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

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 [email protected] 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

• 0:00Speaker 00

  Nine of the 10 companies I invest, halfway they change their business plan because markets have changed. Yeah. So I like to have entrepreneur as 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 customer and then drive the next generation leadership products. And then right now the Agentic AI and Influence CPU become in a 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.

• 0:44Speaker 00

  This 5 billion become 25 billion now. If you look at it 10 years from now, what do we be the winning company? The one that.

• 1:00Speaker 01

  Hi listeners, welcome back to No Priors. Today, Alad and I are here with Liputan, 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, 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?

• 1:33Speaker 00

  It's a good question. I'm 66 and people thought, well, you should retire rather than take on this hardest job in the industry. And so a couple of reasons. One is this iconic company and it's so important for the semiconductor ecosystem and also so important for United States. And so I decided, you know, do one more. After cadence.

• 1:57Speaker 01

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

• 2:02Speaker 00

  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, born in Malaysia,

• 2:44Speaker 00

  grown up in Singapore, went to MIT and I live in US and never lived 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.

• 2:57Speaker 01

  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?

• 3:07Speaker 00

  Yeah, I just passed fourteen months. A lot of things happened in this fourteen months. So a couple of things. One is to change the culture and then clearly want to drive more accountability. And also in terms of decision making had to be faster. You know, I'm so used to startup culture and you move fast in the speed of light. And going to have that bureaucracy layer of layer of meeting. And so something that I changed accountability, listen to the customer. And a customer delighted, you know, someone like Liverpool 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 engineering report to me.

• 3:51Speaker 00

  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.

• 4:08Speaker 02

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

• 4:11Speaker 00

  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 customer. And then secondly, you're starting to walk. And then finally, you're starting to run and sprint. 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 have horrible in some way. So I'm delighted, you know, US government become a big shareholder. Just I explained to President Trump, TSMC, when they started, they have the Taiwan government as a shareholder. If you look at Japan, you look at Singapore, this is the infrastructure. US government get to provide the support.

• 4:56Speaker 00

  Secondly, very happy that Jensen Huang, my old time friend, he also put five billion in investing and support me. And I'm glad I at least do some good work. His five billion become twenty five billion now and or more. And then the other part is SoftBank Master. I used to be a 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, you know, highly in demand.

• 5:37Speaker 00

  And so, you know, versus one to eight in the training CPU to GPU. Now I can see one to four, maybe one to one, and I'm delighted CPU become important. I talked to some of the AI model and developer, and they said, well, in term of reinforced learning, in term of the speed of orchestrating all the agents, and turn out the CPU is actually is 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 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.

• 6:21Speaker 00

  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 enough orders to have wafer to come, if the yield not good, there will be toes in terms of revenue miss. So with that, I think it's very important to really focus on the yield, the defect density, the cycle time, and then 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.

• 7:03Speaker 00

  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 ask 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 I 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 roller deck that you know who to reach out to call for.

• 7:33Speaker 02

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

• 7:38Speaker 00

  Thirteen years.

• 7:39Speaker 02

  Thirteen years, sorry, yeah, yeah.

• 7:40Speaker 00

  And then two more years as executive chairman, so fifteen years.

• 7:43Speaker 02

  Fifteen years.

• 7:44Speaker 00

  I signed up for three months, three months. So right now I'd be very careful. The moment you said, I just do it for three months, it turned out to be fifteen years.

• 7:53Speaker 02

  Yeah, well, it seems like you have a lot of longevity ahead of you here as well. And so the other big initiative that 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?

• 8:06Speaker 00

  Yeah, good. I mean, Elon Musk, I think we all agree is one of the best, if not the best, entrepreneur in this century. Here and now we share the same view that semiconductor infrastructure actually is not catch up with the AI growth.

• 8:23Speaker 00

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

• 9:05Speaker 02

  Yeah. Could you actually explain what Terrafab is for people who aren't familiar with it?

• 9:08Speaker 00

  Yeah, Terrafab, he decided he want 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 using some of our technology and some of our process. And that's something that we both can collaborate together. And he's a very good team that I work with weekly and it's just refreshing to work with him.

• 9:32Speaker 02

  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 very.

• 9:38Speaker 00

  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 are also listen and see what we can do there.

• 9:49Speaker 02

  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 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 over hiring during 2020.

• 10:19Speaker 00

  Covid period.

• 10:20Speaker 02

  Covid period. But the first things I see actually 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, which have big BPOs, the Philippines, India, et cetera. And 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 will do data centers. Places with the ability to train models will train models, but it's probably only the US and one or two other places. How do you think about the the shift in global supply chain for the semiconductor industry? Should certain countries invest more? Like, should Israel be doing more, given Melonics and Nvidia and Intel presence there? And should they try to do more in semiconductors?

• 11:04Speaker 02

  Should other, should the Philippines move back to more of a manufacturing base? Like, how do you think about that on a global basis?

• 11:10Speaker 00

  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, you know, initially is able to help you to do things more efficiently. And then with a lot of agent helping you to do things that is not 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 the semiconductor design, how much you can drive the efficiency in term of timing? How quickly can you come out? And secondly, the cost. And so I think those will be helping you to drive that.

• 11:52Speaker 00

  And then I think a couple of bottlenecks for the AI, you know, demand and growth. One is, of course, everybody knows the 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 very significant for semiconductor. And then the thirdly is everybody know right now memory is the biggest shortage. And everybody tried to scramble for memory. And then even though you have to build a 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 the also the pricing also go up because we have to pass the price, the cost to the customer.

• 12:37Speaker 00

  So I think those will 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 embracing AI. And because AI can help you to drive a lot of efficiency across all the different function 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.

• 13:08Speaker 01

  A number of people would say the simplistic argument against TeraFab, against Intel Foundry being competitive is really a question of, you know, there's, there's all the factors internal to the building, right? You described 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, 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?

• 13:47Speaker 00

  Right. So I think, you know, the when I decided whether should double down on foundry or should I get out of the foundry? And I

• 13:56Speaker 01

  And there's a lot of voices.

• 13:57Speaker 00

  A lot of voices in the marketplace, as you can tell.

• 14:00Speaker 01

  It's very expensive.

• 14:01Speaker 00

  It's very expensive, it's not gonna work. But I finally 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 this challenges of supply chain. And it's very important for any of the big company in semiconductor and really had to think about the supply chains. And you, 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, you know, the more and more people are gonna realize making in United States is critical. And then the most advanced process, like for example, we have the In the fourteen A is like one point four nanometer.

• 14:45Speaker 00

  And we are already starting to plan for one nanometer and zero point seven 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 you make a mistake, that you just go down, you know, go down the drain. So in some way, you have to be really precise and in that manufacturing. So in some way, this has become more and more going to be the bottleneck. So we felt that we, you know, we have a lot of respect for TSMC. We are great partner. And then the more important, we both need to have more capacity to serve the customer. And then, so I think we decided by the bullet longer term, I think it's critical.

• 15:30Speaker 00

  And then that's where I can create more value for the industry.

• 15:34Speaker 02

  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 which is just too small to be able to keep going. When do you think we actually hit that limit?

• 15:49Speaker 00

  Good question. So I think I can see, you know, right now we have eighteen A. And then now going to production of fourteen A, I can see ten and seven. 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 Cool Water by TSMC. Now we have a really good one called E-MEPT that is a really next generation.

• 16:31Speaker 00

  I had to make sure that you become able to do in the production yield that meet the customer requirement. And now C more starting to run out of steam like you described. So right now I also look at some new materials. So become going back to the material size or the chemical table. So gallium nitride, silicon carbide and the Indian phosphate. So I invest in all three. And then looking at some of this new material, how can we really drive that? And then in term of packaging, I starting to invest into glass. Glass is a very good heat insulator. So we I even invest adventure cycle three DGS. Then I realized that Intel, we have like one thousand pattern on the module.

• 17:14Speaker 00

  So how the in a subscript and the module put it together. And then we just announced a big program with Indian government to manufacturing in in India plus in US 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 and insulator. So I also invest into, uh, you know, diamond foundry. And that's something is the next generation to look at. So new material, new subscript material and new, you know, uh, design methodology to drive it. So one thing good about being an engineer, you're always hitting the wall. Then you find way to either jump over the wall or you work around the wall.

• 17:57Speaker 00

  And then to get to the better result. And that's what I've been, uh, have been long time as an investor and a building semiconductor. From the E D A tool to design to manufacturing. It's kind of nice to have that experience. Now I can help by a way to make a small contribution to the industry.

• 18:16Speaker 02

  Yeah, no, 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 run around. But there are also physical limits where once you hit seven angstroms or whatever the limitation is, you start to run into.

• 18:26Speaker 00

  New material.

• 18:27Speaker 02

  Yeah, you need to find new materials or find other workarounds.

• 18:29Speaker 00

  Yes.

• 18:30Speaker 02

  Um, and then the interesting question is, uh, and we've been talking about this for a long time. I remember twenty years ago, people were talking about how we'd eventually hit this, hit a point where we ran out of space on this. Um, is do you run into some sort of asymptote that actually normalizes performance across different foundries or not?

• 18:44Speaker 00

  Yeah, good question. In term of like most law is a double, you know.

• 18:49Speaker 02

  Yeah.

• 18:50Speaker 00

  And then the power and the cost. And then you can double the performance, but you cannot double down on the cost and and area. So those are the thing here to give give way unless you find some new way of material, new way of design.

• 19:06Speaker 02

  Yeah.

• 19:07Speaker 00

  And then become material side, I 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. Eighteen years ago, and I I still investing in semiconductor. And actually, most of the VC firm, some of them are 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 talking about semiconductor, half make excuse to move out of the room. Yeah. Then eventually, the other half, they said, available, do you have any software service? Ah. So then they went left with only two sympathetically listen to me. So it's kind of the history have changed.

• 19:50Speaker 00

  And now semiconductor, if you look at it, Jensen is a five point three trillion market cap company. And then Broadcom and TSMC is two trillion market cap company. And Lisa, so my good friend at AMD is almost eight hundred billion, and I'm close to six hundred billion. So in some ways, kind of semiconductor become hot again. And it become essential because fifteen years, eight, twenty 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 then now I starting to see a lot VC like to come investing in semi, so I'm very happy. Hmm.

• 20:32Speaker 01

  Given the enormous interest in investing in this area that used to be considered too hard, right?

• 20:39Speaker 00

  Yes.

• 20:39Speaker 01

  Um, what do you think? I mean, you've been a venture investor with Walden for a very long time, as well as an operator. Uh, you know, the the general fears, I'm just gonna list a a bunch of them. Um, the the general fears have been, uh, it's very capital intensive. Um, 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. Um, and uh, you 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.

• 21:11Speaker 00

  Yes.

• 21:11Speaker 01

  To switch, right? I I think, you know, we've been involved in companies together where.

• 21:15Speaker 00

  Yes.

• 21:16Speaker 01

  You know, there's a design win, and then there's still the question of like scaling order volume. Um. And then there's a cyclicality.

• 21:23Speaker 00

  Yes.

• 21:23Speaker 01

  Right of, you know, you you build hard manufacturing capacity and demand may may change or not in any any given year. What is your view on how a bunch of, you know, what makes it hard as an industry? And then the the secular demand growth from a bunch of different areas, right? So you have the recognition of how important the 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

• 22:07Speaker 01

  think there's a there's a lot of like YOLO action of like, there's a memory shortage, buy memory stocks as well as, you know, just unwillingness to take on things that have a 10 year timeline like material science.

• 22:20Speaker 00

  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, M and A, and that's include semiconductor. Just break down to semiconductor. I invest over the years 238% is in US. So what I usually look at semiconductor.

• 22:57Speaker 01

  Just to just to be clear, that's incredible.

• 22:59Speaker 00

  Thank you. Thank you. It's just enjoy building it. And but more important, I will look at is first of all, on the investment side, I always look at where is the bottleneck? What are you trying to solve? And for example, I invest in company called Crado Semiconductor, Australia Lab. Is this interconnect become the bottleneck? So I decided to back and also back Celestial AI in the optical side.

• 23:25Speaker 01

  Yeah.

• 23:25Speaker 00

  And then because speed become more important in the interconnect in the cluster. So I think optical become very important. Look at Jensen, he invest in almost every company is photonic related. Uh huh. And then the other part I'm looking at is, you know, okay, what are the uh 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 a better design and better solution? So a couple of new startup actually go into the EDA related area to drive performance improvement. Uh huh. I think it's a goldmine to do that. And then the other part you look at the new material.

• 24:05Speaker 00

  Uh we talk about, you know, this uh you know, Indian phosphide, that's why I invest in Inphi and then Marvell bought it. And then uh then you invest into some of the new material, that gallium nitride and then silicon carbide. And then some of the companies starting to being acquired, include one of them, you know, doing power management. And EDA is a sport called M Power. And so again, this IVR, that's a very, very good area in power management become bottleneck now. In term of converting from forty volt down to one volt. And then those in term of that conversion, you lost a lot of power and how you do drive the power improvement. So I think power, thermal, those become the bottleneck. So I think I always look at from.

• 24:48Speaker 00

  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 is very important from day one. You'd have to target the first customer. Uh huh. And usually I like the customer is hyperscale. They have the skill. If they like what you have, they're willing to pay million of dollars next few years. And even giving some warrant 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, yeah, 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.

• 25:33Speaker 00

  A lot of talents, so I back quite a few, quite a significant amount 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 suddenly say, okay, there's a, 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 ways, kind of fun, they kind of resilient entrepreneurship, I really enjoy. So I think all in all, I thought that there's a lot of opportunity and especially in the AI. And right now beside the Agentic AI, now you're looking at physical AI, it's next to makes big frontier. And then you had to really look at a full stack. That's why I'm still involved with a lot of this frontier model that we very familiar.

• 26:18Speaker 00

  And some of the investment I back because I really like open source frontier, uh, you know, technology for physical AI. I think that's the goal, my.

• 26:27Speaker 01

  You mentioned the opportunity to uh make certain parts of the design and test of um uh of chips uh faster, cheaper, more creative with AI. Um, given your cadence experience, like where do you, what do you think is most fertile? Is there anything you think is already working?

• 26:45Speaker 00

  Yeah, I think you know, uh, for almost fifteen 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 drive more efficient. Uh, but it's good part, I think synopsis, Sashin also tried to do that. And they have the investment from, you know, Nvidia two billion, I think helping him to do a lot. And he acquired answers to move into the whole system uh 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.

• 27:27Speaker 00

  And then eventually they can I go public or being acquired by both of them or semen 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 entrepreneur want to sell the company and it's quicker way for exit. You don't have a lockup, you don't have to worry about quarter to quarter earning. And then some entrepreneur, they 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 I help them to fulfill their dream.

• 28:02Speaker 02

  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 to your point, folks working on the EDA side and design and other aspects. And sort of throughout the chain is 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?

• 28:28Speaker 00

  Yeah, I think so. I think first of all, back to Sarah, your question about capital intensive and a little bit unpredictable and cyclical. So you have to kind of put that into factor into your decision making investment. And 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 whatever the brain and firm, I usually go for the individual. And if we're 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 time people are very enjoyable, working with you is a good time.

• 29:13Speaker 00

  When the company do trouble, they just walk away. I like to have 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 both important to find a partner willing to do that. And then the other part is look at what are the strategic investor that can help you either in manufacturing or memory connectivity or various way to add value to the company. And also have couple of friend, they are 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. He can guide the company entrepreneur where not to go. And so those can be very helpful. So I think all in all, I think it's just fun to do that. And then just realize

• 29:59Speaker 00

  is engineering for startup is 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 frankly speaking, I look back. Nine of the 10 company I invest, halfway they change their business plan because market have changed. So I like to have entrepreneur as team, not just one person. Secondly, open mind, you know, 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

• 30:44Speaker 00

  that you can embrace is the right decision. That's kind of fun of doing startup, you know, they can much 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 scale 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 really, you know, transform themselves to be looking at big platform. Like Jensen, I admire him. You know, he focus on Kuda, he focus on Libo.

• 31:28Speaker 00

  I want to be a platform company and he did it. And so in some way you can do that. Or startup company like Entropic, OpenAI, they find a way to do it in a more elegant way. They change the game and then it startup move fast, you know, 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 advanced packaging and we have foundry. If you put that all together, can build some of the purpose built silicon for different workload. I think that's where I'm going.

• 32:03Speaker 02

  Yeah, that makes a lot of sense. And I guess part of the question I was I was wondering is where you're going. And then 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 thirties, forties, fifties because they're used to managing teams.

• 32:25Speaker 00

  Yes.

• 32:25Speaker 02

  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 there's 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 A 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.

• 32:57Speaker 00

  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 starting to look at what are the software talent I need to bring on board and in order to build a full stack. And now I starting to look at, you know, my average age of my team in the forty, late forty, fifty. I need to bring in some new talent. And then so then 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 to grandkids.

• 33:39Speaker 00

  I starting to tap on him on all the AI machine learning is more plugin than me. So I learned a lot and then try to understand investing and then bring some of the talent to come in. So we are changing Intel, used to be a very old legacy spreadsheet company. Now I'm transforming it to become AI nine. And AI enable using some of our design and also across all the engine, all the organization embracing AI. And then so they'll become less, less depend on the spreadsheet and label to do that. And you're going to combine the two talent plus the best AI tool that I can use, not only for my organization,

• 34:23Speaker 00

  not only for my sales, and then now I starting to look at not just marketing and now the design and then to embrace that.

• 34:31Speaker 01

  I think a lot of investors, you know, at, 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, and so your need to have smart friends with a very different stance and balance sheet was less if you're like, ah, I need a hundred fifty million dollars before this thing gets to, you know, some critical mass. And, 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 TSMC, right?

• 35:15Speaker 01

  The most important companies in the world. It's also been a bit frowned upon in American business culture for a long time. Like, how do you think that should change now or where is it relevant?

• 35:26Speaker 00

  Good question. So I think, you know, 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.

• 35:45Speaker 01

  Yes.

• 35:45Speaker 00

  And some of the venture firm willing to put one billion into some company is very unheard of in the VC business now is happening.

• 35:52Speaker 01

  Yeah.

• 35:53Speaker 00

  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 then because it's starting to do the series A is over one billion valuations. And so you had to go in pre-money, uh, pre-seed to go into that kind of twenty, thirty billion valuation. It's very rare right now. Yeah. 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, uh, early states to join, join me to investing. I delight them because they are very less sensitive of whether I had to own twenty percent of the company. There's not too many twenty percent to give.

• 36:36Speaker 00

  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, uh, you know, there are some big fund that doing that. And they are really, 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 have become very important. And also as a public company, I also purposely want to focus on some of the investor.

• 37:16Speaker 00

  They 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, you know, buy back your shares. Those are good question, but meanwhile, I also had to build the business. Yeah. And so I think it's kind of the balance is important.

• 37:35Speaker 01

  Do you think there is something that investors like most misunderstand about Intel at this moment?

• 37:42Speaker 00

  Quite a few things. First of all, I think, uh, you know, as a back to this, uh, crawl, run and walk. Last four months I crawl and then, but the people 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 perform, 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.

• 38:25Speaker 00

  And then the other part is beside the product, there are some new energy coming in like in agentic AI, the physical AI, that's a lot of area 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 term of their performance. So that's 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 is a trust business. People want to trust you before they give you the wafer to count on you. So those are the thing will take longer time. But I think by two thousand thirty, two thousand thirty

• 39:09Speaker 00

  two, thirty one, thirty two, I think I was starting to surface up. People may not understand how big potential I can be in term of product, you know, the PC client, that's our bread and butter. And we moved up to the edge and move into the physical AI and agentic AI. And because not right now, in the past, you basically provide the server, provide the PC for human. Now it's starting to have another different dimension is millions of agent, they need to come exactly to compute, the access into the the software stack. So I think that part, I think we have a chance to really play. The game is not over yet.

• 39:50Speaker 00

  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 a beginning. You know, you have the training that Jensen own and the edge and also in term 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. And so I think hopefully the investor will know, even though in fourteen month, you know, we make six time return to the shareholder, they just a beginning. We still have a lot of room to go.

• 40:23Speaker 01

  There's venture returns from here.

• 40:24Speaker 00

  Yeah. So, you know, I always look for ten X, you know, being a venture at heart, you want to look for ten X. And at Tadens, when I stepped down as a CEO. I think we make about close to seventy six time, you know, starting from interim CEO, two dollar forty two cent. And then when I retire as executive chairman, about eighty five time return to the shareholder. So it's hard to do that at Intel because the base is bigger.

• 40:51Speaker 01

  Uh huh.

• 40:52Speaker 00

  So I kind of said, okay, let's do it at ten X, you know, and then and five year, ten years, if we can do ten X, I think it's a good return, uh, being a venture capital at heart. That's kind of my goal.

• 41:04Speaker 01

  So there's a godspeed on this very, very large mission from this, um, from this huge base already. Um, 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 gonna be build bigger and bigger data centers and a gigawatt is the beginning and then, uh, uh, but the, the centralization and the efficiency from running even the inference compute in a centralized way is the, is the dominant way versus thinking about the edge, thinking about the client. Um, do you think that there's like an equilibrium state that you believe in of where the compute is or, or is it just we will find out from the workload? How do you think about that?

• 41:46Speaker 00

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

• 42:03Speaker 01

  And we are supply constraint.

• 42:04Speaker 00

  We're a supply constraint.

• 42:05Speaker 01

  Yeah.

• 42:05Speaker 00

  So I think anything slowed down is a supply constraint. But I think the other part is, uh, I always look at all this infrastructure buildup. 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 application to become meaningful and you focus on that, it's not everybody built gonna be winning.

• 42:33Speaker 01

  Uh huh.

• 42:33Speaker 00

  And so some gonna be winning big time and some gonna lose over time or some 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 is 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 is very crowded. So if it's too crowded, you know, maybe one or two may survive. 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 become the real winner.

• 43:17Speaker 00

  So I think that's kind of a, we've watched the movie before. So it's not a surprise to me, but focus on application like Netflix is application. You know, Amazon is a real application that to me they're winning.

• 43:31Speaker 01

  But you're assuming that some of these applications, they will be better served by client or edge compute.

• 43:36Speaker 00

  That's correct.

• 43:37Speaker 01

  Than than than only by the data center.

• 43:39Speaker 00

  Exactly.

• 43:39Speaker 01

  Okay.

• 43:40Speaker 00

  Exactly.

• 43:40Speaker 01

  Yeah, I mean, I will say as a, I'm an investor in a number of companies that, you know, they're, 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.

• 44:01Speaker 00

  Yes.

• 44:02Speaker 01

  And I think that that's been kind of, it was kind of forgotten for a little bit in the, in the SaaS era.

• 44:06Speaker 00

  Uh huh. Yes. Yes. I think I'm more, my investment thesis is finding 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.

• 44:27Speaker 01

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

• 44:33Speaker 02

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

• 44:36Speaker 00

  Thank you so much.

• 44:37Speaker 01

  Thanks, Lipton.

• 44:38Speaker 00

  Thank you.

• 44:41Speaker 01

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