Google supercharges machine learning tasks with TPU custom chip
I wonder if we will be seeing more of this in the (near) future. I expect so, and from more people then just Google. Why? Look at the problems the fab labs have had with the latest generation of chips and as they grow smaller the problems will probably rise. We are already close to the physical limit of transistor size. So, it is fair to assume that Moore's law will (hopefully) not outlive me.<p>So what then? I certainly hope the tech sector will not just leave it at that. If you want to continue to improve performance (per-watt) there is only one way you can go then: improve the design at an ASIC level. ASIC design will probably stay relatively hard, although there will probably be some technological solutions to make it easier with time, but if fabrication stalls at a certain nm level, production costs will probably start to drop with time as well.<p>I've been thinking about this quite a bit recently because I hope to start my PhD in ~1 year, and I'm torn between HPC or Computer Architecture. This seems to be quite a pro for Comp. Arch ;).