| It is good to see Nvidia trying to create a virtual world like Google has. But the problem is Google has the real-life experience to use with their virtual California. But honestly Nvidia is so far behind in SDC and without any patents it is hard to see them competing. https://www.theatlas.com/charts/r1iEkmKkz Yes obvious would agree. But Google implemented late 2014 and Nvidia did NOT in 2014 or 2015 or 2016 as far as I am aware? AI is not a secretive area. So if Nvidia had something we would know. On the lack of patents puts them in a very weak position. Especially with SDC. " but note that they had to go out and buy that expertise." This is one of the more stupid things I have read in a bit on the Internet. In late 90s Larry Page was asked about using AI to make search better. He shared we are doing search to make AI better. TPUs did NOT even come from Deepmind. But honestly knowing what to buy is important. But Google is miles ahead of everyone without Deepmind. TF also did NOT come from Deepmind. So many other things. I would actually say the Brain team has done a lot more in actual production than even DeepMind. But DeepMind is Google and rather dumb comment, no offense. How old are you? Yes the TPUs are very strategic. It is how they were able to do AlphaZero. Or more importantly their new Speech offering at a reasonable cost. Without the TPUs that would not be possible and that is a strategic advantage for Google and why Amazon and everyone else will copy. Buying off the shelve can NEVER give you a strategic advantage. Google does NOT run their inference at scale on Nvidia. But also training has been moving to TPUs quickly for Google. They offer a choice but with the TPUs half the price as it shows how much better they are. You want to get TF to be the canonical solution and then use your fundamental advantages. Just business 101. "The TPU is not heads and shoulders above the competition. " We can see the TPUs are heads and shoulders better. Heck they are half the cost. Much bigger advantage than the iPhone. But more importantly they will improve far faster than anything from Nvidia. "Basically, Google is not starting from a 'commanding lead' position like Apple did. " Google lead in AI is much, much larger than any of Apple. Heck Apple market share is about 14% and Google with Android has over 80% market share. "Larger ecosystems tend to beat fully vertical stacks in the long term. " There is no Nvidia eccosystem that I am aware of? The AI eccosystem is built around TF. |
> But DeepMind is Google and rather dumb comment, no offense. How old are you?
Why are you getting all worked up? That's not an insult to Google, simply pointing out that their own organically grown corporate org (including Brain) was not adequate to do the cutting-edge research they felt they needed.
> AI is not a secretive area. So if Nvidia had something we would know. On the lack of patents puts them in a very weak position. Especially with SDC.
I disagree. Think about this the other way; if some company was quietly plugging away with large AI advances and deciding not to publish them, how would you even know? My evaluation of Nvidia's technology is based on their public presentations and the products that have already been released—products that every single AI practitioner on the planet buy and use, plus the 150+ car ecosystem partners that have decided to go with Nvidia's driving platform [1].
People who are far more deeply enmeshed in this technology than you or I have voted with their feet and decided to build their core competency for the next 5+ years on Nvidia's platform, while Waymo has maybe 2-3 major automotive partners?
> Google lead in AI is much, much larger than any of Apple. Heck Apple market share is about 14% and Google with Android has over 80% market share.
Bottom line, I definitely agree that Google is an AI leader, but I do not believe that the AI future will be run on TPUs, for the simple reason that chipmaking is a risky, expensive endeavour, and Nvidia has much more expertise than Google does in that regard, while having access to a larger partnership, ecosystem, and its own set of data and engineering.
Put it this way, the actual chipmaking stack is more important than the data stack when it comes to making chips. Just think about it—let's say you've run your thousands of NNs to benchmark the workloads on the TPU, and it turns out that CPU-TPU and TPU-TPU bandwidth is the real bottleneck. What do you do as Google? They have no expertise in building interconnects and scaling them, while Nvidia does.
Data only gets you so far, you still need to be able to do the semiconductor engineering + create partnerships, and in that regard Nvidia is light-years ahead.
To belabor the point, if the goal is to make chips, then being good at chipmaking is very important, and Nvidia is closer to Google in data, than Google is to Nvidia in chipmaking.
I will bet you that 2 years down the line, Nvidia will have abandoned its own TPU project and all major players just buying Nvidia chips, both for inferencing and training.
This is exactly the role Intel plays today in CPUs, and it's both natural and reasonable, and the largest reason is because of structural market factors, which you have never even responded to.
Google's cloud is a fraction of the size of AWS and Azure's — that means Nvidia makes far more money from Voltas than Google will ever save on the TPUs, and plough that right back into additional R&D. Business people demand a positive ROI. Where will the positive ROI from a TPU come from?
Google is and will be an AI leader. But it will certainly not be doing its own chips.
[1] https://www.nvidia.com/en-us/self-driving-cars/partners/