What to learn to be a graphics programmer

> This is why most indy games now are 2D. That's do-able. Often in HTML/JavaScript.

Most indie games are definitely not in HTML/JavaScript unless you count vibe coded ones.

> You would encourage an individual to walk a path that is 90%(95%/99%) likely to damage their life horribly in the name of "progress"

Are we still talking about graphics programming? Damage one’s life horribly, really? Those poor kids you saw ‘spat out’, are they irretrievably broken? You speak as if people are single-purpose machines, and that there is nothing to learn from adversity and challenge. That skills are not transferable and there is nothing new is there to be discovered.

Turning this around, would I discourage a kid from seriously pursuit a career as an astronaut or racing driver? That has a higher likelihood than most to ‘damage one’s life horribly’.

I honestly cannot understand nor subscribe to this pessimistic worldview, the one that would tell a kid to abandon their dream and go do what they believe society needs. Bollocks to that.

Both are large fields with many varied applications of linear algebra (and non-linear math too), and many people trying a lot of interesting & complicated ideas. The question is way too vague to answer meaningfully, it depends on what you mean by ‘graphics’ and by ‘machine learning’ and by ‘linear algebra’ and by ‘more complicated’. ;)

The linear algebra used in the basic raster pipeline to manage drawing a 3d unshaded mesh is pretty simple, and you can get by knowing just a little bit of linear algebra, like dot products and how to multiply matrices, and maybe what homogeneous coordinates are. But that is by no means the extent of linear algebra in all of graphics.

The linear algebra used in a basic neural network is also pretty simple, and you can get by knowing dot products and matrix multiply if you’re writing your own inference, and maybe just a tiny bit of derivative calculus if you’re writing your own backprop, but otherwise you don’t need anything else.

Students in both fields have to learn some basic linear algebra, but most people working in ML & graphics generally don’t use any linear algebra day to day, because most people aren’t writing inference/backprop and most people aren’t writing the graphics pipeline.

BTW, matrices and linear algebra are pure convenience for neural networks, and maybe for the graphics raster pipeline too. You can do both of these things without using matrices per se (though you might re-invent something equivalent and/or less efficient by avoiding matrices).

> tell me which operators you’re imagining have any resemblance with typical graphics linear algebra

FWIW, since it seems like you’re unaware: most of those are used in graphics in general, and have been used since long before Torch existed. Convolution’s extremely common. Pooling is just a type of image resampling to graphics people. Non-linear activations are just response functions that graphics people use for colors for example, also volume rendering. Normalization, linear, distance, vision, and shuffle layers are all absolutely standard common operations in graphics, on everything from images to meshes to volumes to matrices.

BTW, most of those Torch layers aren’t “linear algebra” per se, they are just convenient building blocks for neural networks, many of which are also convenient building blocks for graphics… and for similar reasons.

Was your point implicitly limited to rotations or a raster pipeline’s model-view-projection matrix? That certainly does not amount to all “graphics”, right?

> Graphics in no way, way, shape, or form prepares you for ML. I don't understand why this is so controversial.

This isn’t really controversial, it’s just not particularly true as stated. Graphics is much more than 3d rotation matrices, and doing real modern graphics involves all kinds of linear algebra, with immense amounts of overlap between the linear algebra that ML and computer vision use.

Perhaps missing from this conversation is any thoughtful consideration to the history of today’s ML and the cross pollination between the fields we call graphics, vision, and ML. The implicit assumption you seem to be making that they are distinct fields without a shared history and co-development and without a shared foundation is not a good assumption.

I personally know enough ex-graphics people that transitioned to ML and were well prepared by graphics and are wildly successful in ML that it makes your claim sound somewhat ignorant of what’s happened and is happening in both graphics and ML from my perspective, for what it’s worth.

And if you have written one before, it might take five years. ;)

At least, that was my actual experience at a game studio. The engine team wanted to rewrite the engine but underestimated how much was there, how much was worth keeping, and how much work needed to be done. But that was a long time ago, and the studio’s now on Unreal.