this post was submitted on 16 Sep 2024
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[–] [email protected] 10 points 1 month ago (1 children)

Usually people are against just throwing more hardware at a problem.

They're going to keep making more powerful hardware either way, since parallel processing capability supports graphics and AI just fine. But if they can use a novel software solution to drastically increase performance, why not?

[–] [email protected] 11 points 1 month ago (2 children)

They’re going to keep making more powerful hardware either way, since parallel processing capability supports graphics and AI just fine.

It's not quite as simple as that. AI needs less precision than regular graphics, so chips developed with AI in mind do not necessarily translate into higher performance for other things.

In science/engineering, people want more—not less—precision. So we look for GPUs with capable 64-bit processing, while AI is driving the industry in the other direction, from 32 down to 16.

[–] [email protected] 4 points 1 month ago (1 children)

For science and engineering, workstation cards like the A6000 aren't going anywhere.

[–] [email protected] 1 points 1 month ago

That’s true, but I would like to see improvements driven along the consumer segment also. AI rendering is a nice software addition but I could easily see it becoming a distraction from hardware improvements.

Consumers generally can’t just throw more money at a problem in the way that professional and business can.

[–] [email protected] 3 points 1 month ago

It's funny because we don't even need GPU's. There's tech that offloads the model's "search" to an analog computer which is ~98% accurate for a fraction of the energy.

I imagine NVIDIA isn't too excited about that side of AI, though.