[jacksmith21006]

Strongly disagree. If Google is able to offer at about 1/2 the cost using their own silicon versus AWS using Nvidia that is all about the silicon difference.

But we also have the V1 TPU paper and can see the TPUs are able to use less joules per inference compared to an older Nvidia architecture. Was not that close. Just makes sense Google V2 TPUs would do the same.

Hope Google does a V3 TPU and then will share a V2 TPU paper like they did on V1 of the TPUs.

What is far more impressive of the TPUs is

https://cloudplatform.googleblog.com/2018/03/introducing-Clo...

If really doing 16k a second through a NN and at a price you can offer generally now that is incredible. I want this paper even more so.

[nightski]

What makes you so sure it is all the silicon difference and not just AWS pricing their product at a more profitable price point?

These costs also ignore transferring and storing massive data sets in the cloud. In general the cloud is a huge pain and I'd avoid it like the plague unless I was caught and really, really needed the scalability. But even then that only works if you have a scalable implementation of the algorithm you are working on.

[shaklee3]

Maybe, maybe not. They have the advantage that they make the hardware, so they're not paying as much retail as nvidia is charging them for their cards. I don't think there's any way you can say the TPU is cheaper compared to buying your own system. If Google decides to release it to the public, that's a different story. Also, keep in mind that Google allows you to mix and match the CPU core count to GPU, whereas AWS doesn't. It's possible that the Google cloud price with fewer CPU cores will be much cheaper than the AWS instance.

[jacksmith21006]

That is true. But the cost of running is where all the cost is at really not so much in making the chips.

Yes I can say it is a lot cheaper. That is what this article is all about.

You can do about twice the images per dollar using the TPUs with GCP versus using Nvidia with AWS.

Or what am I missing?

BTW, Google has released to the general public. What are you talking about?

"Google’s AI chips are now open for public use"

https://venturebeat.com/2018/02/12/googles-ai-chips-are-now-...

[shaklee3]

You misunderstood. They released them to the public on GCP only. Nvidia's cards are released to the public as a hardware device that you can customize around. Big difference.

[jacksmith21006]

Yes in the cloud as you would expect in 2018. Available to the general public.

[shaklee3]

They announced in 2016 they had TPUs. So no, I would not expect that 2 full years later they're just now being available in the public cloud. These are not new products to them; they likely just don't want to deal with supporting them in different configurations.

[ndesaulniers]

> they likely just don't want to deal with supporting them in different configurations.

It is a lot of work. But mainly that TPUv1 only did inference while TPUv2 does training+inference.