifying F# and other .NET languages too Let's formally verify dotnet github.com/NethermindEth/Lea…
I just proposed an official @leanprover 4 formal semantics for C# - giving C# a foundation for machine-checkable proofs. AI agents are getting very good at writing code - and very good at breaking it. In the agentic era, "tests passed" won't be enough for critical software. We need to be able to prove properties of the code we ship. And this is becoming practical. Rust already has Aeneas -> Lean. Microsoft Research is using it to formally verify SymCrypt. Java and C have roots into formal verification too. C# should not be left behind. AI can write the code. AI can construct the proof. A deterministic proof kernel checks whether the proof is actually correct. That is a very different trust model from: AI writes code -> AI reviews code -> hopefully both were right. Proposal: github.com/dotnet/csharplang…
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GenTT retweeted
Big news for CAD: SMLIB, NVIDIA's NURBS based kernel is finally open source today 🍻🎉 We have been working with SMLIB and its dev team for more than 20 years. It enables all our products: classcad.ch headless CAD, GUI, AI/MCP, PDM, etc github.com/NVIDIA-Omniverse/…
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没想到一年半后大家还在讨论 手洗的衣服比机洗干净 手写的代码比AI写的好
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GenTT retweeted
codebases have always contained slop. we have always been okay with this because code rarely needs to be perfect, outside of mission critical "hard" (eg embedded) software. swe is a unique form of engineering because you're often building something that constantly evolves and is almost organic - user tastes change, your mental models evolve, and features come and go. admittedly, i and many others who've been coding for a long time were initially (like back in 2024) skeptical that agents would write production code. "but what about all the slop that would enter our beautiful codebase?". well, even before, we had human slop, and there was a lot of it! if we're being truthful, most people call "code i didn't write" slop. the reality is that 99% of people (i include myself in that number) don't even know what Good Code looks like, let alone be capable of writing it. i would propose that Good Code is: • correct • bug free • fast and cost efficient to run it has always been exceedingly difficult and expensive to write truly Good Code, because for the longest time (maybe @bendlang will change that), code was not something you could cheaply and formally guarantee to have all 3 of these properties. this is why writing hard software is much more difficult and expensive, because depending on the use case, you may only get one chance and so you have to be right from the start. but the vast majority of software we use does not need to be Good Code to provide value to users. in fact, it is very likely that most software we use is not formally verifiable! we accepted some bugs in exchange for velocity and progress, so we rely on tests and o11y instead and have adopted a more incremental approach. this is a good thing! agents help us move faster, and if you're open to the idea, are capable of helping us write better code. it won't be Good Code (that is still expensive), but it is likely to be much better on average at scale. the new craft of swe is to figure out how to do this. it's your job now! if your productivity with and without agents is not significantly different, you're doing something wrong. but it's not too late to embrace it and use it as an opportunity to learn a whole new skill tree
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We need self-replicating factories. Reindustrialization won't happen against economic laws. Manufacturing has to be competitive worldwide. And improving existing factories, even with automation, is not enough. Only 30-40k robots were installed in the US last year, so the pull from existing factories is weak. They’re good. Humanoids are being promised as the solution. But who will build them? Still humans. Humanoids not optimised for self-build. The most practical solution to these problems is a self-replicating factory.
It will build humanoids, enable the US reindustrialization, and help colonise other planets as a side product. Who should I talk to? I’m assembling people who think the same way.
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It’d be awesome if logistics software could be visualized and turned into a strategy game. You manage transportation, routes, and the entire logistics network like you’re playing a strategy game. Inspired by @DilumSanjaya, I also used Opus 5.5 to build it.
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text-to-cad plugin extension is now live on codex! - generate 3D models as STEP, STL, 3MF, or GLB - DFM for printing, sheet metal, CNC, injection moulding - connect to fab services like bambu and sendcutsend 100% open source and free, runs locally inside the codex desktop app
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昨天晚上 Anthropic 推出了 Claude mods,PI最近 1.0 更新也推出了 code mode,再加上 Codex 更新的插件系统和 DeepSeek harness 的一切皆插件。 似乎所有的这种超级 Agent 都在开发类似的功能,可以让用户自己往 Agent 上叠加功能的插件体系。 但是这几个的作用位置以及工作原理都不太一样。我跟Muse 讨论了一下,收集了信息,然后做了张图,让大家用更简单的方式去理解这 4 个产品,以及它们这套插件系统不同的能力。
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