There are various bits of this blog post that detail how they’re making it easier for devs to use TPUs, particularly the discussion of TorchTPU and the attendant link. That being said if you’re looking for a link to a tutorial I think it’s easily findable on Google. “Tpu tutorial Google cloud” or “Tpu developer hub” would be good queries. For example [this](https://docs.cloud.google.com/compute/docs/tpus/quickstart-c...) is at least somewhat responsive.
The quote is:
“As TPU demand grows from AI labs, capital markets firms, and high-performance computing applications, we'll begin to deliver TPUs to a select group of customers in their own data centers in a hardware configuration to expand our addressable market opportunity.”
It’s a competitive advantage which allows them to deliver lower cost per inference. If quality continues to asymptote, best value becomes most interesting to consumers.
Then again, if they can provide competition to Nvidia, it may force Nvidia to lower prices across the board.
Every TPU they keep for Google Cloud reduces the need to buy GPUs from Nvidia. Or really, in this market, means they have additional ability to support AI compute beyond what they can buy from Nvidia.
They are finally starting to. Oracle just announced a week or so ago that they're going to be introducing TPUs to their cloud next year for customers to use.
Interesting times ahead with a number of chip makers now vying for this market. TPUs are a mature chip now which gives some strong advantage. At the same time as the TPU announcement, they also mentioned they'll be deploying Cerebras systems as well.
Because it has been historically strongly coupled to the Google infra, both hardware and software. Now the situation has improved and now they are selling this to external clients, though it is still in a limited fashion.
Plenty of people and firms use TPUs, both directly and indirectly. You can rent them via Google Cloud. Apple Intelligence and Anthropic both use them. And of course your Gemini traffic is using the TPUs as well.
This is a marketing announcement, it's got the right level of info for the target audience. If you want more technical detail there's loads available elsewhere online.
They were originally a separate company (and I think still based in the UK) so it's a bit more separate than probably random other internal departments
There does come a point where if you're in the follow up article discussing what's new in 2 new variants of the 8th generation of a niche product for that vendor it stops being reasonable from them explaining what everything means each time and starts being reasonable to either click the links to the earlier introduction or search around for it to get a proper understanding as if you didn't know "TPU" was "Tensor Processing Unit" then there is a lot more you want to know before reading this article.
Also, it doesn't just come out and say what the peak throughput of these chips are, just 2.7x the prior generation. This is one of those things that Apple does every Mac release--it's always some big dumb bar that is bigger or some line up and to the right that has absolutely no explanation.
I disagree. I think you're saying that because this is your niche and finding the term isn't difficult for you.
However, consider the Tolkien community. I enjoy lord of the rings and want to know more. But there's an absurd acronym for another book (home) that no one ever expands in that community. And it's not in the wiki's and it's not in Google (bc what do you get if you google "tolkien home"?) it was intentionally frustrating for me to figure out what that acronym was. The people in the tolkien community also adopted your pov and just wouldn't help, expecting new people to bootstrap themselves. It was not a fun experience. These styling conventions aren't for the 99% of the time they're for the 1% of the time.
The experience can't have been that bad, you just used "bc" and "pov" without batting an eye. Reasonably so, because it'd be crazy to expand and explain what everything means all the time when it takes so little effort for anyone who wants to to familiarize themselves yet is so convenient for everyone who already knows.
And what I'm saying here is different from "you should not care to ever expand acronyms/abbreviations/initialisms" but that does not necessarily mean your goal should be that it's "fun" for every possible reader. It's about what's reasonably efficient for everyone likely to read the article. If 50%, 10%, 1%, and 0.1% of your audience will understand an acronym, abbreviation, or piece of jargon then it has different implications for what the right balance of reasoning is. Not every piece need target a generic audience, not every acronym need assume the reader can't be bothered to learn anything not spelled out for them in the page, and not everything is equally hard to figure out when it's not spoon-fed to the reader.
And, again, what is "Tensor Processing Unit" going to gain you if you don't already know that's what TPU stands for in the context of this article? I.e. who knows what a tensor is and why youd have a processor for them yet gains something by the acronym being expanded? People who don't know what a TPU is should start with a different article completely, probably several, and then read this one. Expecting every piece of writing should assume no knowledge blocks more knowledge than it helps share.
It is good writing practice, even in technical documents, to spell out an acronym the first time it is used in your document.
> We first designed Tensor Processing Units (TPUs) more than a decade ago motivated by Google’s...
Literally all it takes. Basically free and it helps both broaden your audience and avoid mistakes. Also, high key, it is a great opportunity for a back link to https://cloud.google.com/tpu, which you'd think Google would care about.
I see your point, but it's good practice to introduce abbreviations at least once before using them. I even still see GPU defined at least once in most professionally written articles.
To be fair, does it matter? It seems pretty clear what they are to be used for. Does Nvidia define what CUDA is anymore? It doesn't really matter what the actual acronym is.
Full disclosure: I work in this space at Google, but my opinions here are my own.
You benefit indirectly because it gives Nvidia a competitor in the datacenter space and takes some pressure off the GPU market. You can also rent them on GCP.
As someone interested in 3d-printing, and not particularly interested in AI chips, having a (Tensor Processing Unit) somewhere in the title would have been nice...
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[ 783 ms ] story [ 2696 ms ] threadThey could still be renting them out.
Then again, if they can provide competition to Nvidia, it may force Nvidia to lower prices across the board.
And even if Google sold them, they probably won't sell any affordable ones. Nvidia sells DGX Spark, but who can afford to buy them?
https://www.msn.com/en-us/technology/tech-companies/oracle-e...
Interesting times ahead with a number of chip makers now vying for this market. TPUs are a mature chip now which gives some strong advantage. At the same time as the TPU announcement, they also mentioned they'll be deploying Cerebras systems as well.
> TPUs are now a rapidly growing business with nearly 100 customers
‘Nearly 100 customers’ in 10 years isn’t very impressive
So basically Google has both SOTA models (Argon and Carbon and top of the line TPUs, but...
Google is in trouble?
(reading HN search is dead and hence Google is done)
And how does each compare to their NVDA price equivalent?
You are not the target market.
/sarcasm at the unoriginal naming scheme
I love it when companies expose their org charts publicly like this. As if anybody cares that they think about Google and DeepMind as different.
(It's "Tensor Processing Unit".)
Also, it doesn't just come out and say what the peak throughput of these chips are, just 2.7x the prior generation. This is one of those things that Apple does every Mac release--it's always some big dumb bar that is bigger or some line up and to the right that has absolutely no explanation.
would it kill you to use an internet search engine (such as google)?
However, consider the Tolkien community. I enjoy lord of the rings and want to know more. But there's an absurd acronym for another book (home) that no one ever expands in that community. And it's not in the wiki's and it's not in Google (bc what do you get if you google "tolkien home"?) it was intentionally frustrating for me to figure out what that acronym was. The people in the tolkien community also adopted your pov and just wouldn't help, expecting new people to bootstrap themselves. It was not a fun experience. These styling conventions aren't for the 99% of the time they're for the 1% of the time.
But yeah in general it's nice to at least explain the acronym once
And what I'm saying here is different from "you should not care to ever expand acronyms/abbreviations/initialisms" but that does not necessarily mean your goal should be that it's "fun" for every possible reader. It's about what's reasonably efficient for everyone likely to read the article. If 50%, 10%, 1%, and 0.1% of your audience will understand an acronym, abbreviation, or piece of jargon then it has different implications for what the right balance of reasoning is. Not every piece need target a generic audience, not every acronym need assume the reader can't be bothered to learn anything not spelled out for them in the page, and not everything is equally hard to figure out when it's not spoon-fed to the reader.
And, again, what is "Tensor Processing Unit" going to gain you if you don't already know that's what TPU stands for in the context of this article? I.e. who knows what a tensor is and why youd have a processor for them yet gains something by the acronym being expanded? People who don't know what a TPU is should start with a different article completely, probably several, and then read this one. Expecting every piece of writing should assume no knowledge blocks more knowledge than it helps share.
> We first designed Tensor Processing Units (TPUs) more than a decade ago motivated by Google’s...
Literally all it takes. Basically free and it helps both broaden your audience and avoid mistakes. Also, high key, it is a great opportunity for a back link to https://cloud.google.com/tpu, which you'd think Google would care about.
You benefit indirectly because it gives Nvidia a competitor in the datacenter space and takes some pressure off the GPU market. You can also rent them on GCP.
> TPU 8i Max for massive context windows and the highest compute density per rack, and TPU 8tx for secure and confidential inference
You had one job, Google
https://cloud.google.com/blog/topics/ai-infrastructure/intro...
https://github.com/Niko1221/Strata/blob/main/docs/HOW_IT_WOR...