>energy efficiency is the next key metric, and that specialized hardware (like TPU) might be the future.
This is nonsense pushed forward by large corporations who want to own all your data and computational capacity.
This is nonsense pushed forward by large corporations who want to own all your data and computational capacity.
Point one: Indeed, untold millions of dollars can be saved by improving data center efficiency. But if the processors are in desktops instead, where the price pain isn't actually enough to drive improvements in efficiency, then we as a society just pay a higher power bill... Furthermore, data center power tends to be greener than general purpose city grids.
Point two: they could have as easily said GPUs to avoid the fear of data centre only proprietary lock in... The point is the same: we seem to have hit the point where specialized linear algebra coprocessors make a huge difference.
You have something reversed here.
Hardware companies that make consumer devices are pumping barrels of money in improving CPU power usage to enable longer battery life on mobile devices.
Google, on the other hand, promotes insanely power-hungry neural nets as the future of computing, because that's the kind of future that gives them the deciding edge in the market.
His chart shows TPU with ~80x the performance/watt of a CPU, indicating the potential advantages of domain-specific architectures over general purpose for specific applications.
None of this should be surprising to anyone who uses a GPU.