I’m curious how they’re doing it. Obviously the standard bag of tricks (eg, speculative decoding, flash attention) won’t get you close. It seems like at a minimum you’d have to do multi-node inference and maybe some kind of sparse attention mechanism?
I recommend the TechTechPotato YouTube videos on Cerebras to understand more of their chip design.
My recollection from PC CPUs is that we've gotten many more operations per second, and many more operations per second per dollar, but that the power and corresponding cooling requirements for the CPUs have tended to go up as well. I don't really know what power per operation has looked like there. (I guess it's clearly improved, though, because it seems like the power consumption of a desktop PC has only increased by a single order of magnitude, while the computational capacity has increased by more than that.)
A reason that I wonder about this in this context is that people are saying that the power and cooling requirements for these devices are currently enormous (by individual or hobbyist standards, not by data center standards!). If we imagine a Moore's Law-style improvement where the hardware itself becomes 1/10 or 1/100 of its current price, would we expect the overall power consumption to be similarly reduced, or to remain closer to its current levels?