Re-engineering the Semiconductor Supply Chain with Intel CEO Lip Bu Tan

Nine of the 10 companies I invest in change their business plan halfway through because the market has changed.

Yeah.

So I like to have an entrepreneur and a team, not just one person. I always believed, when I was at Cadence and also at Intel, that first of all you crawl and then be humble and listen to the customer. The first step for me is to strengthen my balance sheet, focus on the products, really simplify the product line, listen to the customer, and then drive the next-generation leadership products.

Right now, with the AI agenda, inference CPUs have become highly in demand. In some way, I'm happy right now that demand is very high for my CPU. Secondly, I'm very happy that Jensen Huang, my longtime friend, also invested $5 billion to support me. That $5 billion has become $25 billion now. If you look at it, 10 years from now, what will be the winning company?

Hi listeners, welcome back to No Priors. Today a lot and I are here with Lip-Bu Tan, the legendary investor from Walden, then CEO of Cadence, now CEO of Intel. We talk about his plan to transform Intel, having the US government as a major shareholder, how to be an amazing semiconductors investor and whether or not we can make chips in the United States. Welcome, Lip-Bu. It's great to see you. We'll start with the obvious question: this is a really hard job, to go be CEO of this incredibly important American semiconductor company. Why take the job at all?

It's a good question. I'm 66, and people thought that, well, I should retire rather than take on this hardest job in the industry. There are a couple of reasons. One is that this is an iconic company, and it's so important for the semiconductor ecosystem and also so important for the United States. So I decided to do one more after Cadence.

A lot has happened in this past year. What has been the most surprising to you?

The most surprising thing that I didn't learn from my previous job or even from training was that, one day, early in the morning, President Trump asked me to resign because of a conflict of interest, and there were no exceptions. I convinced myself that, first of all, I didn't need this job. I was doing it purely to save Intel, so I took that personal issue out of the way. Then I figured out what I could do to be helpful to Intel.

The good news is that I had a meeting on Thursday morning, and then on Monday I had another meeting. He listened to me, and I had a chance to explain myself. I was born in Malaysia, grew up in Singapore, went to MIT, and live in the US. I've never lived outside the country. I shared that with him, and somehow he listened very well and gave me the chance. So I'm delighted.

And now you have the chance to do the work. When you said the job is to save Intel, and it's a really important company, what does that look like to you? What does Intel winning or thriving look like?

I just passed 14 months. A lot of things happened in these 14 months. A couple of things: one is to change the culture, clearly drive more accountability, and make decision-making faster. I'm so used to startup culture, where you move at the speed of light and don't have layers upon layers of meetings.

Something that I changed is accountability: listen to the customer, be humble and willing to listen, address some of the problems that they face, and try to delight the customer. From day one, I decided that all engineering reports to me. I'm an engineer by training, and I want to know what went wrong and what I need to correct. I want to listen to the customer and delight the customer, make sure that we have the right product, simplify our product line, and really have the roadmap and vision for the next 5–10 years.

What is your vision of where Intel should be in 10 years?

I think there are a couple of things. One, I always believed, when I was at Cadence and also at Intel, that first of all you crawl, then be humble and listen to the customer; secondly, you start to walk; and finally, you start to run and sprint. That's my culture: step-by-step execution. The first step for me is to strengthen my balance sheet.

Mhm.

The balance sheet is really heavy—horrible, in some way. So I'm delighted that the US government has become a big shareholder. As I explained to President Trump, when TSMC started, it had the Taiwan government as a shareholder. If you look at Japan and Singapore, this is the infrastructure the US government gets to provide support for.

Secondly, I'm very happy that Jensen Huang, my longtime friend, also invested $5 billion to support me. I'm glad that I'm at least doing some good work. His $5 billion has become $25 billion now, or more. The other part is SoftBank's Masa. I used to be on the SoftBank board, and he lent a hand to help me.

So we strengthened the balance sheet, focused on the products, really simplified the product line, listened to the customer, and drove the next-generation leadership products. In some ways, I'm very lucky. Right now, with the AI agenda, inference CPUs have become highly in demand. Versus 1:8 for training, CPU to GPU, now I can see 1:4, maybe 1:1. I'm delighted that the CPU has become important.

I talked to some AI modelers and developers, and they said, “In terms of reinforcement learning, in terms of the speed of orchestrating all the agents, it turns out the CPU is actually better.” So in some way, I'm happy. Right now, the demand is very high for my CPU.

I think overall, we need to build on the product on the data center server side. The other part is our foundry business. Initially, this is a capital-intensive business, and it's not easy. You really need to have a couple of things: all the right IP so that you can support the customer. For example, if it is mobile-related, you've got to have the low-power IP set that you need. Without that, you cannot serve them.

It's a service business. It's a trust business. If people want to give you orders to have wafers come, and the yield isn't good, they will be toast in terms of revenue miss. So with that, I think it's very important to focus on the yield, the defect density, and the cycle time, and then make sure that you're really able to meet and serve the customer with high quality and reliability. Those are the things that I really focus on.

Eventually, you have to move into a full stack. It's not just silicon; you need to have software. Some of the customers ask me, “Give me the whole rack.” That's a system that you have to build. Those are the things that I'm quietly building step by step and recruiting some of the best talent I can find.

By the way, I do all the recruiting myself. No search firm is helping. Sometimes it's good to have a Rolodex, so you know whom to reach out to and call.

Yeah, I mean, you've been in the business for so long, and you've run Cadence for, I think, 12 years before this.

13 years, to be precise.

13 years. Sorry. Yeah, yeah, yeah.

more years as executive chairman, so 15 years. I signed up for 3 months. So right now, I'm being very careful. The moment you say, “I'll just do it for 3 months,” it turns out to be 15 years.

Well, it seems like you have a lot of longevity ahead of you here as well. The other big initiative that has been talked about is TeraFab and working with Elon Musk on that. Can you tell us a bit more about how that came together, your involvement, and how you're all collaborating?

Elon Musk, I think we all agree, is one of the best, if not the best, entrepreneurs of this century. He and I share the same view that semiconductor infrastructure actually hasn't caught up with AI growth. You need the capacity, you need the productivity, and you need the fab efficiency. Those are the things that he and I share: something is missing.

I'm just delighted to work with him. He's very—I call it unconventional. He basically questions every step: why this traditional way of doing things? In some way, it's very refreshing. I like people who have different opinions. Let's work together, find the best route, and we both are going to learn a lot together.

Clearly, he has a vision that his robots and his cars need a lot of silicon.

Can you actually explain what TeraFab is for people unfamiliar with it?

TeraFab

he decided that he wanted to build his own fab. Meanwhile, we're delighted to work with him and make sure that we can work together to enable him to get to production faster and more quickly, using some of our technology and some of our processes. There's something that we're both going to collaborate on. He has a very good team that I work with weekly, and it's just refreshing to work with him.

He's talked about things like wanting you to be able to smoke inside the clean room, and all these things that normally are considered very—yeah, yeah, yeah. Think the polka?

I think I don't go that far. Maybe in some part of the clean room you can do that, but I think we're open-minded, and we're also listening to see whether we can do that.

Yeah, I mean, it's very exciting to see how you're morphing the business here in the US—in terms of incrementally building out the foundry business and collaborating on things like TeraFab.

If you think about the global AI and semiconductor supply chain, say that you were to look at the changes that AI is driving on a macro basis, country by country. If I look at certain countries and the layoffs that are claimed to result from AI, most of them, I think, are overstated right now. Most of the layoffs are actually just overhiring during the 2020 COVID period. But the first things I see being cut are outsourced firms, where you'd rather cut external headcount versus internal. So you're cutting external customer support; you're cutting external IT.

And that has more of an impact, I think, for certain countries that have big BPOs, such as the Philippines and India. So they may be impacted in the short run by AI. And then if you ask how companies participate in the future in a positive way in AI, you have to almost go country by country, right? Places with cheap energy will do data centers. Places with the ability to train models will train models, but that's probably only the U.S. and 1 or 2 other places.

How do you think about the shift in the global supply chain for the semiconductor industry? Should certain countries invest more? Should Israel be doing more, given Mellanox, NVIDIA, and Intel's presence there, and should it try to do more in semiconductors? Should the Philippines move back to more of a manufacturing base? How do you think about that on a global basis?

Yeah, good question. I think AI is clearly changing the whole landscape, and I think the impact will be bigger than the internet. It's more profound, too. Initially, AI is able to help you do things more efficiently. Then, with a lot of agents helping you do the mundane things that you need to do, they can get them to you faster.

In some way, I think you can drive a lot of efficiency. Even in semiconductor design, how much can you drive efficiency in terms of timing? How quickly can you come out with it? And secondly, the cost. Those will help you drive that.

Then I think there are a couple of bottlenecks for AI demand and growth. One is, of course, as everybody knows, the power constraint. Some countries just don't have that power, so they get impacted. Secondly, a lot of people didn't realize that the impact of helium can also be very significant for semiconductors. Thirdly, everybody knows that memory is in an even greater shortage right now, and everybody is scrambling for memory.

Even though you want to build a fab to increase capacity, it will take a couple of years to do that. The same thing goes for CPUs, GPUs, and all of this, which will be highly demanded. I think pricing will also go up because we have to pass the cost on to the customer. Those will be the impacts on industry growth.

Overall, I feel that the companies most impacted are the ones that are not embracing AI, because AI can help you drive a lot of efficiency across all the different functions of the enterprise. We should embrace it and also find ways to better use AI for your prediction, for your design, and for all the different parts of the workload. I think that's tremendous.

A number of people would say the simplistic argument against TeraFab, against Intel Foundry being competitive, is really a question of other factors internal to the building, right? You described IP and velocity—just how you're doing business. Then there are external factors, and a lot of people are talking about a number of them, but one of them is the cost of labor and, actually, the manufacturing capacity.

In investing in the foundry business, you obviously believe there's a version where you can manufacture domestically, and Elon does, too. Can you talk a little bit about that and how real that constraint is—the labor constraint?

Right. So I had to decide whether I should double down on the foundry or get out of the foundry.

Mhm.

I came to the conclusion, despite a lot of voices in the marketplace, as you can tell, saying, “It's very expensive. It's not going to work.” But I finally decided this is very important for the United States and also very important for the industry.

Mhm.

I'll give you the idea that we all lived through these challenges of the supply chain. It's very important for any big company in semiconductors, and we really have to think about supply chains. You have to have a robust and resilient supply chain. You cannot just depend on 1 or 2 players in different geographies.

I think more and more people are going to realize that manufacturing in the United States is critical. The most advanced process, like, for example, our 14A, is 1.4 nanometers. We're already starting to plan for 1 nanometer and 0.7 nanometers. It's getting smaller and smaller. In a way, it's much like our hair. So thin.

There's a lot of complexity. It's not that easy to do, and every step, if you make a mistake, then you just go down the drain. In some way, you have to be really precise in that manufacturing. In some way, this is becoming more and more of a bottleneck.

Mhm.

We have a lot of respect for TSMC. We're great partners, and, more importantly, we both need to have more capacity to serve the customer. So I think we decided to bite the bullet. Longer term, I think it's critical, and that's where I can create more value for the industry.

People have been talking for a long time about eventually hitting a point of resolution where you can't really miniaturize things further. The linewidth gets too small to be able to keep going. When do you think we actually hit that limit?

Good question. Right now we have 18A, and now we're going into production with 14A. I can see 10A and 7A. I think we can get there, but it's going to be more and more expensive and more difficult to do. That's why we need partners. We cannot just do it ourselves alone. We need to partner with the substrate vendors and equipment vendors to make sure that we can really drive those yields and performance.

Yeah.

The other part that is also becoming a bottleneck is packaging.

Mhm.

Advanced packaging. We all know about CoWoS by TSMC. Now we have a really good one called EMIB-T, which is really next generation. We have to make sure that we're able to do it in production with yields that meet the customer requirements.

Now, as you described, semiconductors are starting to run out of steam. So right now I'm also looking at some new materials, going back to the periodic table. Gallium nitride, silicon carbide, and indium phosphide—I invested in all 3.

I see.

Looking at some of these new materials, how can we really drive that? In terms of packaging, I'm starting to invest in glass.

Mhm.

Glass is a very good heat insulator. I even invested in a venture called 3D Glass Solutions, or 3DGS. Then I realized that Intel has around 1,000 patents on the module. So how do you put the substrate and the module together? We just announced a big program with the Indian government to manufacture in India, plus in the U.S., in New Mexico.

I think this is why advanced packaging is very important. I'm also starting to look at artificial diamonds.

Mhm.

That's another very good insulator. I also invested in Diamond Foundry. That's something to look at for the next generation. New materials, new substrate materials, and new design methodologies to drive it.

One thing that's good about being an engineer is that you're always hitting the wall. Then you find a way to either jump over the wall or work around the wall to get to a better result. That's what I've been doing for a long time as an investor and in building semiconductors, from EDA tools to design to manufacturing. It's kind of nice to have that experience. Now I can help find a way to make a small contribution to the industry.

Yeah, and that one is very exciting. One of the reasons I'm asking about it as well is that, to your point, there are always some things that you can work around, but there are also physical limits where, once you hit 7 angstroms or whatever the limitation is, you start to run into—yeah, you need to find new materials or other workarounds.

And then the interesting question is—and we've been talking about this for a long time. I remember 20 years ago, people were talking about how we'd eventually hit this point where we ran out of space. Do you run into some sort of asymptote that actually normalizes performance across different foundries?

That's a good question. In terms of Moore's Law, it's a doubling in the—

Yeah.

—and then the power and the cost. You can double the performance, but you cannot double down on the cost and area. Those are the things you have to give way on, unless you find some new way of using materials or a new way of designing.

In materials science, I'm starting to hire more people in materials science. That is an area of innovation for us. How can we do that? I still remember 18 years ago, and I'm still investing in semiconductors. Actually, most of the VC firms—some of them are very nice, tier-one venture firms, good friends of mine—when I initially went to the partners' meeting, the whole partnership was in the room. Then, after I talked about semiconductors, half of them made excuses.

They ran out of the room. Then eventually, the other half said, “Lip-Bu, do you have any software service?”

So, then they both left, with only 2 people sympathetically listening to me. The history has changed. Now semiconductors are hot again. If you look at it, Tencent is a $5.3 trillion market cap company, and Broadcom and TSMC are $2 trillion market cap companies. Lisa Su, my good friend at AMD, is almost $800 billion, and I’m close to $600 billion.

In some ways, semiconductors have become hot again, and they’ve become essential. Because 15 or 20 years ago, when I invested in semiconductors, no VC wanted to join me, except for some of the big corporations like Samsung, ARM, SoftBank, and others that invested with me. Now I’m starting to see a lot of VCs wanting to invest in semiconductors, so I’m very happy.

Yeah.

Mhm. Given the enormous interest in investing in an area that used to be considered too hard, what do you think? You’ve been a venture investor with Walden for a very long time, as well as an operator.

The general fears are—and tell me what I’m missing—that it’s very capital-intensive. It’s very unpredictable in terms of shipping a design that works or missing tape-out, and you need to understand the workload very well. I think there’s another issue, which is that it’s very high-risk for the customer—

Yes.

—to switch, right? I think we’ve been involved in companies together where there’s a design win, and then there’s still the question of scaling order volume. Then there’s cyclicality, right? You build hard manufacturing capacity, and demand may change or may not in any given year.

What is your view on what makes it hard as an industry, and then on the secular demand growth from a bunch of different areas? You have recognition of how important a more diverse supply chain is, and then you have this explosive demand growth on the AI side. How do you—you’re still an investor, and then you’re making the biggest bet ever by becoming CEO—think about these different risks and advise others about where to invest in this supply chain?

I realize that’s a very large question, but given your history with it, I think there’s a lot of YOLO action, like, “There’s a memory shortage; buy memory stocks,” as well as an unwillingness to take on things that have a 10-year timeline, like materials science.

Good. You have quite a broad range of questions. Let me try to explain that.

First of all, the venture capital startup is in my blood. I really enjoy it. This is not to brag about it, but I’ve had some good exits. I’ve had 159 IPOs and M&As, and that includes semiconductors. To break down the semiconductor investments, I’ve invested in 238 companies over the years, and 38% are in the U.S.

What I usually look at in semiconductors is, first of all, where the bottleneck is and what you’re trying to solve. For example, I invested in a company called Credo Semiconductor. Is the interconnect becoming the bottleneck? I decided to back it, and I also backed Celestial AI on the optical side because speed is becoming more important in the interconnect for the cluster.

Look at Jensen. He invests in almost every company related to photonics. The other part I look at is what solutions are needed. For example, we talked about design, complexity, and cost. Can you use AI and machine learning to drive better design and better solutions? A couple of new startups are moving into the EDA-related area to drive performance improvement. I think it’s a gold mine.

Then you look at new materials. We talked about indium phosphide, which is why I invested in Inphi, and then Marvell bought it. You invest in some of the new materials, such as gallium nitride and silicon carbide. Some of the companies are starting to be acquired, including one doing power management that Analog Devices just bought, called Empower.

Again, power management is a very good area because it’s becoming a bottleneck now. In terms of converting from 40 volts down to 1 volt, you lose a lot of power in that conversion. How do you drive power improvement? I think power and thermal are becoming bottlenecks.

I always look at what problem we’re trying to solve. Is it real? Are customers crying for it? Then I start to invest.

The next thing that’s very important is that, from day one, you have to target the first customer.

Mhm.

Usually, I like the customer to be a hyperscaler. They have scale. If they like what you have, they’re willing to pay millions of dollars over the next few years. Even giving some warrants is worth it because, with one big customer, you can scale. I always look at the formula for how you do that.

Then, where do you get the talent? Sometimes it’s very important to find the talent. That’s why I’m really interested in the U.S., Silicon Valley, and some places in Austin. The other part is Israel, which has a lot of talent. I’ve backed quite a few companies—a significant amount of my investments—in Israel because they have disruptive, innovative entrepreneurs who work really hard.

Even during wartime, they still have conference calls. Suddenly, they’ll say, “There’s a warning. I have to go underground.” Then the internet may not be good, so maybe they’ll just use voice. In some ways, it’s kind of fun. That kind of resilient entrepreneurship is something I really enjoy.

All in all, there are a lot of opportunities, especially in AI. Besides gigantic AI systems, you’re now looking at physical AI as the next big frontier. You have to look at the full stack. That’s why I’m still involved with a lot of the frontier models that we’re very familiar with, and some of the investments I back are because I really like open-source frontier technology for physical AI. I think that’s a good way to go.

You mentioned the opportunity to make certain parts of chip design and testing faster, cheaper, and more creative with AI. Given your Cadence experience, where do you think the most fertile opportunities are? Is there anything you think is already working?

For almost 15 years with Cadence, I was very happy that one of my highlights was being able to find my successor along the way and train him. He became a super-great CEO, and he really embraced AI, driving the AI agenda to create more efficiency.

Synopsys’ Sachin also tried to do that, and they have a $2 billion investment from NVIDIA, I think, helping him do a lot. He acquired Ansys to move into whole-system design. All in all, they’re doing the best they can, but there are also opportunities for startups to do something more disruptive. Eventually, they can go public or be acquired by either of them or by Siemens.

It all depends on the entrepreneur’s vision. My philosophy is that if an entrepreneur wants to sell the company, that’s a quicker way to exit. You don’t have to lock up, and you don’t have to worry about quarter-to-quarter earnings. Some entrepreneurs, from day one, want to go public.

As a VC, I think the 3 of us—we’re all VCs—support the entrepreneurs’ dreams, and I help them fulfill their dreams.

Yeah. If you look at the different areas you mentioned in terms of future product development or the impact of AI on the semiconductor industry, there are companies like Periodic doing materials, your portfolio companies working on the EDA side and design, and other aspects throughout the chain, including manufacturing.

Do you think that either Intel or a future semiconductor company 10 years from now will look radically different from today? If so, how?

I think so. First of all, going back to your question about capital intensity, unpredictability, and cyclicality, you have to factor those into your investment decision-making. I usually like to go in very early and put a team together. It’s fun to do that. I think you should do that, too.

Secondly, you try to find the right investor who can co-partner with you. It’s not just about whatever the brand-name firm is; I usually go for the individual. For the individual who is really knowledgeable in this space, the most important thing is to find a partner through difficult times and good times.

A lot of times, people are very enjoyable to work with during good times. When the company gets into trouble, they just walk away. I like to have a partner who will really work through it. A lot of successful companies have nearly gone bankrupt multiple times, but eventually took off.

The other part is looking at which strategic investors can help you, whether in manufacturing, memory, connectivity, or various other ways to add value to the company. I also have a couple of friends who are in the growth stage and in hedge funds. I really enjoy them because they have a different perspective.

They know about the public market. They can guide the company’s entrepreneur on where not to go. Those people can be very helpful. I think it’s just fun to do that.

What I realize is that engineering for a startup is like problem-solving. Each step of the way, you have to find people to help you solve the problem, and then you trigger that and create the next frontier to work on.

Uh-huh.

Frankly speaking, I look back: 9 out of 10 companies I invest in change their business plan halfway through because the market has changed.

Yeah.

I like to have entrepreneurs as a team, not just one person. Secondly, they need to be open-minded. They are willing to listen and get coaching from us.

Mm-hmm.

Eventually, they formulate their own plan. It’s not just, “Do what I want.” It’s more that they figure out the best thing. The best thing is that you give them enough feedback and they draw their own conclusion. That’s exactly what you like, and whatever they can embrace is the right decision. That’s kind of the fun of doing a startup: they can move much faster.

So, back to your question: if you look at it 10 years from now, what will be the winning companies? This is just my personal view. The ones that articulate a vision, are laser-focused on one niche area, find the right partner, and are able to scale the company will win. In some way, I’m back to my point about full stack. In a way, you need to have a full-stack solution.

It can be a big company that really transforms itself by becoming a big platform, like Jensen Huang. I admire him. He focuses on CUDA, he focuses on the library—“I want to be a platform company”—and he did it. In some way, you can do that.

A startup company like Entropic or OpenAI can find a way to do it in a bit more elegant way. They change the game, and then the startup moves fast, at the speed of light, and can really become a dominant player. Hopefully Intel can play that role, because we have the XPU, advanced packaging, and foundry. If you put it all together, you can build some purpose-built silicon for different workloads. I think this is the way I’m going.

Yeah, that makes a lot of sense. I guess part of the question I was wondering about was where you’re going, and the other part is whether it fundamentally changes how you work. When I look at the software world, I think there’s a very big shift happening right now in terms of who you hire, who you think you want on board, and people managing multiple agents.

Many people I know are now hiring people in their 30s, 40s, and 50s because they’re used to managing teams, and I think that transfers directly over to managing agents in terms of understanding the complexity of what to set up, the QA, and everything else.

I wonder, in the context of the physical world or a fab, how you think about shifts in terms of team structure, capabilities, or how AI layers on. I just wasn’t sure if it’s a natural, slow evolution or if there are areas where there’s a radical shift, where it’s like, “Oh, from materials, now we should just use these 3 AI models plus some chemistry,” or whatever it is. That’s why I was curious about how you think about the future world there.

Good question. As I go back to that crawl, walk, and run, I think in the crawl phase, you basically try to recruit some of the best talent in the semiconductor industry. Now I’m starting to look at what software talent I need to bring on board in order to build a full stack.

The average age of my team is in the late 40s and 50s. I need to bring in some new talent so they understand the workload and frontier models and open source. That is important.

My son has become my teacher now.

Mm-hmm.

Every time he invites me to go to his house, we play with the grandkids. I start asking him about AI and machine learning. He’s more plugged in than I am, so I learn a lot. Then I try to understand it and bring some of that talent in.

We are changing Intel. Intel used to be a very old, legacy, spreadsheet company. Now I’m transforming it to become AI-native and AI-enabled, using AI in some of our design work and across all the engineers and the whole organization, embracing AI. They become less dependent on spreadsheets and labor to do that.

We’re going to combine the 2 types of talent with the best AI tools that I can use—not only for my organization and not only for my sales. Now I’m starting to look not just at marketing, but also at design, and embracing that.

I think a lot of investors—I know that, at least for me, the last few years since I started a firm have been very educational in terms of thinking about the different capital sources for more capital-intensive companies. I did a lot of software before, and your need to have smart friends with a very different stance and balance sheet was less if you were saying, “I need $150 million before this thing gets to some critical mass.”

You’ve lived that for a very long time, and then you have the unique experience of working with the government as a large stakeholder. How do you think this sort of industrial policy—which has led to huge successes like TSMC, the most important company in the world—should change now? It’s also been frowned upon in American business culture for a long time. How do you think that should change, or where is it relevant?

It’s a good question. Clearly, in a full, capital-intensive business and infrastructure play, you need access to capital. In some way, even early-stage venture capital investments are now starting to become very capital-intensive.

Yes.

Some venture firms are willing to put $1 billion into some companies. That’s very unheard of in the VC business. Now it’s happening.

Yeah.

I like this kind of bell curve. Either you go in very early, because starting at Series A, it’s over a $1 billion valuation, or you have to go in pre-money, pre-seed. To go into that kind of $20 billion or $30 billion valuation is very rare right now.

Mm-hmm.

You just have to pick the right one. The other part is being able to find capital to scale. That’s why some mutual funds also like to move into the private market, into early-stage investing, to join me in investing. I like them because they are much less sensitive about whether they have to own 20% of the company. There aren’t too many 20% stakes to give, so you have to find the right investor to come in.

In terms of capital-intensive areas like AI factory and also the foundry, you really need to tap either government funding, a sovereign fund, or some very large capital pools. There are some big funds doing that, and the funds they organize basically support infrastructure. We like to tap into some of them to make sure that we can scale our operations.

Overall, government and sovereign funds have become very important. As a public company, I also purposely want to focus on investors who are more long-term and growth-oriented, so that they can help me grow the business rather than asking short-term capital-allocation questions, like, “Where are you going to buy back your shares?” Those are good questions, but meanwhile, I also have to build the business. I think that balance is important.

Do you think there’s something that investors misunderstand most about Intel at this moment?

Quite a few things. First of all, going back to this crawl, walk, and run: in the last 4 months, I crawled, but people are starting to recognize the potential of it.

The other part is very important: we need to get the best products out. On the PC client side, we still have a big market share, but we really need to build better-performing products. That’s why I’m quietly building up the CPU architecture, GPU architecture, and software architecture, so that we can leapfrog.

I want Intel to have a multiple-startup culture, so that we move fast and can leapfrog using better technology. The other part is that, besides the product, there are new areas of energy coming in, like generative AI and physical AI. There are a lot of areas we can invest in. The market is huge.

On the foundry side, we are very distant from TSMC. In terms of performance, we have to be humble and focus on building the building blocks I mentioned earlier: the IP, the yield, the defect density, and the cycle time, to make it more efficient and more reliable.

It’s a trust business. People want to trust you before they give you their wafers and count on you. Those things will take a longer time. But I think by 2030, 2031, and 2032, it will start to surface. People may not understand how big the potential can be in terms of our products—not just the PC client, which is our bread and butter.

We can move up to the edge and into physical AI and agentic AI. In the past, you basically provided the server and the PC for humans. Now it’s starting to have another dimension: millions of agents. They need access to compute and the software stack.

I think we have a chance to really play. The game is not over yet. We can play in agentic AI and physical AI.

That's kind of where I'm going. AI is just the beginning. You have the training that Jensen owns, and the edge, and also, in terms of agentic AI, agents and physical AI. I think it's the jungle. Everybody has a chance.

That's the part that I want to go for. Hopefully, investors will know that even though, in 14 months, we made a 6-times return to shareholders, this is a beginning. We still have a lot of room to go.

There are venture returns from here.

Yeah. I always look for 10x. Being a venture capitalist at heart, you want to look for 10x. At Cadence, when I stepped out as CEO, I think we made close to 76 times, starting from interim CEO at $2.42. When I retired as executive chairman, it was about an 85-times return to the shareholders.

So it's hard to do that at Intel because the base is bigger. I said, "Okay, let's do it at 10x." In 5 years or 10 years, if we can do 10x, I think that's a good return. Being a venture capitalist at heart, that's kind of my goal.

There's a god-sized bet on this very, very large mission from this huge base already. There's an embedded belief in what you described about where the workload is. Some would say, "We're just going to build bigger and bigger data centers, and a gigawatt is the beginning." The centralization and efficiency from running even inference compute in a centralized way is the dominant approach, versus thinking about the edge and thinking about the client.

Do you think there's an equilibrium state that you believe in for where the compute is, or is it just, "We will find out from the workload"? How do you think about that?

Yeah, I think that's a very good question. Right now, there's a massive buildup in terms of AI. I think it's the right thing to do. I don't see anything to slow it down because the workload is increasing a lot. And then I think the question mark is how—

And we are supply constrained.

Supply constrained, yeah. I think anything that slows it down is a supply constraint. But I always look at all this infrastructure build-out. At the end, you have to look at: What is the solution? What is the application you want to drive?

I'm more focused on applications. If you can identify an application that is humongous, or add up a few applications to become meaningful, and focus on that, not everybody building is going to be winning.

Mhm.

Some are going to win big time, and some are going to lose over time or go sideways. Just like the internet, you can see some of them turn out to be very big, like Amazon and Netflix, and some of them go sideways, disappear, or are acquired.

To me, it's the same approach. Really focus on what application they are trying to serve, how big that application is, whether it's sustainable, and whether it's very crowded. If it's too crowded, maybe one or two may survive, and the others may just consolidate.

I think this industry will go through that big growth and then start to consolidate. Maybe eventually one or two become the real winners. We've watched the movie before, so it's not a surprise to me. Focus on applications: Netflix is an application, and Amazon is a real application. To me, they're winning.

But you're assuming that some of these applications will be better served by client or edge compute than only by the data center.

Okay.

Exactly. As an investor in a number of companies that are doing robotics and defense, I will say that the compute on the device is a very important choice in terms of power and what we assume around it.

Let's say there is eventually a robot in the home. What you assume is in the home, and the connectivity around it, determines what you're able to do. I think that was kind of forgotten for a little bit in the SaaS era.

Mhm. Yes, yes. I think my investment thesis is: Find a problem that really needs to be solved. Secondly, who are the players that you can partner with? And thirdly, look at the application. How big is the application? Is it sustainable? If it's really big and you believe in it, double or triple down.

But you're including betting on applications that have not yet been broadly deployed.

Okay.

It's amazing. Well, thank you so much for joining us today. It was a pleasure.

Thank you so much.

Thanks, Lip-Bu.

Thank you.

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