AI, in its current primitive form, is already benefiting a wide array of industries, from healthcare to energy to climate prediction, to name just a few. But...
That’s rather depressing to hear. AI is often used as a crutch used to pave over crappy code that would cost money to properly optimize. Maybe Nvidia is also using AI as a crutch instead of developing better GPUs that can actually render more pixels?
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?
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.
That’s rather depressing to hear. AI is often used as a crutch used to pave over crappy code that would cost money to properly optimize. Maybe Nvidia is also using AI as a crutch instead of developing better GPUs that can actually render more pixels?
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?
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.
For science and engineering, workstation cards like the A6000 aren’t going anywhere.