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

[00:00:00] Nine of the 10 company I invest, halfway they change their business plan. Because market have changed. >> Yeah. >> 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 sheet, 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 agenda AI and influence CPU become, you know, highly in demand. And so in some way I'm happy right now that demand is very high for my CPU. Secondly, very happy that Jensen Huang, my old time friend, uh he also put 5 billion uh in investing and support me. This 5 billion become 25 billion now. If you look at it, 10 years from now, what are we be the winning company? The one that [00:01:00] >> Hi listeners, welcome back to No Priors. Today a lot and I are here with Lip-Bu Tan, the legendary investor from Walden, then CEO of Cadence, now CEO of Intel. We talk about his plan to transform Intel, having the US government as a major shareholder, how to be an amazing semiconductors investor and whether or not we can make chips in the United States. Welcome, Lip-Bu. Lip-Bu, it's great to see you. We'll start with the obvious question. This is a really hard job to go be CEO of this incredibly important um American semis company. Why take the job at all? >> It's a good question. I'm 66 and people thought that uh well, you should retire rather than taking on this hardest job in the industry. And so a couple reason, one is uh this iconic company and is so important for the semiconductor ecosystem and also so important for 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 [00:02:01] 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 so convinced 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 what can I do to be helpful to Intel. And so good news is uh 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, grown up in Singapore, went to MIT and I live in US and never live outside country. And so something that I share and that somehow he listened very well and then uh he give me the chance and so I'm delighted. >> And now you have the chance to do the work. Um when you said, you know, the [00:03:01] the job is to save Intel, it's a really important company. What what does that look like to you? What does Intel winning or thriving look like? >> Yeah, I just passed 14 months. A lot of thing happened in this 14 months. So a couple of thing. One is to change the culture and then uh clearly want to drive more accountability and also in term 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 layer of meeting. And so something that I change accountability listen to the customer and the customer delighted you know, someone like also 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. I'm being an engineer by training, I want to know what went wrong and what are the thing that I need to correct, listen to the customer and delight the customer, and then make sure that we have the right [00:04:01] product, simplify our product line, and really have the road map and the vision for the next 5-10 years. >> What what is your vision of where Intel should be in 10 years? >> Yeah, I think 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 starting to walk, and then finally you starting to run and 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. >> Mhm. >> And the balance sheet is really heavy. 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. Secondly, very happy that Jensen Huang, my old time friend, he also put 5 billion [00:05:01] in investing and support me. And I'm glad that at least do some good work. His 5 billion become 25 billion now and 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 uh focus on the products and I really simplify the product, listen to the customer, and then drive the next generation leadership products. And then uh in some ways it's very lucky. Uh right now the agenda AI and influence CPU become you know 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, "Oh, well, in term of reinforcement learning, in term of the speed of orchestrating all the agents, and turn out the CPU is [00:06:02] 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 couple of thing. 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 got to have low power IP set that you need to have. If 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 wafer to come, if the yield not good, they will be toast in term of revenue miss. So, with that, I think it's very important to really focus on the yield, the defect density, and the cycle time, and then make sure that you really able to meet and serve the customer in high quality and reliable. And so, those are the thing that I really focus on it. And [00:07:04] 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 thing that I quietly building uh 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 sometime, it's good to have a Rolodex 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 you've run a Cadence for, I think, 12 years before this, and so >> 13 years to be precise. >> 13 years. Sorry. Yeah, yeah, yeah. So, you did then >> more years as executive chairman, so 15 years. >> years. I signed up for 3 months. 3 months So, right now I'm being very careful. The moment you said, "I'll just do it for 3 months." It turned out to be 15 years. >> Yeah, well, it seems like you have a lot of longevity ahead of you here, as well. And so, um the other big initiative that that has been sort of talked about is Terafab and working with Elon Musk on that. Can you tell us a bit more about how that came together and your [00:08:04] involvement and how you're all are collaborating? >> Yeah, good. I mean, Elon Musk, I think we all agree is one of the best, if not the best, uh entrepreneur in this century. He and I, we share the same view that semiconductor infrastructure actually is not catch up with the AI growth. And uh in term of you need the capacity, you need to have the productivity, and you have the dry efficiency. And so, those are the thing that he and I, we share that there's um something missing. And then secondly, he's just delighted to work with him. And uh he's very I call it unconventional. And he basically question every step. And then why this traditional way of doing things? And in some way, it's 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 going to learn a lot together. And then I think clearly he had a vision that his robots and his car, you know, he need a lot of silicon. [00:09:05] >> Yeah, can you actually explain what Terafab is for people unfamiliar with it and so on? >> Terafab, he decide that 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 there's something that we both going to 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 very yeah yeah yeah. Think the polka? Yeah. >> I think I don't go that far. I mean 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 whether we can do that. >> Yeah, I mean it's very exciting to see how you're morphing the business here in the US in terms of incrementally building out the foundry business in terms of collaborating with things like Terafab. 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 [00:10:06] 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, um most of them I think are overstated right now. You know, most of the layoffs are actually just over hiring during 2020 COVID period COVID period. But the first things I see actually being cut are outsourced firms where you'd rather cut external head count 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, etc. 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 that's probably only the US in one or two other places. Um 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 uh Melanox Nvidia and Intel presence there? And should they try to do more in semiconductors? Should other Should the Philippines move back to more of a [00:11:07] manufacturing base? Like 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 uh I think the impact will be bigger than internet. And uh it's more profound also. So I think the AI in a in initially is able to help you to do things more efficiently. And then with a lot of agent helping you uh to do things that is the kind of mundane that you need to do, but now they can keep it to you faster. So, in some way I think kind of you can drive a lot of efficiency. Even like semiconductor design, how much you can drive the efficiency in term of timing. Uh, 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 couple of bottlenecks for the AI you know, demand and growth. One is of course everybody knows power constraint. Some country the power they just don't have that. They get impacted. And then secondly, a lot of people didn't realize the helium [00:12:09] impact can be also very significant for semiconductor. And then the thirdly, is everybody know right now memory is a bigger shortage. And everybody try to scramble for memory. And then even though you want to build a fab to capacity increase, it will take couple of years to do that. And same thing for CPU, GPU, and all this will be highly demanded. And I think that also pricing also go up because we have to pass the price the cost to the customer. 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 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 [00:13:09] simplistic argument against Tera Fab, against Intel Foundry being competitive is really a question of you know, there's there's other factors internal to the building, right? You described um, IP and velocity of just how you're doing business. Then there's 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? >> Right. So, I think, you know, the when I decided whether I should double down on foundry or should I get out of the foundry. >> Mhm. >> And I come to the >> of voices that are saying >> 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 finally decided this is very important for United States and also very important for the industry. [00:14:09] >> Mhm. >> And I 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 we 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 geographical. And so, I think, you know, the more and more people going to realize making in United States is critical. And then the most advanced process, like, for example, we have the you know, 14A is like 1.4 nanometer. And we're already starting to plan for 1 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 you make a mistake, then 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, [00:15:10] this is a become more and more going to be the bottleneck. >> Mhm. >> So, we felt that we, you know, we have a lot of respect for TSMC. We're a great partner. And then the more important, we both need to have more capacity to serve the customer. >> Mhm. >> And then so I think we decided by the bullet longer term, I think it's critical and then that's where I can create more value for the industry. >> People have been talking for a long time about eventually um hitting a point of resolution where you can't really uh miniaturize things further. Like the line width is gets too small to uh be able to uh keep going. Uh 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 then now we do going to production of 14A. I can see 10 and 7. And so I think that path I think we can get there, but going to 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 the sub-script [00:16:10] vendor, partner with equipment vendors so that make sure that we can really drive those yield and performance. >> Yeah. >> And then the other part also very become the bottleneck is packaging. >> Mhm. >> The advanced packaging. And so we all know about CoWoS by TSMC. Now we have really good one called EMIB-T that is a really next generation. I have to make sure that you become able to do in a production yield that meet the customer requirement. And now see more starting to run out of steam like you described. So right now I also look at some new materials of become going back to the material size or the chemical table. >> I see. >> So gallium nitride and silicon carbide and indium phosphide. So I invest in all three. >> Mhm. >> And then looking at some of these new material, how can we really drive that? And in the term of packaging, I starting to invest into glass. >> Mhm. >> Glass is a very good heat insulator. So we I even invest a venture cycle 3D GS. Then I realized that Intel we have [00:17:10] like 1,000 patent on the module. So how do you know, sub-script and the module put it together and then we just announce a big program with Indian government to manufacturing in in India plus in US in New Mexico. So I think this are advanced packaging very important. I also starting to look at artificial diamond. >> Mhm. >> And that's another very good you know insulator. So I also invest into you know diamond foundry. >> Mhm. >> And that's something is a next generation to look at. So new material, new sub straight material and new in the uh design methodology to drive it. So one thing good about being an engineers you always hitting the wall then you find way to either jump over the wall or you work around the wall and then the 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 EDA tool to design to manufacturing. [00:18:10] It's kind of nice to have that experience. Now I can help find a way to make a small contribution to the industry. >> Yeah, and that one is very exciting 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 Yeah, you need to find new materials or find other workarounds. >> Yes. >> Um and then the interesting question is and we've been talking about this for a long time. I remember 20 years ago people are 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 so we're not? >> That's a good question. In term of like Moore's Law is an uh double in the >> Yeah. >> 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 you have to give give way unless you find some new way of material new way of design. >> And then become material science I starting to hire more people in the [00:19:10] 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 I still investing in semiconductor, and actually most of the VC firm, some of them are very nice tier one venture firm, my good friend of mine. And I initially the partners meeting, the whole partners in the room, then after I talking about semiconductor, half make excuse >> Yeah. >> run out the room. >> Yeah. >> Then eventually the other half they said, "Valuable, do you have any software service?" >> Huh. >> So, then they both left with only two sympathetically listen to me. So, it's kind of the history have changed. And now semiconductor, if you look at it, Tencent is a 5.3 trillion market cap company, and then Broadcom and TSMC is 2 trillion market cap company, and Lisa Su, my good friend at AMD, is almost 800 billion, and I'm close to 600 billion. So, in some ways kind of semiconductor [00:20:10] become hot again, and it become 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 then now I starting to see a lot VC like to come investing in semi, so I'm very happy. >> Mhm. >> Given the enormous interest in investing in this area that used to be considered too hard, right? >> Yes. >> 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 going to list a a bunch of them. Um 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 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 [00:21:10] the customer >> Yes. >> to switch, right? I I think, you know, we've been involved in companies together where, you know, there's a design win and then there's still the question of like scaling order volume. Um uh 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 Uh uh what is your view on how a bunch of, you know, what makes it hard as an industry uh and then the the secular demand growth from a bunch of different areas, right? So, you have the um 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 I think there's a there's a lot of like YOLO action of like there's a [00:22:10] memory shortage, buy memory stocks um as well as, you know, just uh 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 uh you know, the venture capital startup is in my blood. And I I really enjoy it. And uh so, I think uh this is not try to brag about it. And so, there's some good exit. You know, I still have 159 IPO, 126 uh you know, M&A. And that's include semiconductor. Just break down the semiconductor, I invest over the years uh 200 and 38% is in US. So, what I usually look at semiconductor >> just to be clear, that's incredible. >> Thank you. Thank you. It's just enjoy building it. And but more important I will look at this first of all on the investment side. I always look at where is the bottleneck? What are you trying [00:23:10] to solve? And for example, I invest in company called Credo Semiconductor Australia Lab. Is this interconnect become the bottleneck? So I decide to back and also I 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 invest in almost every company is photonic related. And then the other part I looking at is you know, okay, what are the solution that need that 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 couple of new startup actually going to the EDA related area to drive performing improvement. I think it's a gold mine to do that. And then the other part you look at the new material. And we talk about you know, this you know, Indian phosphide. That's why I invest in Inphi and then Marvell bought [00:24:11] it. And then then you invest into some of the new material that gallium nitride and then silicon carbide and then some of the company starting to being acquired include one of them you know, doing power management and ADI just bought called Empower. And so again it's IBR. That's a very very good area in power management become bottleneck now. In term of converting from 40 V down to 1 V 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 what is the problem we try to solve? Is it real? Is customer crying for it? And I 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. >> Mhm. And usually I like the customer is hyper scale. They have the scale. If they like what you have, they're willing to pay millions of dollars next few years. And even giving some warrant [00:25:11] 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 what 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. A lot of talents. 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 suddenly they say, "Okay, there's a there's a warning. I have to go to underground." And then the in the name may not be good. Maybe we just use voice. In some way it's kind of fun. They kind of resilient entrepreneurship I really enjoy. So I think all in all I've got that there's a lot of opportunity. And especially in the AI. And then right now beside the gigantic AI, now you're looking at physical AI is next a next big frontier. And then you have to [00:26:12] really look at a full stack. That's why I'm still involved with a lot of this frontier model that we 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 good way. >> You mentioned the opportunity to make certain parts of the design and test of of chips faster, cheaper, more creative with AI. Given your cadence experience, like where do you what do you think is most fertile? Is there anything you think is already working? >> Yeah, I think you know, the 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 become super great CEO and then he really embracing the AI you know driving the agenda AI to drive more efficient but there's good part I think Synopsys Sachin also tried to do that and they have investment from you know Nvidia 2 billion I think helping him to [00:27:13] do a lot and he acquire 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 Siemens 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 to lock up you have 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 >> Yeah if you look at the different areas that you mentioned in terms of future either product development or impact of the AI on the semiconductor industry there's companies like periodic doing materials there's your point folks [00:28:14] working at the EDA side and design and other aspects and sort of throughout the chain there's manufacturing um 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 Sara 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 then I usually like to go in very early put a team together it's kind of fun to do that. I think you should you also do that. And then secondly, you try to find the right investor that can co-partner with you. Uh it's not just the whatever the brain and firm. I usually go for the individual. And then for the individual that really knowledgeable in this space, you can the most important to find a partner through difficult time and good time. A lot of time people are very enjoyable working with you is a good time. When the company got trouble, they [00:29:14] just walk away. I like to have partner that really work through. A lot of successful company, they have multiple time almost bankrupt, but eventually take off. So, I think it's more important to find a partner willing to do that. And then the other part is look at the 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. They can guide the company entrepreneur where not to go. And so those can be very helpful. So, I think all you know, I think it's just fun to do that. And then just what realize is the 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 you you trigger that and great next frontier to work on. >> Uh-huh. >> And then frankly speaking, I look back nine of the 10 company I invest [00:30:16] halfway they change their business plan because market have changed. >> Yeah. >> So, I like to have entrepreneur as team, but just one person. Secondly, open mind. They are willing to listen and listen to you know, getting coaching from us. >> Mhm. >> 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 give them enough feedback. They draw their own conclusion. That you exactly what you like and all different 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 are we 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. [00:31:16] And so, it can be big company, they really, you know, transform themselves to be looking at big platform like Jensen, I admire him. You know, he focus on CUDA, he focus on the liberal, I want to be a platform company and he did it. And so, in some way, you can do that. All startup company like Entropic, OpenAI, they find a way to do it in a bit more elegant They change the game and then they start up 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 it all together, can build some of the purpose built silicon for different workload. I think this way I'm going. >> 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 [00:32:16] 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 used to managing teams and I think that transfers directly over to managing agents in terms of understanding the complexity of what to set up 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, from materials now we should just use these three AI 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 that uh as I back to that crawl, walk, and run. >> Mhm. >> 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. And I've in order to build a full stack. And now I'm starting [00:33:17] to look at, you know, my average age of my team in the 40, late 40s, 50. >> Mhm. >> I need to bring in some new talent. And then so they're understanding the workload, understanding the frontier model open source. Uh that is important. So, if I know that my son become my teacher now. >> Mhm. >> So, every time he invite me to go to his house, we're playing the grandkids. I starting to tap on him on all the AI machine learning. He's more plug-in than me. So, I learn 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 transform it to become AI night and AI enable using some of our design and also across all the engine all the organization embracing AI. And then so they become less less depend on the spreadsheet and labor to do that. And you're going to combine the two [00:34:17] 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. >> Uh I think a lot of investors um you know, I I 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 um 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 $150 million before this thing gets to, you know, some critical mass." Um and and so you've lived that for a very long time and then you have the unique experience of um working with the government as a large stakeholder. How do you think uh this sort of industrial policy, it's led to huge successes like TSMC? >> Right. >> The most important company in the world. [00:35:17] Um 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? >> It's a good question. So, I think in a clearly in a full capital intensive uh business and uh infrastructure play, uh 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 become very capital intensive. >> Yes. >> And uh some of the venture firm willing to put 1 billion into some company >> Mhm. >> 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 go in very early and then because it's it's starting to do the series A is over 1 billion valuation. >> Mhm. >> And so you have to go in pre-money, uh pre-seed to go into that kind of a 20, 30 billion valuation is very rare right now. >> Yeah. >> So, you just have to do that, pick the right one. And then the other part is [00:36:17] able to find capital to scale. And that's why some of these mutual fund they also like to move into the pre-market, uh early stage to join when join me to investing. I delight them because they are very less sensitive or whether have 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 sovereign fund and also some very big capital you know, there's some big fund that doing that and they are really the fund they organize 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 sovereign fund I become very important and also as a public company, I also purposely want to focus on some of the investor they are more long-term [00:37:18] 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 do you going to you know, buy back your shares. Those are good question 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 thing. First of all, I think uh you know, as I back to this uh crawl, run and walk. Last four month 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 big 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 software architect so that we can leapfrog just like I look at Intel I want to be a multiple of startup [00:38:20] 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 in a genetic AI, the physical AI. There'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 uh we have to be humble looking at building the building block that 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 thing will take longer time. But I think by 2030, 2032, 31, 32, I think I was starting to surface up. People may not understand how big potential I can be in term of product, not on the PC client. That's [00:39:20] our bread and butter. And we move 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. >> Mhm. >> Now it's starting to have another different dimension. It's millions of agent. They need to access the compute. They 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. We can play on the agentic 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 and the edge and also in in term of agentic AI with agents and also physical AI, I think it's the jumbo. Everybody have a chance. So, I think that's part that I want to go for it. And so, I think hopefully uh the investor will know even though in 14 month, you know, we make six time return to the shareholder, The this is a [00:40:20] 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. You know, being a venture at heart, you want to look for 10x. You know, at Cadence, when I stepped out as a CEO, I think we make about close to 76 time. You know, starting from interim CEO, $2.42. And then when I retire as executive chairman, about 85 time 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." You know, and then and that 5 year, 10 years, if we can do 10x, I think it's a good return. Uh 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 um from this huge base already. Um there's an embedded belief in what you described about where the workload is. All right, where I think some would say like, "We're just going to be build bigger and bigger data [00:41:20] 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 it 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? >> Yeah, I think you know, that's a very good question. You know, right now there's a massive build-up in term of the AI, you know, the I think it's the right thing to do. I don't see that in anything to slow it down uh because the workload is increasing a lot. And then I think the question mark is how >> And we are supply constrained. >> supply constrained. Yeah. So, I think anything slow down is a supply constraint. But I think the other part is uh I always look at all this infrastructure build out. At the end you have to look at what is the solution, what is the application you want to drive? And I'm [00:42:20] 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 going to be winning. >> Mhm. >> And so some going to be winning big time and some going to 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 the Netflix and then some of them is kind of go sideways and disappeared or being acquired. And so I think to me is the same approach. Then the really focus on what application they try to serve and that application how big is that and whether 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 a industry go through that big growth and then then starting to consolidate, maybe eventually one or two become the real winner. So I think that's kind of a we've watched the movie [00:43:20] before, so it's not a surprise to me, but focus on application like Netflix is application, >> Mhm. >> 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 than than only by the data center. >> Okay. >> Exactly. >> Yeah. I mean I I will say as a I'm an investor in a number of companies that uh 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 um determines what you're able to do. >> Yes. >> Um and I I think that that's been kind of it was kind of forgotten for a little bit in the in the SaaS era. >> Mhm. Yes. Yes. So, I think I have more my investment thesis is find a problem that is really need to solve. And secondly, who are we the player that you can partner with? And then thirdly, look at the application. [00:44:20] How big is the application? Is that sustainable? And if it's really big, you believe in it, double, triple down. >> Yeah. But you're including betting on applications with that have not yet been broadly deployed. >> Okay. It's amazing. Well, thank you so much for joining us today. It was a pleasure. >> Thank you so much. >> Thanks, Lip-Bu. >> Thank you. >> Find us on Twitter at No Priors Pod. Subscribe to our YouTube channel if you want to see our faces. 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