The trouble with the railways comparison is that after investing tons of cash the railways were built. With AI the GPUs have no value after 6 years (if that). So the investment must continue forever. It’s madness.
It’s not that they don’t technically work. It’s just they’re no longer efficient compared to newer versions that can do more with less power. So to remain competitive you need to upgrade otherwise your cost to execute a model is too high.
Hyperscalers used to write GPU’s down to zero value after three years, over the last couple of years they’ve all increased this to six.
But transistors break after what? 100’000 cycles?
GPUs can get “used up”. And if your computing center has twice as much running costs due to old, less efficient hardware, it isn’t competitive.
Edit: looks like transistors can partially recover with sleep cycles.
Editedit: that with the cycles was in flash storage. Looks like it’s higher in computing?
I’m not an expert but I was under the assumption that electronic components (including silicon chips and their internals) will age and give out on the decade timescale
The trouble with the railways comparison is that after investing tons of cash the railways were built. With AI the GPUs have no value after 6 years (if that). So the investment must continue forever. It’s madness.
The other trouble with the railways comparison is that trains actually work and can generate a profit for their owners.
What? GPUs don’t age. They might get old technologically wise, but they don’t just… die. The silicone cheap itself doesn’t care about age.
It’s not that they don’t technically work. It’s just they’re no longer efficient compared to newer versions that can do more with less power. So to remain competitive you need to upgrade otherwise your cost to execute a model is too high.
Hyperscalers used to write GPU’s down to zero value after three years, over the last couple of years they’ve all increased this to six.
But transistors break after what? 100’000 cycles?GPUs can get “used up”. And if your computing center has twice as much running costs due to old, less efficient hardware, it isn’t competitive.Edit: looks like transistors can partially recover with sleep cycles.
Editedit: that with the cycles was in flash storage. Looks like it’s higher in computing?
I doubt the transistor on a GPU wafer break after 100k cycles, as they run at gigahertz frequencies, some cycle billions of times a second.
SURE, BUDDY.
I’m not an expert but I was under the assumption that electronic components (including silicon chips and their internals) will age and give out on the decade timescale
Check out “References” part here