Spent a long time at Intel.
Probably one of the greatest American companies ever. And then absolutely went off the rails and got absolutely demolished by Nvidia, TSMC, and I guess Apple to a certain extent. So you had this incredible Intel inside moment. We bought our computers based on, you know, hey, the Pentium and that sound.
Intel inside, baby. Intel insideum.
And so, let's talk about how things went wrong. What went right and then how did it and you were there for a long time. You took a break and then you came back. But there seemed to have been some critical mistakes that we can learn from. So, let's just embrace it and go right into it. Tremendous success as an American company coming back now I think reasonably but when we look back on it and we do our post-mortem, what were the mistakes and what would we change in terms of the direction of that company?
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Having spent so much of my life there, you know, I view it. I joined when I was 18. I went through puberty at Intel, right? I joke, right? I was just like, you know, I am so early. Grove, Noise, Bar Barrett, right? And they were the people I grew up at, right? You know, so on. They were my mentors. They were the people I adored for it and they were deeply technical.
Andy Grove, Gordon Moore, Bob, you know, co-inventor, you know, these were deeply technical leaders. I remember when I joined the executive staff for the first time, you know, there was, you know, probably 15 of the 20 people that were in the room were PhDs, right? You know, it was just that technical. And, you know, I view one of the things that went off the rail was when it started to be run by business people.
The bean counters, the finance people.
And you know when I became CEO in 2001 that was the first technical leader in essentially 15 years.
Right, you know, associated with it, you know, and if you have a business leader who does he promote? Business leaders, and you know, right, you know, so I think one of the fundamental things is, and you know, as you look at the great technology companies today, you know, they're deeply technical.
And founder-led typically.
You know, and even if they're not, you know, Satya is not a founder, no, right? You know, Sundar is not a founder as well, but they're deeply technical individuals.
And when you're making these hardcore technical decisions that affect billions of dollars, you don't do that through a spreadsheet. That's a lousy investment, right? Unless the technology trends make it the right investment. And I think that's one of the fundamental things. And obviously, you know, in the five years, five, six years before I came back, you know, Intel gave $100 billion to shareholders.
A hundred. What I wouldn't have done for another hundred billion dollars on the... What would you have done? You probably would have made chips for iPhone which Intel passed on. Yeah.
Yeah. You know, but it hadn't built a new factory in a decade when I got there. It's like, how can you not be building? How could you not buy EUV machines? There's just all of these things that you would only do as a technologist because the economics behind them by themselves were not good.
So, you know, it's getting back to the core of technology to me that was the fundamental thing. You make good decisions, you make bad decisions as leaders. Every business does that as they go along, but fundamentally this is a technology business and you need technologists running technology that then hires technologists that are sitting at the staff that then hire the best technologists.
And take big swings at categories that could matter in the future, like skating to where the puck's going. If you look at Apple, they did the same thing for the past 15 years, buying back the stock, tremendous amount of dividends. They're the largest holder of capital of any company, I believe, to this date. And what companies do they buy? They buy little tiny acquisitions on the margins. I think the largest one was Beats because they wanted to get inroads into certain demographic segments like in the Android space that they couldn't get into. But my god, what a colossal waste of time. Like you said, they could have done so many amazing things.
Tell me about Steve Jobs in 2008, 2009 deciding, I think we're going to make our own silicon and that impact because was that a covert product project or did you guys know he was doing that? Did he inform you?
Well, that seemed to be another one of those forks in the road. Yeah, you know, Steve was an incredible leader. He was also a ruthless leader, right? Very difficult. Read Walter Isaacson's book on him as well. I had many, many conversations with Steve over the years. But when they moved to Intel and the Centrino chip, it was a big deal.
Right. And they were putting extraordinary demands on Intel. Make the chip smaller, drive lower power. They were a demanding customer. And when he was no longer convinced that we could continue to do that, he started the project, right? And if you remember, it was P.A. Semi, they acquired some small companies, started to build some competency, but they did a few little chips internally. It wasn't a big deal and then the little chips got a little bit bigger, and Steve was a master of this, just starting these small efforts to build core competence inside the company. I remember when we had the first conversation with Steve about porting the operating system to the Intel chip from the PowerPC chip that they were running on before they moved to Intel. And we were quite proud of the silicon software competencies that we had and compilers and operating systems. So Steve, we'll help you port the operating system to the x86. And I remember that Steve said, "I've been working on that for the last four releases." He had been preparing the core technologies inside of Apple for something that might happen in the future, and he was already, to me, I just remember I was just shocked. I've ported the last four releases to the x86. I think we got this.
Right. It was that kind of thing. And that's how they got into the semiconductor, doing their own semiconductor. Hmm. I'm not sure I can rely on Intel to be that much ahead of the industry and I can start optimizing the system design with the silicon design as opposed to relying on one that's been somewhat optimized for a Windows environment versus an iOS environment. And it was never that kind of thing. They sort of said, you failed as a supplier. No, I can supply myself better.
Yeah. And Jensen decides, hey, he's going to go all in making these video cards and talk about just incredible serendipity that these happen to be also very applicable for cryptocurrency and running these AI jobs.
Was that luck or skill or combination of both there?
Well, you know, when you think about that progression, Jensen, he was just building high performance computers, throughput machines. When we were at the height of our strength on CPUs at Intel, we sort of scoffed at his machines. Yeah.
Right. You like, oh, that's a graphic machine. There's some gamers who want to use that kind of stuff, right? It was always the big CPU and those little GPUs.
But when they started to build a real software stack with it, right? Sort of, okay, this CUDA thing and SIMT as a technology, multi-threading and so on. And it just sort of kept getting a little bit better and a little bit better and it was a little bit Jobs-like in that way. We're just making it better every release and it's becoming more robust and all of a sudden, the crazy Japanese HPC guys said, "Hey, we could take those graphics cards and maybe start using them in HPC." Right? And that was sort of defining moment where it wasn't just about doing graphics anymore. This was a more computationally dense platform to start attacking some of the world's most interesting workloads. And I think Jensen would agree that was a defining moment and them sort of saying, "Oh, these aren't just graphics cards anymore. These are general-purpose computing devices that can start applying to these other workloads." And AI had gone through what its fifth nuclear winter by that point. We're just like, man, this is never going to matter, we're never going to get the breakthroughs, but the community around it was continuing to develop, and the CUDA software kept getting better generation by generation. And I had a project at Intel, Larrabee, right, where we were trying to take the x86 and essentially do the same thing. And in my first departure from Intel, the project was killed a week after I left.
And the world would have been so much different, right? I...
I mean it really, I think it's illustrative of what continuous innovation, taking some risks and doing that fundamental research and the compounding power of technology. Because I think it was William Gibson who said the street finds its own use for technology. Like Nvidia did not predict that this Bitcoin project would take over and that this would be the best way to do those computations, nor did they anticipate, I think, that AI would take off, but because it was the best solution, the hacker community could kind of figure that out. Well, as we wrap on the Intel portion of your career, okay, Apple Silicon, that's one. And then you have Nvidia, and then you have this Taiwanese company that starts making really great at fabricating these chips. And Intel missed that as well. Yeah. And maybe you could talk a little bit about TSMC and their surging and we can even get into a little bit of the politics of it now and then we'll get into some of these AI chips and venture investing.
You know the thing with TSMC was they started with a vision of foundry, right? They were going to become the factory for the industry. And again, these factories are so expensive, 20 billion, 30 billion, and the engineering and the continuous investment required to do it. And it was a stunning vision at that point in time. Intel was IDM, as we called it, the integrated design and manufacturing. We never worked to make our process and our factories available for third parties, right? It was always this thing, hey, we do enough CPUs ourselves, we reuse it for chipsets and some of the other things that we're doing, but it was never standardized in a way that it could be made available for a broad ecosystem using PDKs and all the design tools. We did a lot of our own EDA tools ourselves. One of the projects that I started early in my career was the foundations of EDA, right? The first place and route, the first standard cells, the first high-level description language. It was so proprietary. And TSMC basically cut that in half and says, I don't care whose chip it is. I don't care what you're designing, I'll be your manufacturing partner. And at the time, that was such a trivial piece of the business, Intel didn't even care, right? And then over steady progress over a long period of time and Apple as a customer driving them to become really meaningful. Obviously the world changed and when I came back to Intel in 2001, TSMC was producing 5x the wafers of Intel.
Right. Not 10% more, 5x.
Yeah. And all of a sudden that model of foundry became the model of the semiconductor industry with two exceptions: Intel and memory. Memory design and manufacture, right, for that is uniquely different. And obviously we're seeing the $3 trillion memory companies, just extraordinary, and trillion dollar foundry company in TSMC. The industry has said, I want a lot of wafers. I want a lot of innovation of different designs. I have a layer of standardization and EDA tools. And the world changed. And obviously as I came back to Intel that was one of the core theses of the new strategy. Yeah. We must become a foundry as well. Five to one and now it's more like seven to one in terms of wafers to TSMC.
Are we going to be able to onshore that? Obviously we had the CHIPS Act. And just give us broad strokes what you think is going to happen here in terms of obviously Taiwan is in play. Some people in the administration believe it's going to happen the year after Trump's out unless he takes his third term. Other people believe it was going to happen as early as '27 or maybe going into '28. So, are we going to be able to replicate that here in America in a reasonable amount of time, or is this truly could be a cataclysmic event if, god forbid, China decides to blockade Taiwan and the Taiwanese decide to burn the fabs and fly out all of the engineers and ship them to America?
Well, there's a lot in that question. Do we have an hour to talk about this question? Well, I mean we have six minutes, but okay. Um, yeah, do the best you can.
Okay.
I want to talk also about the AI bubble.
So, super, you know, three things about this super quick. One is the CHIPS Act is having benefit.
Right. You know, when we started the CHIPS Act in 2001 when I came back, the US was building about 12% of leading edge. Today, that number is more like 18%.
Okay. You know, we're making progress. It's not 50%. We have a long way to go, right? Intel is starting to be a real foundry. Okay, that's real progress. And TSMC's factories are up and operating at scale, right? We have Samsung as well. But I say the Intel and the TSMC progress. Okay, that's meaningful. Now, let's make it ugly for a second. The island of Taiwan has less than 3 weeks, a big article in the Wall Street Journal two weeks ago on this, less than 3 weeks of energy reserves. Wow. Okay, that should just put a chill in everybody's spine, right? Because the blockade after 3 weeks, the island browns out. When you turn off a fab, it doesn't come back on for 90 days, right? The economic impact of a brownout of Taiwan is greater than the Great Depression, right? In the world, you never need to do anything, a shot to be fired. You just need to say, "Great, no energy for 3 weeks. No oil." Yes. Right. No LNG, right? That's how the island runs. That is scary to me. We need more resilient supply chains associated with it. And I don't think this is an alternative for the world because if it really does become a risk, and I don't sit in the situation room and get all the data and so on, but let's remind each other that I think China has blockaded the Taiwan Straits seven times over the last four years.
No, no. They're running exercises. They're being pernicious and
Pretty provocative in terms of
Is that 2027? Is that 2030? Is that 2035? Their intentions have been clear over a sustained period of time. We need more resilient supply chains forward. So, something I put a lot of my time and energy into and we're making progress, but we need to go faster, need to go more meaningful.
Yeah. And let's talk a little bit about the AI buildout. I mean, you watched the PC revolution, servers, the internet. These were all extraordinary buildouts. And then this is the buildout to end all buildouts. The amount of data centers, the amount of chips, the amount of inference needed. Do you think it's a bubble? I think I've heard you say like it's obviously a bubble, but what's the risk factor here? That we build too much or that the technology doesn't solve enough problems and we are swimming in tokens? What worries you about what you're seeing now? The valuations of these companies has gotten quite extraordinary. And if they build too much and they spend too much money and they don't make enough money, well, based on your experience with running a company, a public one, that's a lot of tension on it. When you don't make as much money as you're spending, people tend to fall out of love with these stocks. Yeah.
Well, I do think there is a silver lining here that guarantees we don't get too far ahead of ourselves in terms of bubble, and that is energy capacity.
Right. Energy capacity in the world is expanding 4-5%. In the US we had a decade at 1%. I mean, it's just hideous what we did to our energy grid over about a decade and a half. But now that's getting built out. But essentially, nobody's going to build and buy GPUs and build data centers if they don't have energy. So essentially, you have an upper bound on how aggressive and how hyped and bubbled that we get. So I take a lot of solace in that.
Right. Because what then is the incremental value of a token? And if it's a measure of intelligence, it's somewhat infinite, right? In the sense if I have more intelligence, I will do better supply chain. I will do better finance. I will do more efficient logistics. I will do all of those things. So to me, the potential value that we unleash in a token economic world is somewhat infinite, right? And particularly with labor shortages and so on that we see right in developed countries, I am an optimist that we're in a couple of decade buildout.
Right. Not a couple of years, a couple of decades. One of the big objectives I've said is that I have to make AI 10,000x better, right? It's way too expensive today. We want to drop by five orders of magnitude the cost per token, the energy per token so that we really do have Jevons law that we just explode the access to AI in much more economic ways.
