NVidia CEO also said:
"
And so I think people now recognize that AI computing is a very software-rich problem and it is a supremely exciting AI problem, and that deep learning and GPUs could add a lot of value. And it's going happen in 2017. It's not going to happen in 2021. And so I think number one. Number two, our strategy is to deploy a one architecture platform that is open that car companies could work on to leverage our software stack and create their network, their artificial intelligence network. And then we would address everything from highway cruising, excellent highway cruising to all the way to full autonomous to trucks to shuttles. And using one computing architecture, we could apply it for radar-based systems or radar plus cameras, radar plus cameras plus lidars, we could use it for all kinds of sensor fusion environments.
And so I think – our strategy, I think, is really resonating well with the industry as people now realize that we need the computation capability five years earlier. That we – that it's not a detection problem, but it's an AI computing problem and that software is really intensive. That these three observations, I think, has put us in a really good position."
Whose software is most significant in solving this AI problem? Tesla's? Or NVidia' software stack?
Tesla isn't using any of NVIDIA's software stack. But other companies might. Tesla chose NVIDIA's chip for its hardware performance characteristics, and NVIDIA is promoting it as the Drive PX2 platform. Other companies might choose to go with the software parts of the Drive PX2 platform, or hardware platforms themselves as a means to try to jump start. NVIDIA obviously has their own things to sell, even if Tesla's case is really only using the base layer of their stack (in vehicle). Outside of vehicle, we don't know.