No Priors: Artificial Intelligence | Technology | Startups - Re-engineering the Semiconductor Supply Chain with Intel CEO Lip Bu Tan

Episode Date: June 18, 2026

At 66 years old, instead of heading towards retirement, former Cadence CEO and legendary investor Lip Bu Tan decided to take on the hardest job in tech: turning Intel around. Elad Gil and Sarah Guo sit down with Intel CEO Lip Bu Tan to talk about why he took the job and what “saving” Intel actually looks like. Tan explains how his experience in startup culture informed his decisions to drive Intel’s culture towards faster decisions, focus on customer satisfaction, and engineer accountability. He also discusses his strategy to strengthen Intel’s balance sheet by welcoming investments from Jensen Huang’s Nvidia, Softbank, and the US government. Tan also shares his product roadmap that centers the CPU for agentic AI and inference, the collaboration with Elon Musk on Terafab, his investing framework for semiconductors, and his views on how AI is reshaping design and operations at, as he puts it, a ‘legacy spreadsheet’ tech company.         Sign up for new podcasts every week. Email feedback to [e-mail] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LipBuTan1 | @intel Chapters: 00:00 – Cold Open 01:01 – Lip Bu Tan Introduction 01:24 – Why Lip Bu Took the Reins at Intel 03:00 – Fixing Culture 04:08 – Intel’s 10-Year Vision 07:57 – Working with Elon Musk on Terafab 09:59 – Shifting Supply Chain for Semiconductors 15:34 – Limits to Scaling and Packaging 18:30 – Physical Limits to Engineering and Design 20:33 – Challenges in Semiconductor Investing 26:29 – Lessons from Cadence 28:02 – Scaling and Investment Decisions 32:03 – Rethinking Teams in AI Era 34:31 – Industrial Policy and Funding 37:25 – What Investors Misunderstand About Intel 41:10 – Where Compute Will Live 44:59 – Conclusion

Nine of the 10 companies I invest, halfway they change their business plan because market will change. So I like to have entrepreneur, a team, not just one person. I always believe in when I was at Cadence and also at Intel, is first of all, you crawl

and then be humble, listen to customer. And then first step for me is to strengthen my balance sheets, focus on the products, and I really simplify the product, listen to the customer, and then drive the next generation leadership products. And then right now, agentic AI and influence, CPU become highly in demand. And so in some way, I'm happy.

Right now the demand is very high for my CPU. Secondly, very happy that Jensen Huang, my old-time friend, he also put $5 billion in investing and support me. This $5 billion become $25 billion now. If you look at it, 10 years from now, what will be the winning company? The one that... Hi, listeners. Welcome back to No Priors. Today, Alad and I are here with Liputon, the legendary from Walden, then CEO of Cadence, now CEO of Intel. We talk about his plan to transform Intel, having the U.S. 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, Lipu.

Lipu, 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 semis company. Why take the job at all? It's a good question. I'm 66. and people that are, well, you should retire, rather than take on this hardest job in the industry. And so a couple of reasons.

One is this is an iconic company, and it's so important for the semiconductor ecosystem, and also so important for the United States. And so I decided, you know, do one more after Cadence. A lot has happened in this past year. What has been the most surprising to you? Well, the most surprising that I don't learn. from my previous job or even training, is one day, early morning,

President Trump asking me to resign and conflict of interest, and there's no exceptions. And so I had to convince myself, first of all, you know, I don't need this job. I do it purely to save Intel. And so take that personal issue out of the way.

Then I figure out, what can I do to be helpful to Intel? And so good news is I have a meeting, you know, Thursday morning, and then Monday I have the meeting. And then he listened to me, like I have a chance to explain myself. You know, I'm born in Malaysia, growing up in Singapore, went to MIT, and I live in U.S. I never live outside country. And so something that I share, and then somehow he listened very well, and then he gave me the chance, and so I'm delighted. And now you have the chance to do the work. When you said, you know, the job is to save Intel.

it's a really important company, what does that look like to you? What does Intel winning or thriving look like? Yeah, I just passed 14 months. A lot of things happen in this 14 months. So a couple of things. One is to change the culture and clearly want to drive more accountability.

And also in terms of decision making, have to be faster. You know, I'm so used to start up culture and you move fast in the speed of light and don't have that bureaucracy, layer of lay of meeting. And so something that I changed accountability, listen to the customer,

and a customer delighted, someone like Libo, so humble, willing to listen, and then address some of the problem that they face, and then try to delight the customer. And also the other part, from day one, I decided all the engineers report to me. I'm being an engineer by training,

I want to know what went wrong, and what are the things that I need to correct, listen to the customer, and delight the customer, and then make sure that we have the right product, simplify our product line, and really have the roadmap and the vision for the next five, 10 years. What is your vision of where Intel should be in 10 years?

Yeah, I think a couple of things. One, I always believe in when I was at Cadence and also at Intel, is first of all, you crawl and then be humble, listen to a customer, and then secondly, you're starting to walk, and then finally, you're starting to run in spring. So that's kind of my culture of step-by-step doing it. And then first step for me is to strengthen my balance sheets. And the balance sheets really horrible in some way. So I'm delighted, you know, U.S. government become a big shareholder.

Just as I explained to President Trump, TSM when they started, they have the Taiwan government as a shareholder. If you look at Japan, you look at Singapore, this is an infrastructure. U.S. government get to provide the support. Secondly, very happy that Jensen Huang, my old-time friend, he also, also put $5 billion in investing and support me. And I'm glad I'd at least do some good work. His $5 billion become $25 billion now or more. And then the other part is SoftBank Masa.

I used to be at SoftBank Board, and then he lent a hand to help me. So we strengthened the balance sheet and then focus on the products. And I really simplified the product, listen to the customer, and then drive the next generation leadership products. And then in some ways, very lucky. Right now, the agentic AI and influence, CPU become highly in demand. And so, you know, versus 1 to 8 in the training CPU to GPU, now I can see 1 to 4, maybe 1 to 1. And I'm delighted CPU become important.

I talked to some of the AI model and the developer. They said, well, in terms of reinforced learning, in terms of the speed of orchestrating all the agents and turn out the CPU is actually better. And so in some way I'm happy, right now the demand is very high for my CPU. So I think overall, build on the product, on the data center's server side,

then the other part is our foundry business. And initially this is a capital-intensive business, and it's not easy. And you really need to have a couple of things. You need to have all the right IP so that you can support the customer, Like for example, if it is a mobile-related, you've got to have low-power IP set that you need to have. Without that, you cannot serve them.

It's a service business. It's a trust business. If people want to give you, you know, orders to have way forward to come. If the yield is not good, they will be toast in terms of revenue or miss. So with that, I think it's very important to really focus on the yield, defect density, the cycle time, and make sure that you're really able to meet and serve the customer in high quality and reliable. And so those are the things that I really focus on it. And eventually, you have to really move into a full stack.

So not just a silicon, you need to have a software. And some of the customer asked me, give me the whole rack. So there's a system that you have to build. And so I think those are the things that are quietly building step by step and recruit some of the best talent I can find. by the way, all the recruitment, I do it myself. No search firm helping. And so I think sometimes it's good to have a rotor deck that you know who to reach out to call for.

Yeah, I mean, you've been in the business for so long and, you know, you've run a cadence for, I think, 12 years before this. And so 13 years. 13 years. And then two more years as an executive chairman. So 15 years. I signed up for three months. Three months. So right now I'll be very careful.

The moment you said, I just do it for three months. It turned out to be 15 years. Yeah, well, it seems like you have a lot longevity ahead of you here as well. And so the other big initiative that has been sort of talked about is TerraFab and working with Elon Musk on that. Can you tell us a bit more about how that came together and your involvement and how you all are collaborating? Yeah, good.

I mean, Elon Musk, I think we all agree, is one of the best, if not the best, entrepreneur in this century. Yeah, and I, we share the same view that semiconductor infrastructure actually is not catch up with the AI growth. And in terms of you need the capacity, you need to have the productivity and you have the dry efficiency. And so those are the things that he and I

we share that, there's something missing. And then secondly, he just delighted to work with him. And he's very, I call it, unconventional. And he basically questioned every step and why this traditional way of doing things. And in some way, it's very refreshing. And I like that. I like people, have different opinion, and let's work together, find what is the best route,

and we're both going to learn a lot together. And then I think clearly he have a vision that his robots and his car, you know, he need a lot of silicon. Yeah, could you actually explain what tariffab is, or people aren't familiar with it? Yeah, Terry Fab, he decided he wanted to build his own fab. And then meanwhile, we are delighted to work with him, and then make sure that we can work together and enable him to be faster and quicker to the production, and then you'll use it. some of our technology and some of our process. And there's something that we both kind of collaborate together.

And he's a very good team that I work with weekly, and it's just refreshing to work with him. And he's talked about things like he wants you to be able to smoke inside the clean room and all these things that normally are considered. Yeah, yeah. The burger. Yeah. I think I don't go that far.

Maybe some part of the clean room you can do that. But I think something that is open mind, and then we also listen and see whether we can do that. Yeah. I mean, it's very exciting to see how you. or morphing the business here in the U.S. in terms of incrementally building out the foundry business in terms of collaborating with things like Terrafab. If you think about the global AI and semiconductor supply chain, so say that you were to look at the changes that AI is

driving on a macro basis country by country. And if I look at certain countries, when I look at the layoffs that are claimed from AI, for example, most of them, I think, are overstated right now. You know, most of the layoffs are actually just overhiring during 2020 COVID period. But the first things I see actually being cut are outsource 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, which have big BPO's,

the Philippines, India, et cetera. So they may be impacted in the short run by AI. And then if you ask, how do companies participate in the future in a positive way in AI, you have to almost go country by country, right? Places with cheap energy, we'll do data centers, places with the ability to train models, or train models, but it's probably only the U.S. in one or two other places. How do you think about the shifting global supply chain for the semiconductor industry? Should certain countries invest more?

Should Israel be doing more given Melanics and Nvidia and Intel presence there? And should they 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. So I think clearly the AI is changing the whole landscape. And I think the impact will be bigger than Internet. And it's more profound also.

So I think the AI initially is able to help you to do things more efficiently. And then with a lot of agents helping you to do things that is kind of mundane that you need to do, but now they can give it to you faster. So in some way, I think it can drive a lot of efficiency. Even like semiconductor design, how much you can drive the efficiency in terms of timing, how quickly can you come out? and secondly, the cost. And so I think those will be helping you to drive that.

And then I think a couple of bottlenecks for the AI demand and growth. One is, of course, everybody knows power constraint. Some country, the power, they just don't have that. It get impacted. And then secondly, a lot of people didn't realize the helium impact can be also high significant for semiconductor. And then the thirdly is everybody knows right now memory is a bigger shortage.

and everybody tried to scramble for memory. And then even though you want to build the fab to capacity increase, it would take a couple of years to do that. And same thing for CPU, GPU, and all this will be highly demanded. And I think also the pricing also go up because we have to pass the price,

the cost to the customer. So I think those would be the impact, the industry growth. And then I think overall I felt that, you know, the company that most impacted is you are not embroidered, embracing AI. And because AI can help you to drive a lot of efficiency

across all the different functions of the enterprise. We should embrace and also find a way to better use AI for your prediction, for your design, for your, you know, all the different part of the workload. And I think that's tremendous. A number of people would say the simplistic argument against TerraFab against Intel Foundry being competitive is really a question. of, you know, there's all the factors internal to the building, right? You describe IP and

velocity of just how you're doing business. Then there are external factors. And, you know, a lot's talking about a number of them. But one of them is the cost of labor and actually the manufacturing capacity. You know, 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, you know, how real that constraint is? The labor. constraint? Right. So I think, you know, the, when I decided whether it should double down on foundry or should I get out of the foundry. And I come to the- And there's a lot of voices in the marketplace, as you can tell. It's very expensive. It's not going to work. It's not going to work. But I final decided this is very important for United States and also very important for the industry. And I'll give you the idea that, you know, this, we all live through these challenges of supply chain.

And it's very important for any of the big company in semiconductor and really have to think about the supply chains. And you have to have a robust and resilient supply chain. You cannot just depend on one or two player in different geographic goal. And so I think more and more people are going to realize making it in the United States is critical. And then the most advanced process, like for example, we have the 14A is like 1.4 nanometer. and we're already starting to plan for one nanometer and 0.7 nanometer.

It's getting smaller and smaller. So in a way, it's much like our hair so thin. So it's a lot of complexity. It's not that easy to do. And every step, if we make a mistake, that you just go down to drain. So in some way, you have to be really precise in that manufacturing.

So in some way, this has become more and more going to be the bottleneck. So we felt that we, we have a lot of respect for TSMC. We're a great partner. And then more important, we both need to have more capacity to serve the customer. And so I think we decided

by 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. Like the line with just gets too small

to be able to, be able to keep going. When do you think we actually hit that limit? Good question. So I think I can see, you know, right now we have 18A, and now going to production of 14A, I can see 10 and 7. And so I think that path, I think we can get there,

but it could not be more and more expensive and more difficult to do. And that's why we need partners. We cannot just do it ourselves alone, partner with a subscript vendor, partner with equipment vendors, so that make sure that we can really drive those yield and performance. And then the other part also very become the bottleneck is packaging,

the advanced packaging. And so we all know about cohort by TSM. Now we have a really good one called EMIPT that is really next generation. I have to make sure that you become able to do in the production yield that meet the customer requirement. And now Seymour starting to run out of steam like you described. So right now I also look at some new material. So going back to the material size or the chemical table.

So I got down nitride, silicon carbide, and the Indian phosphide. So I invest in all three. And then looking at some of this new material, how can we really drive that? And in terms of packaging, I started to invest into glass. Glass is a very good heat insulator. So I invest an venture site called 3DGS. Then I realized that Intel, we have like, like, 1,000 pattern on the module.

So how the, you know, subscript and the module put it together. And then we just announced a big program with Indian government to manufacturing in India, plus in U.S. and New Mexico. So I think this advanced packaging, very important. I also starting to look at artificial diamond. And that's another very good, you know, insulator. So I also invest into, you know, diamond foundry. And there's something is the next generation to look at.

So new material, new subscript material, and new design methodology to drive that. So when I think about being an engineer's, you're always hitting the wall, then you find a way to either jump over the wall or you work around the wall and then to get to the better result. And that's what I've been, have been a long time as a investor and a building semiconductor from the EDA tool to design to manufacturing. It's kind of nice to have that experience. Now I can help buy a way to make a small contribution to the industry. Yeah, and it's very exciting. And one of the reasons I'm asking about it as well is, to your point, there's always some things that you can vent around,

but there are also physical limits where once you hit seven angstroms or whatever, the limitation is, you start to run into, you need to find new materials or find other workarounds. Yes. 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 a point where we ran out of space on this, is do you run into some, sort of asymptote that actually normalizes performance across different foundries, so we're not.

Yeah, good question. In terms of like most law, it's a double, you know, and then the power and the cost. And then you can double the performance, but you cannot double down on the cost and area. So those are the things you have to give away unless you find some new way of material, new way of design. And then become materialized. I'm starting to hire more people in the material science. So that is kind of innovation in our area. How can we do that? And I still remember 18 years ago,

and I still investing in semiconductor. And actually, most of the VC firm, some of them are a very nice tier one venture firm, a good friend of mine. And initially, the partners meeting, the whole partners in the room, then after I was talking about semiconductor, half make excuse to run out the room.

Then eventually the other half, they said, are valuable, do you have any software service? So then they even left with only two sympathetically listen to me. So it's kind of the history has changed. And now, semiconductor, if you look at it, Jensen is a 5.3 trillion market cap company. And then Broadcom and the TSM is 2 trillion market care company. And Lisa, so my good friend at AMD is almost 800 billion and I'm close to 600 billion. So in some way, it's kind of semiconductor become hot again, and it becomes essential because 15 years, 8, 20 years ago, when I invest in semiconductor, no VC want to join me, except, you know, some of the big corporation, like Samsung, you know, Arm and SoftBank and others and investing with me.

And now I'm starting to see a lot of VC like to come investing in semi-so, I'm very happy. Given the enormous interest in investing in this area that used to be considered too hard, right? Yes. What do you think, I mean, you've been a venture investor with Walden for a very long time as well as an operator. You know, the general fears, I'm just going to list a bunch of them. The general fears have been, it's very capital intensive. And you should tell me what I'm missing. It's very unpredictable in terms of, you know, shipping a design that works missing tape out. And you need to understand the workload very well. I think there's a, there's another. which is just like it's it's very high risk for the customer to switch right i think you know we've been involved in companies together where yes you know there's a design win and then there's

still the question of like scaling order volume um uh and then there's a cyclicality yes right of you know you you build hard manufacturing capacity and demand may may change or not in any any given year um what is your view on how a bunch of you know what makes it hard as an industry and then the secular demand growth from a bunch of different areas, right? So you have the recognition of how important a more diverse supply chain is. And then you have this like explosive demand growth on the AI side. How do you, you're still an investor and then you're making the biggest bet ever, like go be CEO. How do you like 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 just given your your history with it, I think there's a, there's a lot of like yolo action of like, there's a memory shortage by memory stocks, as well as, you know, just an unwillingness to take on things that have a 10-year timeline, like material science. Good.

You have quite a broad range of questions. Let me try to explain that. So first of all, I think, you know, the venture capital startup is in my blood, and I really enjoy it. And so I think this is not tied to brag about it. And so there's some good exit.

You know, I still have 159 IPO, 126, you know, MNA, and that's in crude semiconductor. Just break down to semiconductor, I invest over the years, 200, and 38% is in the U.S. So what I usually look at, some microdustia. Just to be clear, that's incredible. Thank you. Thank you.

It just enjoy building it. But more important, I look at is, first of all, on the investment side, I always look at where is the bottleneck. What are you trying to solve? For example, I invest in a company called Credo Semiconductor, Australia Lab. Is this interconnect become the botanine? So I decided to back, and also back, Celestial AI in the optical side. And then because speed become more important in the interconnect, in the cluster.

So I think optical become very important. Look at Jensen, he invests with almost every company is photonic-related. And then the other part I'm looking at is, you know, okay, what are the solution that need? Like, for example, we talk about design and then the complexity and also the cost. Can you find some using AI machine learning to drive better design and better solution? So a couple of new startup actually go into the EDA-related area to drive performance improvement. I think it's a goal mind to do that. And then the other part, you look at the new material.

We talked about, you know, this Indian fast-fi. That's why I invest in Infi, and then Marvell bought it. And then you invest into some of the new material that gallium nitrite and silicon carbide. And then some of the companies starting to being acquired, include one of them, you know, doing power management. And ADA is a sport called Empower. And so again, this IVR, there's a very, very good area. In power management, it becomes bottleneck now, in terms of converting from 40-volt down to one-volt,

road, and then those, in terms of that conversion, you lost a lot of power and how you do try the power improvement. So I think power, thermal, those become the bottleneck. So I think I always look at from what is the problem we try to solve. Is it real? Is customer crying for it? And then I starting to invest. The next thing is look at, it's very important from day one, you'd have to target the first customer. And usually I like the customer is hyper-scale. They have the scale. If they like what you have, have, they're willing to pay million of dollars next few years, and even giving some warden is worth it because you have a big one customer you can scale. So I always look at some

of the formula, how do you do that, and then where do you get the talent? And then, you know, sometimes it's very important to find the talent. That's why I'm really interested in US, and then Silicon Valley, and then some Austin, and then the other part is Israel, a lot of talent. So I back quite a few quite a significant amount of my investment in Israel. And then because they have very disruptive, innovative entrepreneur, they work really hard. Even in this wartime, they still have conference call. And sometimes they say, okay, there's a warning.

I had to go to underground. And then the internet may not be good. Maybe we just use voice. In some way, it's kind of fun. They kind of resilient entrepreneurship I'd really enjoy. So I think all in all I felt that there's a lot of opportunity and especially in the AI. And right now, besides the Argentic AI,

now you're looking at physical AI is a mixed big frontier. And then you have to really look at a full stack. That's why I'm still involved with a lot of this frontier model that we're very familiar and some of the investment I back because I really like open source frontier, you know, technology for physical AI.

I think that's a goal mind. You mentioned the opportunity to make certain parts of the design and test. of chips faster, cheaper, more creative with AI. Given your cadence experience, like, what do you think is most fertile? Is there anything you think is already working? Yeah, I think, you know, for almost 15 years with cadence,

and I'm so happy. One of my highlight is able to find my successor on the road, and I train him, and he becomes super great CEO. And then he really embracing the AI, you know, driving the agentic AI to the, drive more efficient. But there's good part. I think synopsis. Sarsin also tried to do that. And they have an investment from, you know, Nvidia to billion. I think helping him to do a lot and he acquired answers to move into the whole system design. So I think all in all, they all

do the best thing they can. But also some opportunity for startup to do some of the more disruptive and then eventually they can I go public or being acquired by both of them or seamen to acquire them. So I think there's opportunity for all, depend on what the entrepreneur vision. And then as long as I always have philosophy, if entrant-burner want to sell the company and this quicker way for exit, you don't have a lock-up,

you don't have to worry about quarter-to-quarter earning. And then some entrepreneurs, from day one, they want to go IPO, you know, for being a VC, I think three of you, with three of us, we all VC, we support the entrepreneur, their dream, and then help them to fulfill their dream. Yeah. If you look at the different areas that you mentioned in terms of future, either product

development or impact of AI on the semiconductor industry, there's companies like periodic doing materials, there's pure point folks working it on the EDA side and design and other aspects and sort of throughout the chain of manufacturing. Do you think that either Intel or future semiconductor company 10 years from now looks radically different from today, given AI? And if so, how? Yeah, I think so. I think first of all, back to a start of are your question about capital intensive and a little bit unpredictable and cyclical. So you have to kind of put that into a factor into your decision-making investment. You know, I usually like to go in very early, put a team together.

It's kind of fun to do that. I think you also do that. And then secondly, you try to find the right investor that can co-partner with you. It's not just forever the brain and firm. I usually go for the individual. and where are the individual that really knowledgeable in this space, you can, the most important to find a partner to difficult time and good time. A lot of the time people are very enjoyable working with you.

It's a good time. When the company, no trouble, they just walk away. I like to have a partner that really work through a lot of successful company. They have multiple time almost bank club that eventually take off. So I think it's important to find a partner willing to do that. And then the other part is look at the product, the strategic investor that can help you either in manufacturing or memory, connectivity, or various ways to add value to the company. And also have a couple of friends there in the growth stage and also in the hedge fund. And I really enjoy them because they have a different perspective.

They know about the public market. You can guide the company, entrepreneur, where not to go. And so those can be very helpful. So I think all you know, I think is just fun to do that. And then just realized, it's an engineering for a startup, it's like problem solving. Each step of the way you have to find people to help you to solve the problem. And then if you trigger that, then great next frontier to work on. And then, frankly speaking, I look back, nine of the ten companies I invest,

halfway they change their business plan because market have changed. So I like to have an entrepreneur as a team, not just one person. Secondly, open mind. you're willing to listen and listen, you know, getting coaching from us. And then eventually they formulate their own plan. It's not just do what I want. It's more they figure out the best thing is you get them enough feedback. They draw their own conclusion that you exactly what you like and all different,

that you can embrace. It's the right decision. That's kind of fun of doing startup. They can march faster. So back your question, if you look at it 10 years from now, what will be the winning? company, this is just my personal view, the one that articulate and laser focus on one niche area and also find the right partner and also able to skill the company. And so in some way,

I'm back to my point about full stack. So in the way, you need to have a full stack solution. And so it can be a big company. They transform themselves to be looking at big platform. like Jensen, I admire him. He focused on Kudak. He focused on the liberal. I want to be a platform company, and he did it. And so in some way, you can do that. Or a startup company, like Entropic, Open AI,

they find a way to do it in a more elegant way. They change the game. And then they start up, move fast, speed of light. You can really become a dominant player. And hopefully Intel can play the role because we have the XPU and we have the EMPU, and we have the advanced packaging and we have Foundry,

if you put that all together, can build some of the purpose, build silicon for different workload. I think that's where I'm going. Yeah, that makes a lot of sense. And I guess part of the question I was wondering is where you're going and the other part is,

does it fundamentally change how you work? Because when I look in the software world, I think there's a very big shift happening right now in terms of who you hire, in terms of who you think you want on board, in terms of people managing multiple agents. And so, you know, many people now that,

I know are hiring people more in their 30s, 40s, 50s because they're used to managing teams. Yes. And they think that transfers directly over to managing agents in terms of understanding the complexity of what to set up and the QA and everything else. And I wonder in the context of the physical world or in the context of a fab, how you think about shifts in terms of either team structure or capabilities or how AI layers on. And so I just wasn't sure if it's a natural slow evolution or if there's areas where there's a radical shift where it's like, oh, for materials, now we should just use these three

models plus some chemistry or whatever it is. So that's why I was a little bit curious about how you think about the future world there. Good question. I think, you know, as I back to that, Crawl, walk, and run. So I think Crawl, you basically try to, I recruit some of the best talent in the semiconductor industry. And then now I'm starting to look at

what are the software talent I need to bring on board in order to build a full stack. And now I'm starting to look at, you know, my average age of my team in the late 40, 50, I need to bring in some new talent. And then, so they're understanding the workload, understanding the frontier model, open source,

that is important. So for now that my son become my teacher now. So every time he invite me to go to his house, we're playing the grandkids. I'm starting to tap on him on all the AI machine learning. He's more plug-in than me. So I learned a lot and then try to understand investing and then bring some of the talent to come.

So we are changing Intel. It used to be a very old legacy spreadsheet company. Now I'm transforming it to become AI-A-Nable using some of our design and also across all the organization embracing AI. And so they'll become less depend on the spreadsheet and label to do that. And you're going to combine the tool talent plus the best AI tool that I can use not only for my organization, not only for my sales,

and then now I'm starting to look at not just marketing, and now the design, and then to embrace that. I think a lot of investors, you know, at least for me the last few years since I started a firm, it's been very educational thinking about the different capital sources for more capital-intensive companies. I did a lot of software before. And so you need to have smart friends

with a very different stance and balance sheet was less if you're like, I need $150 million before this thing gets to, you know, some critical mass. And so 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, it's led to huge successes like TSM, right, the most important companies in the world? it's also been a bit frowned upon in American business culture for a long time.

How do you think that should change now or where is it relevant? Good question. So I think clearly, you know, for capital-intensive business and infrastructure play, you need to access to the capital. And then in some way, I think, for our early-day venture capital investment,

you know, now starting to become very capital-intensive. Yes. And some of the venture firm willing to put one billion into some company is very unheard of in the VC business. Now it's happening. Yeah. And so in some way, you just have to be, you know, I like this kind of bell curve. Either you're going very early and because it's starting to do the Series A is over one billion valuations. And so you had to go in pre-money, precede to go into that kind of a 2030 billion valuation.

It's very rare right now. So you just have to do that. pick the right one. And then the other part is able to find capital to scale. And that's why some of this mutual fund, they also like to move into the pre-market, early states to join me to investing. I delight them because they are very less sensitive

of whether I had to own 20% of the company. There's not too many 20% to give. So you have to find the right investor to come in. And then in terms of the capital intensive, like AI in a factory and also the foundry, and then you really need to tap either government funding or some solvent fund and also some very big capital, you know, there's some big fund they're doing that and the fund they've organized is basically support the infrastructure.

And we like to tap into some of them and then to make sure that they can scale our operation. So I think in overall, government, solvent fund has become very important. And also as a public company, I also purposefully want to focus. on some of the investor, there are more long-term growth-oriented, and so that they can help me to grow the business. And then rather than short-term, asking capital location,

you know, where you're going to buy back your shares, those are good questions, but meanwhile, I also had to build the business. And so I think it's kind of that balance is important. Do you think there is something that investors, like most misunderstand about Intel at this moment? Quite a few things. First of all, I think,

you know, as a back to this, crawl, run, and walk. Last four months, I crawled. But the people are starting to recognize that potential of it. And so the other part is very important. We need to really get the best product out. Either PC client, we still have a market share. But we really need to really build more,

better performance. So that's why I'm quietly building up the CPU architect, GPU architect, and the software architect. so that we can leapfrog, just like, I look at Intel, I want to be a multiple of startup culture so that we move fast and we can leapfrog using better technology. And then the other part is beside the product,

there are some new energy coming in, like an agentic AI, the physical AI. That's a lot of areas that we can invest. Market is huge. That's on the product side. And the foundry side, we are very distant from TSMC, and then in terms of their performance, So we have to be humble looking at building the building block

like 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 the wafer to count on you. So those are the things that will take longer time. But I think by 2030, 2013, I think I was starting to surface up People may not understand how big potential I can be in terms of product, a PC client, that's our blood and butter.

And we move up to the edge and move into the physical AI and agentic AI. And because right now, in the past, you basically provide the server, provide the PC for human. Now you're starting to have another different dimension. It's millions of agents. They need to expect to compute. the access into the software stack. So I think that part, I think we have a chance to really play.

The game is not over yet. We can play on the injected AI and also the physical AI. So that's kind of where I'm going. And the AI is just the beginning. You know, you have the training that Jensen owns, the edge and also, you know, in terms of agentic AI with agents. And also physical AI, I think, is the jumbo. Everybody have a chance.

So I think that's part that I want to go for it. So I think hopefully the investor will know, even though in 14 months, you know, we make six-time return to the shareholder. It's just a beginning. We still have a lot of room to go. There's venture returns from here. Yeah. So, you know, I always look for 10x. Yeah.

You know, being a venture at heart, you want to look for 10x. And now at Cadence, when I step now as a CEO, I think we make about close to 76 times. and starting from interim CEO $2.42. And then when I retire as executive chairman, about 85 times return to the shareholder. So it's hard to do that at Intel because the base is bigger. So I kind of said, okay, let's do it at 10x. And five years, 10 years, if we can do 10x,

I think it's a good return, being a venture capital at heart. That's kind of my goal. So there's a, Godspeed on this very, very large mission from this from this huge base already. There's an embedded belief in what you described about where the workload is, right? Where I think some would say like, we're just going to build bigger and bigger data centers

and a gigawatt is the beginning. And then, but the centralization and the efficiency from running, even the inference compute in a centralized way is the dominant way versus thinking about the edge, thinking about the client. Do you think that there's like an equilibrium state that you believe in of 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. You know, right now there's a massive buildup in terms of the AI. I think it's the right thing to do. I don't see that's going to anything to throw it down because the workload is increasing a lot. And then I think the question mark is how can... And we are supply constraint.

Well, supply constraint. Yeah. So I think anything slowdown is the supply constraint. But I think the other part is I always look at all this infrastructure built out. At the end, you have to look at what is the solution, what is the application you want to drive. And I'm more focused on application. So if you can identify the application that is humongous or add up a few applications to become meaningful, and you focus on that, it's not everybody built going to be winning.

And so some are going to be winning big time. and some are going to lose over time or go sideways. So, you know, just like internet, you can see some of them turn out to be very big, like Amazon, like Netflix, and then some of them is kind of go sideways and disappear or being acquired. And so I think to me it's the same approach. Then they really focus on what application they try to serve, and that application, how big is that?

And whether it's sustainable or not, or it's very crowded. So if it's too crowded, you know, maybe one or two minutes of that. the other maybe just consolidate. So I think this industry go through that big growth and then starting to consolidate maybe eventually one or two becomes a real winner. So I think that's kind of, we've watched the movie before, so it's not surprised to me.

But focus on application like Netflix is an application. You know, Amazon is a real application. That to me, they're winning. But you're assuming that some of these applications, they will be better served by client. or edge compute than the, then only by the data center. Exactly. Exactly. Yeah. I mean, I will say as a, I'm an investor in a number of companies that, you know, they're doing robotics, they're doing defense. And so the compute on the device

is a very important choice in terms of our and what we assume around it. Like let's say if a robot in the home eventually, like what you assume is in the home and in connectivity around it determines what you're able to do. And I think that that's been kind of, it was kind of forgotten for a little bit in the SaaS era? Yes. Yes. I think my investment thesis is find a problem that is really need to solve. And secondly, who will be the player that you can partner with?

And then thirdly, look at the application. How big is that application? Is that sustainable? And if it's really big, you believe in it, double, 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, Lippoo. Thank you. Find us on Twitter at NoPriarsPod. Subscribe to our YouTube channel if you want to see your faces, follow the show on Apple Podcasts, Spotify, or wherever you listen. That way you get a new episode every week. And sign up for emails or find transcripts for every episode at no dash priors.com.