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Published · transcript-backed

David Rosenthal: evaluation

6 Sept 2023 Acquired Nvidia Part III: The Dawn of the AI Era (2022-2023)

“I think in the current state of things, it’s even more favorable to Nvidia than iOS versus Android, because Nvidia has had first dozens and then hundreds and now thousands of engineers working on CUDA for 16 years.”

— David Rosenthal

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Everything needed to verify it.

Speaker
David Rosenthal
Attribution
Verified speaker
Claim type
evaluation
Recorded
6 Sept 2023
Publisher
Acquired

Transcript context

…I think this is exactly the right framing here, that Nvidia is the Apple of AI and PyTorch is Android because it’s open source and it’s got a bunch of different companies that care about it. OpenCL is the Android as it pertains to graphics, but it’s pretty bad and pretty far behind. ROCm is the CUDA competitor made by AMD for their hardware. But again, new, not a lot of adoption. They’re working on it, but they’ve open sourced that because they realize they can’t go directly head-to-head with Nvidia. They need a different strategy. But yes, they are absolutely running the Apple playbook here. I think in the current state of things, it’s even more favorable to Nvidia than iOS versus Android, because Nvidia has had first dozens and then hundreds and now thousands of engineers working on CUDA for 16 years. Meanwhile, the Android equivalent out there in the open source ecosystem has only just been getting going. If you think about the delta of the timeline between iOS and Android, it was a year-and-a-half, two years. There are probably at least 10, probably closer to 15 year lead than Nvidia has. We talked to a few people about this and we’re like, oh, what’s going on in the open source ecosystem? Is there an Android equivalent? Even the most bullish people we talked to were like, oh yeah. Now that Facebook has really moved PyTorch into a foundation and outside of Facebook, that means that other companies can now contribute a couple of dozen engineers to work on it. And you’re like, cool. AMD is going to contribute a couple of dozen, maybe a hundred engineers to work on PyTorch. And so will Google, and so will Facebook, and so will everybody else. Nvidia has thousands of engineers working on CUDA 10 years ahead. I sent you this graph, David, of my estimated number of employees working on CUDA per year since inception in 2006. If you look at the area under the curve and just take the integral, it’s approximately 10,000 person years that have gone into CUDA. Good luck.…

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