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More Math to Shaders!! Visualize(and edit) both the code and the visuals instantly.
Now with data types and control flow, we can create function nodes with multi-line math to code.
Here's SDFs for Box, Sphere, Torus and Plane in maths straight from iq's blog
All in a browser!
Palash Bansal retweeted
For the next few days or weeks, anyone now has a root CA thanks to eMudhra. Time to have some fun with MiTMing unwilling devices!
Ported model editing blender operations and and editing ui, realtime in the browser with threejs (with an ai bridge)
Palash Bansal retweeted
when I started writing my engine, my expectation was that it would take 4 to 5 years to get it to a level where everybody could use it.
instead it took 18 months, and that's because I only even started using AI code in July, after Fable 5.
the actual core runtime of a game engine (the part that actually matters), can be written by hand by an experience programmers in a couple of months give or take.
the problem is the sheer amount of glue code you have to write to make it usable: editor code, serialization code, supporting different graphics features per platform, refactoring systems to make sure everything works together without impacting performance, the list goes on.
that kind of code is neither fun to write nor an exercise in technical thinking, and it made up 70% of the work before.
now we have automation for a big part of it. not for the thinking part imo (Fable knows every trick in the book but it seems to struggle with deciding what to do with it), but for the manual work that came after it.
this will simultaneously unlock incredible progress, and incredible disruption. programming doesn't look the same, jobs don't look the same, running a company doesn't look the same. we will have to figure out the new normal in the upcoming years.
do I miss writing code? every day. I went through rough times this year trying to come to terms with this new reality. part of me wants it back, the other part is excited about what the future will look like.
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.
make the hill climb racing game in webgi, threejs but it should look like unreal engine. graphics and physics should be very accurate
Play it here now - share.ijewel.info/ssgi-world…
it can prototype so many environments, gameplay mechanics very fast powered by a single toolset in a temporary container. this one took a couple hours.
just give claude webgi and a shell and it can iterate on its own.
Miniature worlds kit in webgi, threejs, created all within hours, interactive and realtime.
This has been possible because of a single stack(webgi) able to do everything -
Realistic realtime lighting + procedural generation + modelling and editing tools all in browser available
that makes it possible for Opus to focus and iterate on high quality and consistent results without having to worry about blender, different file format, inconsistencies in rendering, tech stacks whatever
Roam around in these worlds here - share.ijewel.info/webgi-worl…
Same frame, three renderers:
three.js WebGL, three.js WebGPU, threepipe+webgi.
Each sheet is one GPU pass
WebGPU: fewest draw calls (134).
webgi: fewest full-screen passes (14).
Watch the full video -
What Your GPU Does for One Frame: G-buffer, AO, Reflections, Bloom
youtu.be/oIFjSg6_OB0
Counted from the GPU call log of each frame in Chrome.
All same settings.
webgi plugins for threepipe go open source soon. Built on threepipe: threepipe.org
Automatic Video to live 3D
rebuilt the AlphaNIST robot assembly scene in threejs - real geometry, PBR materials, soft shadows, SSR and screen-space GI.
It renders live in your browser.
try it - share.ijewel.info/threepipe-…
more details below
basically just gave claude this video post and asked for a live interactive experience in threepipe, it found the models, set them up, made them move and recorded the video xitter.cf/octi_zhang/status/2110…
(1/6) From @GoogleDeepmind’s AlphaGo to AlphaZero, we saw machines find moves that reached beyond what we’d imagined for them. No one taught them those strategies. They emerged from reinforcement learning: playing, failing, and trying again under a single binary task reward for success or failure. Inspired by them, we couldn’t help but wonder: what might a robot discover if we gave it that same freedom to learn?
That question led us to AlphaNIST. Starting tabula rasa, with that same binary reward plus only a simple control cost, a single policy solves all 20 @NIST assembly tasks at a 98.2% success rate in simulation. More surprising still, AlphaNIST can complete 10 different tasks in a row, receiving that reward only once, after all 10 are done.
Just as AlphaGo’s strategies surprised its creators, AlphaNIST discovered dexterous strategies we couldn’t have come up with ourselves.
Paper: arxiv.org/abs/2610.13354
Website: alpha-nist.github.io
fixed the noise in webgi (#threejs) ssr (screen space reflections) also. its so smooth now, not sure if the video compression will allow to see the difference, but its definitely noticeable.
open source soon at threepipe.org
Try it on the link - share.ijewel.info/pr-threepi…
SSGI in webgi used to turn into TV static the moment anything moved
Try it out now - share.ijewel.info/pr-threepi…
temporal reprojection
variance-guided denoiser
one light per scene, no fill. everything else is bounce
no bvh, no baking, all in the browser








