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Not just AWS, looks like Anthropic uses it heavily as well. I assume they get plenty of handholding from Amazon though. I'm surprised any cloud provider does not invest drastically more into their SDK and tooling, nobody will use your cloud if they literally cannot.




Well AWS says Anthropic uses it but Anthropic isn’t exactly jumping up and down telling everyone how awesome it is, which tells you everything you need to know.

If Anthropic walked out on stage today and said how amazing it was and how they’re using it the announcement would have a lot more weight. Instead… crickets from Anthropic in the keynote


AWS has built 20 data centers in Indiana full of half a million Trainium chips explicitly for Anthropic. Anthropic is using them heavily. The same press announcement that Anthropic has made about Google TPUs is the exact same one they made a year ago about Trainium. Hell, even in the Google TPU press release they explicitly mention how they are still using Trainium as well.

Can you link to the press releases? The only one I'm aware of by Anthropic says they will use Tranium for future LLMs, not that they are using them.

This is the Anthropic press release from last year saying they will use Trainium: https://www.anthropic.com/news/anthropic-amazon-trainium

This is the AWS press release from last month saying Anthropic is using 500k Trainium chips and will use 500k more: https://finance.yahoo.com/news/amazon-says-anthropic-will-us...

And this is the Anthropic press release from last month saying they will use more Google TPUs but also are continuing to use Trainium (see the last 2 paragraphs specifically): https://www.anthropic.com/news/expanding-our-use-of-google-c...


There is no press release saying that they are using 500k trainium chips. You can search on amazon's site.

In the subheading of https://www.aboutamazon.com/news/aws/aws-project-rainier-ai-... Unless there are other Project Ranier customers that it's counting.

I met a AWS engineer a couple of weeks ago and he said Trainium is actually being used for Anthropic model inference, not for training. Inferentia is basically defected Trainiums chips that nobody wants to use.

> Anthropic isn’t exactly jumping up and down telling everyone how awesome it is, which tells you everything you need to know.

You can’t really read into that. They are unlikely to let their competitors know if they have a slight performance/$ edge by going with AWS tech.


With GCP announcing they built Gemini 3 on TPUs the opposite is true. Anthropic is under pressure to show they don’t need expensive GPUs. They’d be catching up at this point, not leaking some secret sauce. No reason for them to not boast on stage today unless there’s nothing to boast about.

Yes, but Google benefit from people using their TPUs, while Anthropic gains nothing unless AWS throws money at them for saying it.

This.

Anthropic is not going to interrupt their competitors if their competitors don't want to use trainium. Neither would you, I, nor anyone else. The only potential is downside. There's no upside potential for them at all in doing so.

From Anthropic's perspective, if the rest of us can't figure out how to make trainium work? Good.

Amazon will fix the difficulty problem with time, but that's time Anthropic can use to press their advantages and entrench themselves in the market.


I am not sure, I would imagine enthusiastic quotes will lead to huge discounts and in that scale that matters

Striking a deal with a competitor (AZURE) does though.

> I'm surprised any cloud provider does not invest drastically more into their SDK and tooling

I used to work for an AI startup. This is where Nvidia's moat is - the tens of thousands of man-hours that has gone into making the entire AI ecosystem work well with Nvidia hardware and not much else.

It's not that they haven't thought of this, it's just that they don't want to hire another 1k engineers to do it.


>I'm surprised any cloud provider does not invest drastically more into their SDK and tooling, nobody will use your cloud if they literally cannot.

Building an efficient compiler from high-level ML code to a TPU is actually quite a difficult software engineering feat, and it's not clear that Amazon has the kind of engineering talent needed to build something like that. Not like Google which have developed multiple compilers and language runtimes.




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