Jensen Huang

But the problem is when you become a computing company, it's too general purpose and it takes away from your specialization.

I connected two words together.

there actually have fundamental tension.

The better computing company we become, the worse we became as a specialist.

The more of a specialist, the less capacity we have to do overall computing.

And I connected those two words together on purpose, that the company has to find...

That really narrow path, step by step by step, to expand our aperture of computing, but not give up on the most important specialization that we had.

Okay, so the first step that we took beyond acceleration was we invented the programmable pixel shader.

So that was the first step towards programmability.

You know, it was our first journey towards moving into the world of computing.

The second thing that we did was we put FP32 into our shaders.

That FP32 step, IEEE compatible FP32, was a huge step in the direction of

It was the reason why all of the people who were working on stream processors and other types of data flow processors discovered us.

And they said, hey, all of a sudden, we might be able to use this GPU that's incredibly computationally intensive, and it's now compliant with IEEE.

I can take my software that I was writing previously on CPUs, and I can see about using the GPU for that.

And which led us to create, put C on top of FP32, what we call CG.

That CG path took us to eventually CUDA.

CUDA, step by step by step.

Well, putting CUDA on GeForce, that was a strategic decision that was very, very hard to do because it cost the company enormous amounts of our profits and we couldn't afford it at the time.

But we did it anyways because we wanted to be a computing company.