Today, we’re bringing you something a little different. The Code Conference was this week, and we had a great time talking live onstage with all of our guests. We’ll be sharing a lot of these conversations here in the coming days, and the first one we’re sharing is my chat with Dr. Lisa Su, the CEO of AMD.

Lisa and I spoke for half an hour, and we covered an incredible number of topics, especially about AI and the chip supply chain. These past few years have seen a global chip shortage, exacerbated by the pandemic, and now, coming out of it, there’s suddenly another big spike in demand thanks to everyone wanting to run AI models. The balance of supply and demand is overall in a pretty good place right now, Lisa told us, with the notable exception of these high-end GPUs powering all of the large AI models that everyone’s running.

The hottest GPU in the game is Nvidia’s H100 chip. But AMD is working to compete with a new chip Lisa told us about called the MI300 that should be as fast as the H100. There’s also a lot of work being done in software to make it so that developers can move easily between Nvidia and AMD. So we got into that.

You’ll also hear Lisa talk about what companies are doing to increase manufacturing capacity. The CHIPS and Science Act that recently passed is a great step toward building chip manufacturing here in the United States, but Lisa told us it takes a long time to bring up that supply. So I wanted to know how AMD is looking to diversify this supply chain and make sure it has enough capacity to meet all of this new demand.

Finally, Lisa answered questions from the amazing Code audience and talked a lot about how much AMD is using AI inside the company right now. It’s more than you think, although Lisa did say AI is not going to be designing chips all by itself anytime soon.

Okay, Dr. Lisa Su, CEO of AMD. Here we go.

This transcript has been lightly edited for length and clarity.

Hello, hello. Nice to see you.

Nice to see you.

Thank you for having me.

I have a ton to talk about — 500 cards’ worth of questions. We’re going to be here all night. But let’s start with something exciting. AMD made some news today in the AI market. What’s going on?

Well, I can say, first of all, the theme of this whole conference, AI, is the theme of everything in tech these days. And when we look at all of the opportunities for computing to really advance AI, that’s really what we’re working on. So yes, today, we did have an announcement this morning from a company, a startup called Lamini, a great company that we’ve been working with, some of the top researchers in large language models.

And the key for everyone is, when I talk to CEOs, people are all asking, “I know I need to pay attention to AI. I know I need to do something. But what do I do? It’s so complicated. There are so many different factors.” And with these foundational models like Llama, which are great foundational models, many enterprises actually want to customize those models with their own data and ensure that you can do that in your private environment and for your application. And that’s what Lamini does.

They actually customize models, fine-tune models for enterprises, and they operate on AMD GPUs. And so that was a cool thing. And we spent a bit of time with them, quite a bit of time with them, really optimizing the software and the applications to make it as easy as possible to develop these enterprise, fine-tuned models.

I want to talk about that software in depth. I think it’s very interesting where we’re abstracting the different levels of software development away from the hardware. But I want to come back to that.

I want to begin broadly with the chip market. We’re exiting a period of pretty incredible constraint in chips across every process node. Where do you think we are now?

It’s interesting. I’ve been in the semiconductor business for, I don’t know, the last 30 years, and for the longest time, people didn’t really even understand what semiconductors were or where they fit in the overall supply chain and where they were necessary in applications. I think the last few years, especially with the pandemic-driven demand and everything that we’re doing with AI, people now are really focused on semiconductors.

I think there has been a tremendous cycle. One, a cycle where we needed a lot more chips than we had, and then a cycle where we had too many of some. But at the end of the day, I think the fact is semiconductors are essential to so many applications. And particularly for us, what we’re focused on are the most complex, the highest performance, the bleeding edge of semiconductors. And I would say that there’s tremendous growth in the market.

What do you think the bottleneck is now? Is it the cutting edge? Is it at the older process nodes, which is what we were hearing in the middle of the chip shortage?

I think the industry as a whole has really come together as an ecosystem to put a lot of capacity on for the purposes of ensuring that we do satisfy overall demand. So in general, I would say that the supply / demand balance is in a pretty good place, with perhaps the exception of GPUs. If you need GPUs for large language model training and inference, they’re probably tight right now. A little bit tight.

Lisa’s got some in the back if you need some.

But look, the truth is we absolutely are putting a tremendous amount of effort getting the entire supply chain ramped up. These are some of the most complex devices in the world — hundreds of billions of transistors, lots of advanced technology. But absolutely ramping up supply overall.

The CHIPS and Science Act passed last year, a massive investment in this country in fabs. AMD is obviously the largest fabless semiconductor company in the world. Has that had a noticeable effect yet, or are we still waiting for that to come to fruition?

I do think that if you look at the CHIPS and Science Act and what it’s doing for the semiconductor industry in the United States, it’s really a fantastic thing. I have to say, hats off to Gina Raimondo and everything that the Commerce Department is doing with industry. These are long lead time things. The semiconductor ecosystem in the US needed to be built five years ago. It is expanding now, especially at the leading edge, but it’s going to take some time.

So I don’t know that we feel the effects right now. But one of the things that we always believe is the more you invest over the longer term, you’ll see those effects. So I’m excited about onshore capacity. I’m also really excited about some of the investments in our national research infrastructure because that’s also extremely important for long-term semiconductor strength and leadership.

AMD’s results speak for themselves. You’re selling a lot more chips than you were a few years ago. Where have you found that supply? Are you still relying on TSMC while you wait for these new fabs to come up?

Again, when you look at the business that we’re in, it’s pushing the bleeding edge of technology. So we’re always on the most advanced node and trying to get the next big innovation out there. And there’s a combination of both process technology, manufacturing, design, design systems. We are very happy with our partnership with TSMC. They are the best in the world with advanced and leading-edge technologies.

They’re it, right? Can you diversify away from them?

I think the key is geographical diversity, Nilay. So when you think about geographical diversity, and by the way, this is true no matter what. Nobody wants to be in the same place because there are just natural risks that happen. And that’s where the CHIPS and Science Act has actually been helpful because there are now significant numbers of manufacturing plants being built in the US. They’re actually going to start production over the next number of quarters, and we will be active in having some of our manufacturing here in the United States.

I talked to Intel CEO Pat Gelsinger when he broke ground in Ohio. They’re trying to become a foundry. He said very confidently to me, “I would love to have an AMD l