CsUtil.com

Software Engineer working on #opensource in my free time. See the full project list at

[Ian Curtis @XRarchitect]

Late night experiment. I built a demo that generates 3D environments from images into 3DGS, then uses them as a spatial reference for directing real-time AR camera movements. The capture is then run through Seedance 2.0 for the final output. all running on the web via three.js↓

[“paula” @paularambles]

sf is an extremely walkable city and i will die on this hill

[stash @stash_pomichter]

Announcing the first production robot navigation framework on $500 hardware

Explore the world once → your robot agent will relocalize and build a persistant, spatial memory across sessions

SLAM, relocalization, loop closure, map i/o, planning, control

No ROS. Open source.

[David Li @daviddotli]

Paint with squishy sea creatures in Splash Canvas, a web toy I created for Google Arts & Culture. Play with it at https://t.co/hVt3cUevZk
Procedural audio by @krighxz, easel model by @ugstuho

[CsUtil.com @csutil_com]

@dangreenheck Congrats, great work!

[Ian Curtis @XRarchitect]

20 million Gaussian splat of SF running all on a mobile device in WebAR. It’s really fun to move the phone around to zoom into different streets. Crazy to see the amount of detail in this scan

Threejs + 8th Wall (now open source) + sparkjs

[Ray Foss @FossPrime]

I made my Steam Controller automatically charge itself

@Dexerto @HardwareSteam @valvesoftware

[Alexander Goslin @xandurglar]

Unlike autoregression, InfiniteDiffusion is deterministic, randomly accessible, and effectively stateless:
- Worlds are shareable by seed
- Teleportation is O(1) instead of O(n)
- It works in multiplayer and across distributed clusters
- Zero persistent storage required

[Z.ai @Zai_org]

GLM-5.2 leads GLM-5.1 by a wide margin across various domains, including coding, tool usage, reasoning, and general knowledge.

[0beqz @0beqz]

Pushing interior reflections with denoised glossy SSR

#threejs

[Ettore Di Giacinto @mudler_it]

Depth Anything 3 now runs as pure C++/ggml (@ggml_org) . No Python, no PyTorch, no CUDA toolkit at inference, just one self-contained GGUF.

It's faster than PyTorch on CPU! and ties speed on GPU. The CPU win came from the last place..I'd have looked.

Quantized GGUF on @huggingface🤗

Shout out to @ggerganov for ggml (we are building a ggml-world!❤️) and to @ByteDanceOSS and Depth Anything 3 authors @bingyikang @jhliew91 @donydchen !

[Radiance Fields @RadianceFields]

For the people asking about 3D printing gaussian splats, this is honestly amazing.

[Spencer Baggins @bigaiguy]

A French engineer who lives quietly in Paris has spent 30 years writing software that the entire internet now runs on without knowing his name.

He wrote the code that streams every YouTube video, every Netflix show, every TikTok clip. He wrote the code that runs the virtual servers underneath AWS, Google Cloud, and Microsoft Azure. He calculated more digits of pi than anyone in history. He has no Twitter. He has no marketing. He just keeps shipping.

His name is Fabrice Bellard.

Here is the story, because almost nobody outside the systems programming world knows what one man has built.

Fabrice was born in 1972 in Grenoble, France. He studied at École Polytechnique, the top French engineering school. He never went to Silicon Valley. He never built a startup empire. He just wrote code.

In 2000 he started a project called FFmpeg, an open-source multimedia framework for encoding, decoding, and streaming video. He was 28. The project did one thing nobody else had done well. It handled every video and audio format that existed, in one library, on every operating system. He led it himself for years.

Today FFmpeg is the invisible engine of the internet. YouTube uses it. Netflix uses it. VLC uses it. Chrome and Firefox use parts of it. Every Android phone, every iPhone, every smart TV, every video editing tool you have ever touched runs FFmpeg somewhere underneath. If you have watched a video on a screen in the last 20 years, Fabrice's code processed it.

He was not done.

In 2003 he started QEMU, a machine emulator and virtualizer. He wrote it solo until version 0.7.1 in 2005. QEMU lets you run any operating system on any other operating system. It became the foundation of modern virtualization. KVM, the Linux kernel hypervisor, runs on top of QEMU. Every major cloud provider, AWS, Google Cloud, Microsoft Azure, IBM Cloud, runs virtual machines on infrastructure built around it. The Quick Emulator is the most cited piece of cloud infrastructure code on Earth.

He kept going.

In 2001 he won the International Obfuscated C Code Contest with a small C compiler that grew into TCC, the Tiny C Compiler. TCC can compile and boot a Linux kernel from source in under 15 seconds. In 2004 he calculated the most digits of pi ever computed at the time, using a personal desktop computer and an algorithm he derived himself called Bellard's formula. In 2011 he wrote a complete PC emulator in pure JavaScript that runs Linux in your browser, a project called JSLinux that engineers still cannot believe is real.

In 2019 he released QuickJS, a small but complete JavaScript engine that fits where V8 cannot. In 2021 he released NNCP, a neural network based lossless data compressor that immediately took the lead on the Large Text Compression Benchmark.

Then he turned his attention to large language models. He built TextSynth Server, a web server with a REST API for running LLMs locally. He released ts_zip and ts_sms, compression utilities that use language models to compress text and short messages at ratios traditional algorithms cannot reach. He released TSAC, a very low bitrate audio compression system. In December 2025 he released Micro QuickJS, a new JavaScript engine for microcontrollers, separate from QuickJS, designed for environments with almost no memory.

Fabrice co-founded a telecom company called Amarisoft in 2012, where he serves as CTO. Amarisoft builds 4G and 5G base station software used by carriers and labs around the world. He has been running it for over a decade while continuing to ship personal projects from his own home page at bellard dot org

He has no Twitter. He has no Instagram. He gives almost no interviews. His personal website is a flat list of projects with no styling, no fonts, no marketing copy. Just titles and links.

A quiet French engineer who never moved to Silicon Valley wrote the code that quietly runs the internet.

He is still shipping.

[0beqz @0beqz]

Indoor scene using my three.js SSR denoiser

Glossy reflections in real time has always been a hard challenge.
Here, it's using a recurrent denoiser and a special temporal reprojection pass with hit point reprojection.

Publishing soon, just need to clean it up for a PR 👀

[CsUtil.com @csutil_com]

@simonw Sounds to me like it could also be preparation for granting only us citizens access to Mythos level models again in the future?

[Lukas Ziegler @lukas_m_ziegler]

This is actually sick! 🤯

A motion generator for robotics. and gaming.

This is MotionBricks cooked by @NVIDIAAI. It's a 15,000 FPS real-time motion generation for robots and games.

MotionBricks shipped to SIGGRAPH 2026 with code that integrates directly into NVIDIA's GR00T Whole-Body Control stack. 15,000 FPS, 2ms latency, 350,000 motion skills from a single neural backbone.

Okay, let's have a look how it works: first train one generative model on 350k production-grade mocap clips (BONES-SEED dataset from Bones Studio).

Then add "smart primitives" on top, a unified interface where you specify navigation targets, object interaction keyframes, and style prompts. The network generates everything else in real-time.

There's no animation graph., and no per-task fine-tuning.

Their demo-character navigates, picks up a sword, vaults a bench, sits down, switches between zombie/injured/skipping styles. Every frame generated by the network, in real-time.

I think that this matters as MotionBricks is now core to GR00T Whole-Body Control which is the same stack powering humanoids widely used in research across the globe.

Btw. code ships with an interactive G1 demo, but a full robotics-integrated release coming in ~1 month.

The motion stack for humanoid robots is getting bigger! 🔥

Check it out here: https://t.co/eiCcRTzTFc

cc: @NVIDIARobotics

~~

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[Mykhailo Moroz @Michael_Moroz_]

I've been implementing multi-object combined LODs (actual LODs this time) for gaussian splats. It is insanely cool, due to the way I select LOD's I *always* render the same amount of splats no matter how many splats are in the scene. This scene has 108M total combined splats.

[MrNeRF @janusch_patas]

Everybody is stepping into the LOD game, and so is LichtFeld Studio.

Preview of 260M Gaussians streaming into the viewer live.

I use the RAD format which is processed on GPU within LichtFeld. It can be also simply dumped straight into the spark.js web viewer, albeit it will die at that amount of Gaussians.

What other solutions don't tell you is that they need hours to preprocess a 3DGS ply to make it streamable. This was just a ply exported to RAD by LichtFeld Studio's convert tool (took 5 min at that size) and it is immediately ready to stream.

In the comments there is a smaller dataset with 103M Gaussians that streams on startup into the viewer. Both datasets were created by Andrii Shramko.

Let's see how far I can push this (need bigger datasets)

[Martin Valigursky @ValigurskyM]

🌍 What if the entire Earth could be streamed as a photorealistic 3D world?

This prototype renders billions of 3D Gaussian splats directly in the browser.

Powered by @playcanvas . WebGPU + WebGL.

The technology is ready. The remaining challenge is capturing the planet.

👇

[CsUtil.com @csutil_com]

@Jacobcygd @GabRoXR Nice! Where can I download that?