Does Amazon want to be an AI innovator or an AI enabler?

AWS enables thousands of other companies to run their business. Amazon has designed their own Graviton ARM CPUS and their own Trainium AI chips. You can access these through AWS for your business.

I think Amazon sees AI being used in AWS as a bigger money generator than designing new AI algorithms.

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DoesntMatter22 7 days ago | parent | next [-]

Also I think that they realize this is just a money losing proposition right now for the most part. And they're not going to have a problem getting in later when there's a clear solution. Why fight it out? I don't think they're going to miss much because they can use any models they need and as you said some of that stuff may be run on their servers

	▲	coredog64 6 days ago \| parent [-]
		I can make a case: Building their own models like Nova and Titan allow them to build up expertise in how to solve hyperscaler problems. Think of it like Aurora, where they have a generally solved problem (RDBMS) but it needs to be modified to work with the existing low-level primitives. Yes, it can be done in the open, but if I'm AWS, I probably want to jealously guard anything that could be a key differentiator.

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PartiallyTyped 7 days ago | parent | prev | next [-]

Reading comments from the appropriate VPs will illuminate the situation.. Swami is looking to democratise AI, and the company is geared towards that more than anything else.

Disclaimer; I work for amzn, opinions my own.

https://aws.amazon.com/blogs/machine-learning/aws-and-mistra...

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mips_avatar 6 days ago | parent | next [-]

I don't know what democratizing AI means, AWS doesn't have the GPU infrastructure to host inference or training on a large scale.

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lizknope 6 days ago | parent | next [-]

I started this part of the thread and mentioned Trainium but the person you replied to gave a link. Follow that and you can see Amazon's chips that they designed.

Amazon wants people to move away from Nvidia GPUs and to their own custom chips.

https://aws.amazon.com/ai/machine-learning/inferentia/

https://aws.amazon.com/ai/machine-learning/trainium/

	▲	mips_avatar 6 days ago \| parent [-]
		TBH I was just going off of that I've heard AWS is a terrible place to get h100 clusters at scale. And for the training I was looking at we didn't really want to consider going off CUDA.

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PartiallyTyped 6 days ago | parent | prev [-]

Huh? That’s quite the assertion. They provide the infrastructure for Anthropic, so if that’s not large scale idk what is.

	▲	ZeroCool2u 6 days ago \| parent [-]
		They have to use GCP as well, which is arguably a strong indictment of their experience with AWS. Coincidentally, this aligns with my experience trying to train on AWS.

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JCM9 6 days ago | parent | prev [-]

It’s unclear why Swami is put in charge of this stuff. He’s not a recognized leader in the space and hasn’t delivered a coherent strategy. However, per the article Amazon is struggling to hire and retain the best talent and thus it may just be the best they have.

	▲	code4tee 6 days ago \| parent [-]
		Who is “Swami?” Although I suppose that’s just making the point that Amazon’s folks aren’t recognized leaders in this space.

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justinator 6 days ago | parent | prev | next [-]

Selling pick axes vs. mining for gold yet again!

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dangus 6 days ago | parent [-]

I'm glad this analogy is at the top. I think that some large companies like AWS really should not try to blow money on AI in ways that only make a lot more sense for companies like Meta, Google, and Apple. AWS can't trap you in their AI systems with network effects that the other competitors can.

Companies like OpenAI and Anthropic are still incredibly risky investments especially because of the wild capital investments and complete lack of moat.

At least when Facebook was making OpenAI's revenue numbers off of 2 billion active users it was trapping people in a social network where there were real negative consequences to leaving. In the world of open source chatbots and VSClone forks there's zero friction to moving on to some other solution.

OpenAI is making $12 billion a year off of 700 million users [1], or around $17 per user annually. What other products that have no ad support perform that badly? And that's a company that is signing enterprise contracts with companies like Apple, not just some Spotify-like consumer service.

[1] This is almost the exact same user count that Facebook had when it turned its first profit.

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jsnell 6 days ago | parent [-]

> OpenAI is making $12 billion a year off of 700 million users [1], or around $17 per user annually. What other products that have no ad support perform that badly?

That's a bit of a strange spin. Their ARPU is low because they are choosing not to monetize 95% of their users at all, and for now are just providing practically limitless free service.

But monetising those free users via ads will pretty obviously be both practical and lucrative.

And even if there is no technical moat, they seem to have a very solid mind share moat for consumer apps. It isn't enough for competitors to just catch up. They need to be significantly better to shift consumer habits.

(For APIs, I agree there is no moat. Switching is just so easy.)

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chii 6 days ago | parent | next [-]

> They need to be significantly better to shift consumer habits.

i am hoping that a device local model would eventually be possible (may be a beefy home setup, and then an app that connects to your home on mobile devices for use on the go).

currently, hardware restrictions prevent this type of home setup (not to mention the open source/free models aren't quite there and difficulty for non-tech users to actually setup). However, i choose to believe the hardware issues will get solved, and it will merely be just time.

The software/model issue, on the other hand is harder to see solved. I pin my hopes onto deepseek, but may be meta or some other company will surprise me.

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dangus 5 days ago | parent [-]

I think you're super wrong about the local model issue and that's a huge risk for companies like OpenAI.

Apple products as an example have an excellent architecture for local AI. Extremely high-bandwidth RAM.

If you run an OSS model like gpt-oss on a Mac with 32GB of RAM it's already very similar to a cloud experience.

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chii 4 days ago | parent [-]

i dont have the hardware to run or try them, but from the huggingfaces discussion forums, gpt-oss seems to be pretty hard censored. I would not consider it as being a viable self-hosted LLM except for the very narrowest of domains (like coding for example).

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dangus 4 days ago | parent [-]

I'm not sure where censorship comes in with this discussion, it seems like cloud models are censored as well? And local models are frequently created that are abliterated? Correct me if I'm wrong or misunderstanding you.

Either way, it's just an example model, plenty of others to choose from. The fact of the matter is that the base model MacBook Air currently comes with about half as much RAM as you need for a really really decent LLM model. The integrated graphics are fast/efficient and the RAM is fast. The AMD Ryzen platform is similarly well-suited.

(Apple actually tells you how much storage their local model takes up in the settings > general > storage if you're curious)

We can imagine that by 2030 your base model Grandma computer on sale in stores will have at least 32GB of high-bandwidth RAM to handle local AI workflows.

	▲	chii 4 days ago \| parent [-]
		which is why i made the claim that hardware "problem" will be solved in the near future (i don't consider it solved right now, because even the apple hardware is too expensive and insufficient imho), but the more difficult problem of model availability is much, much harder to solve.

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8n4vidtmkvmk 6 days ago | parent | prev | next [-]

There does seem to be a mind share mote, but all you have to do is piss off users a little bit when there's a good competitor. See Digg to Reddit exodus.

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hiatus 6 days ago | parent | prev [-]

Which advertisers would risk having their product advertised by models that have encouraged kids to commit suicide?

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Mars008 6 days ago | parent | prev | next [-]

This is not mutually exclusive. They have home made robots and let others sell robots on their website. The same way they want to use AI and have resources to make their own. One way to use is to drive those robots. Another to enhance their web site. Current version sucks. I recently return the item because their bot told it has functionality while in fact it didn't.

	▲	rswail 6 days ago \| parent [-]
		AWS is very much not the same as Amazon the product selling website. The two are effectively separate businesses with a completely separate customer base.

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6 days ago | parent | prev [-]

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