CNBC’s Deirdre Bosa joins 'Money Movers' to report on Google's initiative to challenge Nvidia's proprietary software.

The release of Open AI's ChatGPT has accelerated the development of artificial intelligence and warnings about its impact on society.

Rise of AI

Google is working on a new initiative, called torch TPU, to address the main barrier to broader adoption of its custom AI chips by making them easier to use for external customers. This move targets Nvidia's longstanding advantage, which comes from its integrated ecosystem of chips and CUDA software that has made it the default choice for AI development.

The initiative reflects a broader industry trend, with other major tech companies like Amazon and Meta also seeking to reduce reliance on Nvidia and gain leverage in hardware pricing. While Nvidia remains the dominant player, increased competition and improved software compatibility could shift the dynamics of AI infrastructure and supply, though the future demand for AI compute remains uncertain.

Google working on initiative to challenge Nvidia's software advantage

Google now working on a new initiative that would challenge one of NVIDIA's biggest advantages in AI. It's proprietary software. Deirdre Bosa has more in today's Tech Check segment. Morning Deirdre. Hey good morning Sarah. So Google's chip challenge to NVIDIA it's moving from hardware to software. The main knock against those custom AI chips TPUs is that they're hard to adopt. NVIDIA's advantage is its ecosystem. So that's its chips and its CUDA software. If Google can crack the software and the adoption piece this becomes a very real test for NVIDIA's moat. So Google's TPUs they started as an internal tool built to run Google's own AI as efficiently as possible and optimized around Google's own software. Now that worked really well inside of Google. But as the company started selling these chips to outside customers that created friction. TPUs were harder to drop in because they required extra engineering work. NVIDIA by contrast has CUDA. That's a software platform that is deeply embedded in how its AI is built and run making NVIDIA the easier default for pretty much anyone building. Now Reuters first reported and a source familiar confirms to me that Google is now trying to fix that with its own initiative torch TPU which is essentially trying to lower the software and engineering barriers that have held adoption back. So this doesn't mean that NVIDIA is about to be displaced but it does change the stakes. The AI race it's not just about peak performance anymore it's about margins and scale and that is where the real pressure is starting to build. So there's Google TPUs but this is part of a bigger trend as well. Amazon is pushing its own custom chips. Meta is looking for ways to lower inference costs. Every hyperscaler they want more leverage in GPU pricing negotiations. That has long been the case. So even if NVIDIA keeps most of the market here the pricing environment around infrastructure we could start to see that shift. And the big question for investors is what this chip neutrality means for the AI trade. And that is just simply the idea that companies are less locked into one vendor and they can move workloads to where compute is cheapest or most available. Be that a TPU. So in the short term guys it creates uncertainty. But here's the thing in the longer term it what it may be what actually makes the build out more sustainable. Although I wonder what you make of the idea that we've seen sort of the logistical gating issues frictions on the build out the financing frictions on the build out and now the memory price frictions on the build out. That's those are three big gating issues. I mean this has been a supply and demand issue for the past few years. Right. There's so much compute that needs to be built out. And NVIDIA GPUs have really been pretty much the only game in town. So if you're looking at a TPU you get the software piece right. Not just the hardware piece. And by the way this could be true of Google. It could be true of Amazon. That's really been NVIDIA's key moat is having that CUDA software. So if Google gets close that would be a huge win because it would mean that those custom AI chips could work outside of Google Cloud which has really been the main knock that I hear from folks in the industry that could really alleviate some of those supply constraints. Of course Carl you bring up a good point. Is the demand still going to be there. And that is like you know the trillion dollar question in all of it. Multi trillion. Yeah. Thank you.

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Google working on initiative to challenge Nvidia's software advantage

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