CNBC’s MacKenzie Sigalos reports on Amazon's 2025 re:Invent conference where the company unveiled major upgrades to its AI stack.

At the re:Invent conference, Amazon Web Services CEO Matt Garman introduced significant advancements in Amazon's AI infrastructure. The company announced the launch of Tranium 3 chips, which offer four times the compute memory bandwidth and energy efficiency of the previous generation, and shared details about the upcoming Tranium 4 chips, designed for greater flexibility and efficiency.

Amazon also debuted its Nova suite of large language models, including Nova 2 and Nova Forge, as well as Frontier Agents capable of extended autonomous operation. These developments are part of Amazon's strategy to compete more effectively in the AI and cloud sectors, diversify beyond NVIDIA hardware, and potentially open its chips to third-party buyers.

Amazon unveils new 'trainium' chips, AI model at re:Invent conference

Hey there, Carl. So AWS CEO Matt Garman is on stage now, unveiling major upgrades across the Amazon AI stack. Now let's start with what's increasingly become the deciding factor in both the cloud and AI wars, those in-house chips. AWS is rolling out its new Tranium 3 chips. The headline here is performance and price, roughly four times the compute memory bandwidth and energy efficiency of the prior generation. So customers can train much larger models faster and at a lower cost. Big users like Anthropic are already using Tranium to cut AI compute bills by as much as half. But we're also getting new details on Tranium 4, their next chip in development that promises even bigger jumps in speed and memory. And it's being designed to plug into the same high-speed racks as NVIDIA GPUs so that customers can mix and match everything in one giant cluster. All right, second, Amazon. It is debuting a new suite of its Nova LLM models as they look to get competitive in the model race. Nova 2 is what you'd think of as the rival to Gemini in chat GBT. Nova Forge is basically for the enterprise customer that wants to run proprietary data in-house on its own LLM. So this is very much the build your own frontier model. And then finally, Amazon, it is introducing Frontier Agents. They can run for days with virtually no human intervention. That's supposed to be a huge perk for enterprise customers operating on Amazon's cloud business. In all of this, it is very much a big swing at convincing investors that Amazon is a formidable contender in the full-stack AI race. Guys? This is all so interesting, Mac. I'm wondering a little bit more about the Tranium chips. I guess the first question is, are those details for the Tranium 3 as expected? And then, what do you make of the fact that they're already talking about number 4? I know you said no release date, but does that sort of take the wind out of the sails of number 3? It's a good question. And part of what the strategy is here is showing that there's even greater efficiency ahead, that these Tranium 4 chips are already in development. And I think that also comes at a very sensitive time for the company where Google has been getting all this great publicity around its in-house silicon, the TPU. But keep in mind, they were three years earlier to the AI race in terms of developing their own chips in-house. And so Amazon is saying, we've got a playbook. We're looking ahead. This has six times greater efficiency, the Tranium 4 chip. It is coming down the pike. And what's really notable here is they talked about this fungibility where you don't have to use Tranium 4 in the context of being an AWS customer. You can plug it into other racks. And it goes to this larger question of, will these companies, whether it's Google, whether it's Amazon, start to sell their in-house chips to third-party buyers instead of make them use it in the context of their cloud program? It doesn't seem like that long ago, going vertical in semis, remember Apple? I mean, it seemed like such a weird idea. And so labor-intensive, but a couple years later, Mac, I mean, it's obviously a no-brainer now. And completely vital to being a competitor not just in the cloud wars but to winning these AI compute loads. You very much want to have a diversification strategy away from NVIDIA just on price alone. This is all very fascinating, Mac. Thanks so much, and thanks for being there.

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