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Published · transcript-backed

David Rosenthal: belief

20 Apr 2022 Acquired Nvidia Part II: The Machine Learning Company (2006-2022)

“We can tune it to exactly our use cases, sort of similar to the Cerberus Graphcore bear case on NVIDIA. I think in both of these cases, it hasn't happened yet.”

— David Rosenthal

Source trail

Everything needed to verify it.

Speaker
David Rosenthal
Attribution
Verified speaker
Claim type
belief
Recorded
20 Apr 2022
Publisher
Acquired

Transcript context

…They paint the bull case for us when they say there's a $100 trillion future and we're going to capture 1% of it. There's $300 billion from automotive, there are the four or five segments that add up to a trillion dollars of opportunity. Sure, that's a very neat way with a bow on it and a very wishy-washy hand-wavy way of articulating it. The question sort of becomes, where does AMD fall on all this? There are legitimate second place competitors for high-end gaming graphics and I think will continue to be. That feels like a place where these two are going to keep going head to head. The bear case is that there's a TikTok rather than a durable competitive advantage for NVIDIA, but most high-end games, you can play on both AMD and NVIDIA hardware at this point. The question for the data center is, is the future for these general purpose GPUs that NVIDIA continues to modify the definition of GPU to include specialized functions as well, all this other stuff they're putting in their hardware? Or is there someone else who is coming along with a completely different approach to accelerated computing where they're accelerating workloads off the GPU on to something new, like a Cerebrus or a Graphcore that is going to eat their lunch in the enterprise AI data center market? That's an open question. It's interesting. People have been talking about that for a while. The other big bear case that people have been talking about, again, for a while now is the big, big customers of NVIDIA that are paying them a lot of money—the Teslas, Googles, Facebooks, Amazons, and Apples. Not just paying them a lot of money and getting assets of value of that, they're paying high gross margin dollars to NVIDIA for what they're getting. That those companies are going to want to say, you know, it's not that hard to design our own silicon to bring all this stuff in house. We can tune it to exactly our use cases, sort of similar to the Cerberus Graphcore bear case on NVIDIA. I think in both of these cases, it hasn't happened yet. There have been a lot of people who have made a lot of noise, but there have been few that have executed on it. Apple has their own GPUs on the M1s. Tesla's switching hasn't happened yet, but switching for the full self-driving, they're doing their own stuff on the car.…

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