Not aware of Nvidia having any where the number of neural networks in production or the nearly the number of users.

Not even sure where they are hosting them or even what they do? How about some color as you have me curious?

Have watched videos of Jensen but also watched an excellent almost 2 hour presentation from one of their VPs. He said a lot of things that were in the Google TPU paper which I found a bit funny. How you can use 8 bits and integers for inference for example. Said to me these guys are trying to catch up.

The problem is Amazon has that data NOT Nvidia. It is not in Amazon best interest to help Nvidia this is my exact point. The entire dynamics of the chip business have changed. You will see Amazon do their own just like Google has.

Once Google did the gen 1 TPUs they set the direction of you just can NOT buy off the shelve and compete long term.

The silicon is strategic for AI.

MS went the wrong direction in using a FPGA solution in addition to using Nvidia. But once again no data for Nvidia.

Market cap does not give you the money. But Google in 2018 will spend about 2x Nvidia 2017 sales! Yes you read that correct. Google on R&D will spend 2x Nvidia 2017 sales!

Google profits will be over 4x Nvidia total 2017 sales.

Once again Nvidia does NOT do the entire stack. I am not aware of any algorithm breakthroughs that came from Nvidia. I can not even name one AI expert Nvidia.

But the score board is papers excepted at NIPS. Nvidia did NOT get a single paper accepted that I saw at the conference?

Versus Google had more than anyone. 9% of all the paper accepted came from Google.

https://medium.com/machine-learning-in-practice/nips-accepte...

If Nvidia is playing in the entire stack how could they NOT get a single paper accepted at NIPS?

Or did I miss it?

If we look at Self Driving cars one of the most important AI applications Nvidia does not even show up on patents? Once again Google ahead by a mile.

https://www.theatlas.com/charts/r1iEkmKkz

Something in your post does NOT add up? Why if Nvidia is a player in the stack besides the silicon why do they NOT show up any where?

Google deploys both, TPUs and Nvidia, for a number of reasons I suspect.

The biggest is they want TF to be the canonical framework for AI and they MUST show not favoring their own solution until it is a done deal which is getting close.

In the TF will never run as well on Nvidia as they will on the TPUs. We can see hit here with about 1/2 the cost using the TPUs over Nvidia.

It is like saying Android would run as well as iOS on the Apple processors. It is all about controlling the entire stack like Apple has done and Nvidia is just not in a position to be able to.

Makes no sense to buy the processors so would not make any sense for Google to sell them to others. Not going to ever see that happen.

But I do think it is possible Google will sell the PVCs.

The ultimate problem is Nvidia is in perceptual catching up. Right now the big new thing that came from Hinton is Capsule networks and using dynamic routing. Google will have that optimized in silicon long before Nvidia will.

I suspect it will create the need for a different approach how you access memory in chip architecture.

But Capsule networks are heavy computationally and so silicon will matter a lot. Google has the algorithms and how they want to use in production at scale and then the money to execute in supporting in silicon. They just move way too fast for Nvidia to ever be able to catch up.