Jensen Huang: evaluation

Transcript context

…Install base is everything. Install base defines an architecture. Not… Everything else is secondary, okay? And so there were other architectures at the time. CUDA came out, OpenCL was here. There were… You know, there’s several other competing architectures. But the thing that… The decision that we made that was good was we said, “Hey, look, ultimately it’s about install base and what is the best way we could get a new computing architecture into the world? ” By that timeframe, GeForce had become successful. We were already selling millions and millions of GeForce GPUs a year, and we said, “You know, we, we ought to put CUDA on GeForce and put it into every single PC whether customers use it or not, and use it as a starting point of cultivating our install base.” Meanwhile, we’ll go and attract developers, and we went to universities and wrote books and taught classes and put CUDA everywhere. And eventually people discover… And at the time, the PC was the primary computing vehicle. There was no cloud, and we could put a supercomputer in the hands of every researcher in school, every scientist, you know, every engineering school, every… or every student in school, and eventually something amazing will happen. Well, the problem was CUDA increased our cost of that GPU, which is a consumer product, so tremendously, it completely consumed all of the company’s gross profit dollars. And so at the time, the company was probably, you know, worth, I don’t know, at the time, eight… Was it like $8 billion or something? Like six, $7 billion or something like that. After we launched CUDA, I recognized that it was going to add so much cost, but it was something we believed in. You know, our market cap went down to like one and a half billion dollars. And so we were down there for a while and we clawed our way back slowly, but we carried CUDA on GeForce. I always say that NVIDIA is the house that GeForce built, because it was GeForce that took CUDA out to everybody. Researchers, scientists, they discovered CUDA on GeForce because they were all, you know… Many of ’em were gamers. Many of them built their own PCs anyways. In a university lab, many of them built clusters themselves, you know, using PC components. And, and so that, you know, that’s kind of how we got going. And then that became the platform and the foundation for the deep learning revolution.…

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