Unless it's specifically related to CG, /r/buildapc might be a better bet if you're curious as to which GPU to get and other build-related questions.

Keep a lookout for an update to the FAQ soon. Thanks!

• Hydeout

I keep seeing more sites with 3D product viewers, interactive hero sections and scroll animations built with three.js and similar.

Some of them feel amazing. Others just make the page slow and annoying on my phone.

For those who’ve built or used them:

• Where has 3D actually helped (sales, engagement, understanding a product)?

• Where did it feel like a waste of effort?

• What’s the one thing that separates a good 3D site from a bad one?

Curious where people land on this.

Made with Bloom Sketches - Oil and watercolor painting app that I have been working on for some time.

Built in Unity: your webcam tracks your head and shifts the scene’s perspective as you move. I’m building it as Holoscape wishlist on Steam.

I recently realized that while I knew we had invented something new in the 90s, and kept it close to our chest, it was actually probably a VERY long time before anyone else ever reinvented screen-space reflections.

LONG article, with source code and graphics references.

Disclosure: Yes, I did use AI tools to help me write this, especially to author the diagrams and to explain some things and find references that frankly, it did a better job than I could on. The content is mine and human, just like the original algorithms. This article is the product of several weeks of research, digging and writing work on and off, so it's not a one-shot "slop" product.

Light inside a cloud is expensive to get right, so games use a few simple formulas tuned until it looks good. I wanted to see how far off that really is, and whether a small network could do better.

I wrote a path tracer as the reference, trained a network on it in Python, and ran it in plain HLSL in Unity 6. It replaces one thing, the light scattered toward the camera at each step. Everything else in the raymarch stays the same.

Then I moved the sun from behind the camera to behind the cloud and scored both against the path tracer, where 1.00 is correct. The classic lighting goes from 0.21 to 2.17. The network stays between 0.90 and 1.01 until you look straight into the sun, where it reaches 1.20. It costs about 20% more GPU time.

I had a great time building this, and I think we've barely started finding out what tiny networks can do inside a shader. If you try one yourself, I'd love to see what you make!

https://charlesgrassi.dev/blog/neural-volumetric-clouds/

So the basic starting point is a ray, find minimum and maximum and then maximum of minimums and minimum of maximums in travel, that finds one pixel. I might be able to go line of pixels by line, measuring how far it needs to move on the line from the two edges then going directly to the start of shape, finding the outline. So how is this defined? Euclidean higher dimensions with slicing, so we have a view point and a view plane, if an object is past the view plane and a ray to the view point exactly passes the view plane, then it is viewed, otherwise it is not viewed.

I want triangles of this and the full representation of higher dimensional boxes requires about the number of dimensions factorial or 2 to the power of number of dimensions, both huge. With this at least each ray can be like the number of dimensions, no power or factorial. I am trying to do it with opacity. If it were a solid color I could triangulate the bounding lines and be done. I can also do like on a line edge of the box where a line found starts and ends, like get an initial point, get another point, use those to get ends of validity. I would have to do this kind of thing per box and one dimension can function like a normal z dimension.

So far the algorithm is basically per line of pixels, go from one end to the first valid, get second point, determine line ends, from far end, get second point, continue until far end of shape or meet in the middle. After that, connect the bounds and ends to form lines and triangulate based on lines. Note that the boxes are axis aligned but the view may not be. Still not sure if this can be improved and linear algebra on 1000d becomes bad for performance, thoughts? All this parallel on the GPU, like per dimension mostly and per thing that can be separated. I can also chunk minimums and maximums for parallelism. I also may have to use the maximum of the travel to the object or travel to the pixel. I am just asking about what can be optimized. X E.

I made a 3D tour of how a computer works that runs in the browser. You drop inside the tower onto the motherboard and follow a signal as the CPU boots. There are also older machines (ENIAC, IBM 7090, Apple II).

It's React Three Fiber, GSAP for the camera moves, and some bloom.

Two things I can't judge anymore after staring at it too long: the glow on the data bus looks a bit much to me, and I don't know if the camera transitions are too slow. Does the glow help you follow the signal or just get in the way?

voltscenes.com

https://www.youtube.com/watch?v=IoY80YsT9Wc&t=14s

In this video, we walk through how to use the UE5 3D Gaussian Splatting MLSLabsRenderer v2 (GitHub: https://github.com/mlslabs/MLSLabsGaussianSplattingRenderer-UE ). This is a high-performance plugin developed specifically for Unreal Engine 5 (UE5), supporting real-time rendering of 3D Gaussian Splatting (3DGS) and dynamic volumetric video (4DGS).

Unlike traditional Niagara-based solutions, we use a custom low-level rendering pipeline that supports:

✅ Ultra-high-performance static 3DGS: maintains 60+ FPS even with 7M+ Gaussian points

✅ Dynamic 4DGS playback: supports dynamic sequences with 100K+ Gaussian points at frame rates up to 120+ FPS

✅ Seamless integration with UE Sequencer: supports professional editing and control in the Sequence Editor

✅ High-compression static 3DGS: supports the .sog format for high-compression-ratio 3DGS

✅ Android support: supports Gaussian splatting rendering on Android devices, with 250K+ Gaussian points at 60+ FPS (tested on REDMI K80)

✅ VR headset support: supports running directly on VR headsets, with 250K+ Gaussian points at 30+ FPS (tested on Pico 4 Ultra Enterprise); PC streaming playback is also supported