The big difference is Google works top down. So Google comes up with WaveNet as an example. That then causes a need to optimize the entire stack to be possibl

The big difference is Google works top down. So Google comes up with WaveNet as an example. That then causes a need to optimize the entire stack to be possible to offer at scale. So WaveNet part of the Google Assistant and things like Duplex. But Nvidia silicon is just not going to make it possible. So Google does the TPUs as it just would not be possible to do at a reasonable price with Nvidia. They are doing 16k cycles through a NN in real-time and competing against a far less compute intensive technique. Now do not get me wrong I am long Nvidia and been for a while. Bit disapointed on the hit after an incredible earnings report. I think they will do well from a investor marketing standpoint as really the only alternative to Google hardware. But they have a fundamental disadvantage. They just do not have the applications like Google. They do NOT have the data to iterate like Google. It is why they appears to be 2 generations behind Google. What is the goal of Nvidia? It is hardware for hardware sake? IMO, it should be driven top down and just do not see that happening at Nvidia. Is their goal the singularity? Versus Google clearly wants to create the singularity and the silicon is in support. That is a very different calculus compared to Nvidia. We can see it so strongly this week. The Google Keynote was all about AI applications. Then the TPUs are too support. Take a look at the duplex video for example. That is the focus and the silicon is what makes it possible. But the more success for Google and presentations like Duplex this week and the buzz across the Internet helps Nvidia if the goal is investing. But from an actual technical solution it just points out the problem for Nvidia that much stronger.