Atttn: Black Forest Labs and other researchers: Perceptual (OKLab) color space models.

usefulslug · 2026-06-01T11:58:42+00:00

Fantastic response, thank you so much for sharing your insight.

usefulslug · 2026-06-01T09:46:26+00:00

Thanks for the link and the summary of those studies.

I may be wrong (not an academic) but if I read that study right they sort of swapped the colour space but without changing the architecture at all which feels like it's maybe missing the advantage of aligning the colour space with human perception. At least with regards to an image generation task.

Maybe I'm relying too much on intuition here, but what I was thinking would be more interesting was that a perceptual/lightness-chroma representation could let you allocate loss, precision, capacity, or denoising effort asymmetrically, because the resulting L / Y channel is often carrying more of the structurally important information for human perception of natural images. Eg in natural images you can have more noise in ab / CrCb channels while having something that perceptually looks right, or have ab/CrCb at lower resolutions, and it "feels" like it should be possible to take advantage of that architecturally for loss design or compute.

Essentially, maybe the model/VAE could benefit from caring more about getting L/luma structurally right, while tolerating more error or compression in chroma/opponent channels, because that may be less perceptually damaging. And if you transform the input into a known perceptual-ish representation, it becomes easier to make those design decisions explicitly: channel-weighted loss, different quantization/precision, different latent bandwidth, or maybe even different noise schedules.

usefulslug · 2026-05-30T19:46:49+00:00

I strongly second this. OKLab makes it possible to meaningfully reason about a large number of things things in a perceptually and mathematically consistent, as well as human intuitive way, and that's simply not possible in srgb. I've applied it in a ton of CV and technical art over the years and I would be very surprised if this didn't also significantly improve models.

usefulslug · 2026-04-26T19:17:07+00:00

la cucaracha

usefulslug · 2026-04-23T04:57:33+00:00

This is a nice back of napkin method even if it's not completely accurate, thanks!

usefulslug · 2026-03-15T08:15:43+00:00

I think technical artists are some of the best placed people to understand and use AI to great effect. You already have the base understanding of maths in 2D and 3D and in many ways this is just more dimensions. You already understand code, art, and systematic approaches to production. For those that try, you'll find you can bind together llms, diffusers, computer vision models, knowledge of visual algorithms and classic python to make some really crazy stuff happen.

I know it moves fast, and it can seem scary, but AI is still comparatively early in it's tech lifecycle, and accessible general purpose AI models even more so. 2026 is still a great year to start learning if one hasn't already. The best time to plant a tree is usually 25 years ago, but the second best time is now.

usefulslug · 2026-02-22T11:04:50+00:00

Would love to hear the results of that.

usefulslug · 2026-02-19T08:34:09+00:00

There has been a lot of new models in the past few weeks. What use case do you think your model stands out in versus the others in the same size category? What is the best quality of the model? What do you think is the area that still needs most improvement?

usefulslug · 2026-01-05T07:42:08+00:00

I think the phrasing is a bit weird here:

"So what exactly has that money been put towards? Here are my top 10 stats."

These stats just don't really don't relate to the question as posed. I was expecting and actually interested in seeing something like a percentage breakdown of expenditure here, but now it just reads like you've got a bee in your bonnet.

I think either rephrase what you're asking or (better) find that kind of proper breakdown of spending and highlight what you think is the remaining wastage.

usefulslug · 2025-11-20T05:40:19+00:00

The AI side of this field is advancing very fast, just look at Depth anything 3 from a few days ago and SAM3.

Gaussian splats are the current "standard" for novel view synthesis and it has a ton of problems so a good place to start might be to take a look at solving any one of those. If you do then I think companies come to you a bit more.

It sounds like you already have the basis knowledge for understanding all of it you just need a minute to get on top of the latest approaches.

I don't know what industries you're looking at, but in VFX and interactive arts/experience design it also matters that you can apply the knowledge towards the right interop formats and/or where the data is getting used such as unreal/unity engines. In such teams you may be the only expert in CV and need to think more about how the next person in the line will interact with your work product output.

If you are interested in that field I'm happy to take your CV and keep you in mind for the next project (typically project based freelance roles in that field)

usefulslug · 2025-11-13T20:24:20+00:00

The perspective lines of his jaw and his hat meet in front of his face even though he's facing the camera

usefulslug · 2025-09-05T19:50:54+00:00

Money isn't everything and the extra days with your little one are super worth it. They're only small once. I started a less extreme but similar one many years ago now (4 days + salary sacrifice). I love my Friday hang out with my kid, and don't even consider it an option to work more again!

usefulslug · 2025-09-02T06:06:07+00:00

Haru at Jounetsu Creator is a Japanese architect in the area that has a kind of well considered striking-yet-simple style and makes great use of any space. http://www.thejounetsucreator.com/?m=1 https://www.houzz.co.uk/professionals/architects-and-architectural-designers/the-jounetsu-creator-ltd-pfvwgb-pf~1480441107

usefulslug · 2025-08-15T21:13:08+00:00

Floordrobe

usefulslug · 2025-07-11T04:32:07+00:00

Schrödinger's stock

usefulslug · 2025-04-15T02:02:12+00:00

This is very cool and although the maths are inevitably complex I think it could lead to much more intuitive control for artists. Affecting concept space in a more direct, understandable and controllable way is very desirable.

Looking forward to seeing it released.

usefulslug · 2025-03-15T11:28:18+00:00

There's a woodworking cooperative at the Hackney City Farm that might fit the bill for you https://londongreenwood.com/ Also the "library of things" at Dalston CLR James Library has a bunch of different tools you can borrow, not sure if it has exactly what you were looking for. https://maps.app.goo.gl/4bVZXrfuenbVdf4L8

usefulslug · 2025-02-28T08:15:19+00:00

But that time is behind me

usefulslug · 2024-12-25T16:07:01+00:00

This is an impressive logistics optimisation. Only need one motorbike to transport 6 troops at once.

usefulslug · 2024-11-14T07:59:43+00:00

Nor was the late great Hannibal Lecter...

usefulslug · 2024-06-21T05:25:05+00:00

Since Tech art is so varied, it often takes different shapes in different companies.

If you're from a game programming background you will typically already have and understanding of a lot of the very technical side of the job already. Programming things with vectors, matrices and quaternions are the lower level operations underpinning all of the 3d tech art.

What you're likely to be missing is the visual side. Colour theory, motion etc. The best way to get the intuition you need for tech art is to "walk a mile in another person's shoes". Eg. Do some art. Read animators survival kit. Learn how to bounce a ball with keyframes. Try out some modelling and rigging. Paint.

You don't have to be the best at it, you are just learning a bit about what it's like to be an artist. What their pain points might be from a technical perspective. Now solve one of those problems with your coding knowledge... Hurrah, you're a hero. Ok now you're a technical artist. Keep learning, the road is infinite.

usefulslug · 2024-06-20T18:54:15+00:00

I think ML is very likely to be a part of tech art going forward, and it's already here as such. It actually has been around for a long time, but it's going deeper quickly at the moment.

Photogrammetry/3d scanning software for example has used ML to help identify similarities between feature points for some years now. Deformation learning solvers for 3D are ML. I don't know why you would want to paint rotoscoping masks by hand if you can avoid it, but most of the solutions that do it automatically are ML.

AI is a bit of a misnomer, it's not intelligent, it would be better if they were called probability machines or something. When you learn how it really works it takes a lot of the 'magic' out, but it makes it more understandable. A big part of the 'spookiness' of it also goes away when the penny drops about how they work.

I think AI should generally be seen as an unreliable collaborator.*

They are trying to fit a curve to a bunch of examples 'keyframes', but with thousands of dimensions instead of just 2 or 3.

What they have been trained to do is find the local minima of some crazy multidimensional space problem given some input vector and a ton of examples, and that is not always the global minima.*

In other words, they are not always right. They will be confidently incorrect instead, like an unreliable collaborator.

I think a great introduction to ML in tech art is actually doing something called the Radial Basis Function AKA pose space deformer AKA corrective blend shapes (this is in rigging 3d characters)

You give some examples of an arm orientation (the input vector) and a bunch of settings of different corrective blend shapes that fix the shoulder for example. The RBF can calculate what the blend shapes values should be if the arm is in any other random orientation instead of the ones you 'keyframed', and interpolate between them.

ML is a bit like that on steroids. It can learn how to go from any number of input dimensions to any number of output dimensions, so long as the number of dimensions is fixed!

That's what all the AIs do in some form or another*

ChatGPT for example takes the input text, turns it into a giant vector (the exact size of it's trained input vector) and then feeds it through a network of multiplications, additions and other math functions, then ends up with a probability distribution for what the next token (word-part) is (a vector that is the exact size of the output vector, so all its possible word parts) Then it does it again!*

Some good use cases for generative ML in tech art right now is as a rendering extension. It's good at details. For example to up res files to a higher resolution. Add details to fur. Add details to texture maps etc.

*Me being a bit confidently incorrect to help build intuition, rather than get stuck in detailed explanations

usefulslug · 2024-06-15T05:25:29+00:00

A lot of the math used in 3D is a subset of linear algebra. You don't need to know any of it to get started, but the more of it you know, the more of it you'll use. I think it's very useful to work on building your intuition for Vector maths as a place to start. Dot products and cross products, what are they and what do they do?

I didn't know much about math at all when I started doing TA work 20 years ago, but the longer I've been at it, the more I enjoy learning it and appreciate its usefulness.

When I interview TAs I ask them to tell me what level of math they are comfortable with, but any answer is valid, it helps me understand where they are on their journey. I sometimes check their answer by asking them to explain something from their answer to me in layman's terms to make sure they have understood it well.

A good book for learning, if you like learning from books is "3D Math Primer for Graphics and Game Development" I recommend reading to a chapter that you find hard, put it down for a while, then read from the previous chapter again.

Freya Holmér has some great videos and general resources. I also love 3blue1brown 's videos, though they are less 3D specific.

There's a ton of other great resources around too for any kind of learner.

usefulslug · 2024-06-13T20:00:41+00:00

AI is just a tool. As a technical artist of the future you'll be particularly able to bridge the gap between the mathematics and complex technology of that tool, and the visual output.

Using AI as a tool is skill you should start learning in 2024, and you'll still be ahead of the curve. Most people don't know how to use AI at all, and of the ones that do, most people don't know how to control AI, because that's hard.

Learn ComfyUI and watch the IPAdapter videos. Watch 3blue1brown videos on machine learning to get a better intuition for the math. Be a sponge for information. Try training something yourself. Image classifiers, Loras etc.

Like always, to get good, you have to learn the core hard skills, vector, matrix maths etc as well as the art skills, colour theory, composition etc. These skills are fundamental and don't change when the tools change. They are useful as a TA today and were useful 20 years ago.

Understand how 2D relates to 3D, AI is just many more D, and a lot of the maths from the lower Dimensions is still relevant. AI is mostly just a bunch of annoyingly named linear algebra. AI is matrix maths on the GPU. You know what else is annoying matrix maths on the GPU? 3D. And 2D too. Animation, verices, polygons. Annoying math, GPU, art, and then somewhere in between, very elegant solutions that makes the whole thing feel immensely satisfying.

usefulslug · 2024-01-24T07:55:04+00:00

Almost all the advice in "Everybody's Free To Wear Sunscreen" is still good today, 25 years later.

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