Thank you for being here.

I'm delighted to be here, thank you.

In honor of your return to Stanford,

I decided we'd start talking about the time when you first left.

You joined LSI Logic, and that was one of the most exciting companies at the time.

You're building a phenomenal reputation with some of the biggest names in tech, and yet you decide to leave to become a founder.

What motivated you?

Chris and Curtis.

Chris and Curtis, I was an engineer at LSI Logic, and Chris and

Curtis were at Sun.

And I was working with some of the brightest minds in computer science at the time, of all time, including Andy Bechtolsheim and others, building workstations and graphics workstations, and so on and so forth.

And Chris and Curtis said one day that they'd like to leave Sun, and they'd like me to go figure out what they're gonna go leave for.

And I had a great job, but they insisted that I figure out with them how to build a company.

And so we hung out at Denny's whenever they dropped by, which is, by the way, my alma mater, my first company.

My first job before CEO was a dishwasher, and so, and I did that very well.

And so anyways, we got together, and it was during the microprocessor revolution.

This is 1993, and 1992 when we were getting together.

The PC revolution was just getting going.

You know that Windows 95, obviously, which is the revolutionary version of Windows, didn't even come to the market yet.

And Pentium wasn't even announced yet.

And so, and this is all before, right before the PC revolution.

And it was pretty clear that the microprocessor was going to be very important, and we thought, why don't we build a company to go solve problems that a normal computer that is powered by general purpose computing can't?

And so that became the company's mission, to go build a computer, the type of computers, and solve problems that normal computers can't.

And to this day, we're focused on that.

And if you look at all the problems that, and the markets that we opened up as a result, it's things like computational drug design, weather simulation, materials design.

These are all things that we're really, really proud of.

Robotics, self-driving cars, autonomous software we call artificial intelligence.

And then, of course, we drove the technology so hard that eventually the computational cost went to approximately zero.

And it enabled a whole new way of developing software, where the computer wrote the software itself, artificial intelligence as we know it today.

So that was it, that was the journey.

Yeah.

Thank you all for coming.

Well, these applications are on all of our minds today.

But back then, the CEO of LSI Logic convinced his biggest investor,

Don Valentine, to meet with you.

He is obviously the founder of Sequoia.

Now I can see a lot of founders here edging forward in anticipation.

But how did you convince the most sought-after investor in Silicon Valley to invest in a team of first-time founders, building a new product for a market that doesn't even exist?

I didn't know how to write a business plan.

So I went to a bookstore, and back then there were bookstores.

And in the business book section, there was this book, and it was written by somebody I knew, Gordon Bell.

I should go find it again, but it's a very large book.

And the book says, How to Write a Business Plan.

And that was a highly specific title for a very niche market.

And it seems like he wrote it for 14 people, and I was one of them.

And so I bought the book.

I should have known right away that that was a bad idea, because Gordon is super, super smart.

And super smart people have a lot to say.

And I'm pretty sure Gordon wants to teach me how to write a business plan completely.

And so I picked up this book.

It's like 450 pages long.

Well, I never got through it, not even close.

I flipped through it a few pages, and I go, you know what?

By the time I'm done reading this thing, I'll be out of business.

I'll be out of money.

And Lori and I only had about six months in the bank.

We had already Spencer and Madison and a dog, and so the five of us had to live off of whatever money we had in the bank.

And so I didn't have much time, and so instead of writing the business plan,

I just went to talk to Wilf Corrigan.

He called me one day and said, hey, you left the company.

You didn't even tell me what you were doing.

I want you to come back and explain it to me.

And so I went back and I explained it to Wilf.

And Wilf, at the end of it, he said, I have no idea what you said.

And that's one of the worst elevator pitches I've ever heard.

And then he picked up the phone and he called Don Valentine.

And he called Don and he says, Don, I'm gonna send a kid over.

I want you to give him money.

He's one of the best employees LSI Logic ever had.

And so the thing I learned is you can make up a great interview.

You could even have a bad interview, but you can't run away from your past.

And so have a good past, try to have a good past.

And in a lot of ways, I was serious when I said I was a good dishwasher.

I was probably Denny's' best dishwasher.

I planned my work, I was organized, I was Nissan Plus.

And then I washed the living daylights out of the dishes.

And then they promoted me to busboy.

I was certain I'm the best busboy Denny's ever had.

I never left the station empty-handed.

I never came back empty-handed.

I was very efficient.

And so anyways, eventually I became a CEO.

I'm still working on being a good CEO.

You talk about being the best.

You needed to be the best among 89 other companies that were funded after you to build the same thing.

And then with six to nine months of runway left, you realized that the initial vision was just not gonna work.

How did you decide what to do next to save the company when the cards were so stacked against you?

Well, we started this company called For Accelerated Computing.

And the question is, what is it for?

What's the killer app?

And that came our first great decision.

And this is what Sequoia funded.

The first great decision was the first killer app was gonna be 3D graphics.

And the technology was gonna be 3D graphics.

And the application was gonna be video games.

At the time, 3D graphics was impossible to make cheap.

It was million dollar image generators from Silicon Graphics.

And so it was a million dollars, and it's hard to make cheap.

And the video game market was $0 billion.

So you have this incredible technology that's hard to commoditize and commercialize.

And then you have this market that doesn't exist.

That intersection was the founding of our company.

And I still remember when Don, at the end of my presentation,

Don was still kind of, he said, one of the things he said to me, which made a lot of sense back then, makes a lot of sense today.

He says, startups don't invest in startups, or startups don't partner with startups.

And his point is that in order for

NVIDIA to succeed, we needed another startup to succeed.

And that other startup was Electronic Arts.

And then on the way out, he reminded me that Electronic Arts' CTO is 14 years old, and had to be driven to work by his mom.

And he just wanted to remind me that that's who I'm relying on.

And then after that, he said, if you lose my money, I'll kill you.

And that was kind of my memories of that first meeting.

But nonetheless, we created something.

We went on the next several years to go create the market, to create the gaming market for PCs.

And it took a long time to do so.

We're still doing it today.

We realized that not only do you have to create the technology and invent a new way of doing computer graphics so that what was $1 million is now $300, $400, $500 that fits in a computer.

And you have to go create this new market.

So we had to create technology, create markets.

The idea that a company would create technology, create markets, defines NVIDIA today.

Almost everything we do, we create technology, we create markets.

That's the reason why people would call it a stack, an ecosystem, words like that.

But that's basically it.

At the core, for 30 years, what NVIDIA realized we had to do is, in order to create the conditions by which somebody could buy our products, we had to go invent this new market.

And it's the reason why we're early in autonomous driving.

It was the reason why we're early in deep learning.

It was the reason why we're early in just about all these things, including computational drug design and discovery.

All these different areas, we're trying to create the market while we're creating the technology.

And so that's, okay, and then we got going, and then Microsoft introduced a standard called Direct3D.

And that spawned off hundreds of companies.

And we found ourselves, a couple years later, competing with just about everybody.

And the thing that we invented the company, the technology we invented 3D graphics with, the consumerized 3D with, turns out to be incompatible with Direct3D.

So we started this company.

We had this 3D graphics thing, a million dollar thing.

We're trying to make it consumerized.

And so we invented all this technology.

And then shortly after, it became incompatible.

And so we had to reset the company or go out of business.

But we didn't know how to build it the way that Microsoft had defined it.

And I remember a meeting on a weekend and the conversation was, we now have 89 competitors.

I understand that the way we do it is not right, but we don't know how to do it the right way.

And thankfully, there was another bookstore.

And-

And the bookstore is called Fry's, Fry's Electronics.

I don't know if it's still here.

And so I had, I think I drove Madison, my daughter, on a weekend to Fry's.

And it was sitting right there, the OpenGL manual, which would define how Silicon Graphics did computer graphics.

And so it was right there, it was like $68 a book.

And so I had a couple hundred dollars, I bought three books.

I took it back to the office and I said, guys, I found it, our future.

And I handed out, I had three versions of it, I handed out.

Had a big, nice centerfold.

The centerfold is the OpenGL pipeline, which is the computer graphics pipeline.

And I handed it to the same geniuses that I founded the company with.

And we implemented the OpenGL pipeline like nobody had ever implemented the OpenGL pipeline, and we built something the world never seen.

And so a lot of lessons are right there.

That moment in time for our company gave us so much confidence.

And the reason for that is you can succeed in doing something, inventing a future, even if you were not informed about it at all.

And it's kind of my attitude about everything now.

When somebody tells me about something and I've never heard of it before, or

I've heard of it, never don't understand how it works at all.

My first thought is always, how hard can it be?

And it's probably just a textbook away.

You're probably one archive paper away from figuring this out.

And so I spent a lot of time reading archive papers.

And it's true, it's true.

You can, now of course, you can't learn how somebody else does something and do it exactly the same way and hope to have a different outcome.

But you could learn how something can be done, and then go back to first principles.

And ask yourself, given the conditions today, given my motivation, given the instruments, the tools, given how things have changed, how would I redo this?

How would I reinvent this whole thing?

How would I design it?

How would I build a car today?

Would I build it incrementally from 1950s and 1900s?

How would I build a computer today?

How would I write software today?

Does it make sense?

And so I go back to first principles all the time, even in the company today, and just reset ourselves.

Because the world has changed.

And the way we wrote software in the past was monolithic, and it's designed for supercomputers, but now it's disaggregated, so on, so forth.

And how we think about software today, how we think about computers today, how we think, just always cause your company, always cause yourself to go back to first principles, and it creates lots and lots of opportunities.

Yeah, the way you applied this technology turns to be revolutionary.

You get all the momentum that you need to IPO, and then some more, because you grow your revenue nine times in the next four years.

But in the middle of all of this success, you decide to pivot a little bit the focus of innovation happening at NVIDIA, based on a phone call you have with this chemistry professor.

Can you tell us about that phone call, and how you connected the dots from what you heard to where you went?

Remember, at the core, the company was pioneering a new way of doing computing.

Computer graphics was the first application.

But we always knew that there would be other applications, and so image processing came, particle physics came, fluids came, so on, so forth.

All kinds of interesting things that we wanted to do.