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Nvidia's sustained investment in a real software stack (CUDA) turned GPUs from niche graphics chips into general-purpose computing devices that could take on HPC and eventually AI, while Intel's competing x86-based Larrabee project was killed the week after Gelsinger first left the company.

Gelsinger credits Nvidia's steady build-out of the CUDA software stack for turning GPUs into general-purpose computing devices, while Intel's rival Larrabee effort was killed right after he left the company. ✦ AI generated

Pat Gelsinger · All-In Podcast · 2026-07-15 · original ↗

starts at this moment · 8:32

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Jensen decides he's going to go all in making these video cards... Was that luck or skill or a combination of both?

When they started to build a real software stack with it — this CUDA thing and SIMT as a technology — it just sort of kept getting a little bit better and a little bit better... I had a project at Intel, Larrabee, where we were trying to take the x86 and essentially do the same thing, and in my first departure from Intel the project was killed a week after I left.

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8:32CPUs, uh, at Intel, we sort of scoffed at his machines. Yeah. >> Right. You like, oh, that's a graphic machine. You, you know, there's some gamers who want to use that kind of stuff, right? You know, it was always the big CPU and those little GPUs. But when they started to build a real software stack, Yes. with it, right? You know, sort of, okay, this CUDA thing and

8:52SIMT as a technology, you know, uh, you know, uh, multi-threading and so on. And it just sort of kept getting a little bit better and a little bit better and it was a little bit jobslike in that way. You know, we're just making it better every release and it's becoming more robust and all of a sudden, you know, the crazy, you know, uh, Japanese HPC guys said, "Hey, we could take those

9:15graphics cards and maybe start using them in HPC." H, >> right? you know, and that was sort of defining moment where it wasn't just about doing graphics anymore. This was a more computationally dense platform to start attacking some of the world's most interesting workloads. And I think Jensen would agree that was a defining moment and them sort of saying, "Oh, these aren't just graphics cards anymore. You know, these are

9:39generalpurpose computing devices that can start applying to these other uh workloads." And you know AI was you know had gone through what its fifth nuclear winter by that point. We're just like man you know you know this is never going to matter right we're never going to you know get the breakthroughs but the community around it was continuing to develop uh you know for it and the

10:01CUDA software kept getting better uh generation by generation and uh you know I had a project at Intel Larabe right where we were trying to take the x86 and essentially do the same thing right you know for it and you know in my first departure from Intel the project was killed a week after I left >> huh >> and the world would have been so much different right I

10:24>> I mean it really I think it's illustrative of [snorts] illustrative of what continuous innovation taking some risks and doing that fundamental research and the compounding power of technology because I think it was William Gibson who said the street finds its own use for technology like Nvidia did not predict that this Bitcoin project would take over and that this would be the best way to do those

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