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...
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.
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.
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.
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.