Intel Corporation (INTC) Earnings Call Transcript & Summary

You have a very unique record in my life. Do you know what that is? The speed at which I have developed a friendship with you, I don't think I've developed with anyone else. And it's not a function of me. I think it's a function of just how good you are at doing the kind amount of things that you do on a regular basis, but, thank you for coming here.

Thank you for inviting.

Tell us a little bit about Intel is a national Treasurer. Intel has gone through some tough times. You are bringing it back again to life, but there's so much that needs to get done. Walk us through the current state of Intel. Where do you think it is? Where do you think it should go? How should people think about it?

Yes. I think, first of all, I joined the Board for 2 years and learned somethings going on, a lot of good friend of mine from Intel. And it took me a while to decide to take this role. And I say, no, that's not easy. A lot of my friend told me that don't do it. And we have a great reputation in the venture investment that you love it and to take on this one. But finally, I decided this is an iconic company. It's very important for the industry and also for United States. So I finally convinced my wife, let me do it one more. And after cadence and he supported me to do it one more time. And just to update, I think I just passed 10 months coming to 11 months. And I kind of call it matching off the map. So something that some of the surprises, I don't even know you have to kind of reacting at a real-time basis and learn from it. So in some way, I think it's good to have. And then just update. And we have a very complex company. You have a foundry that's strategically very important. And then the other part is the product. And then -- so clearly, you need to balance the two. And then the other part is.

Do you believe your foundry business becomes a general purpose foundry that's outside of just your products?

Yes. And so that's the intent. And we have the 18A. And when I took over, the yield is quite poor. And so I really get all my friends to help from PDF solution to KLA in the equipment to make sure that we have that 7% to 8% yield improvement per month.

8% of yield improvement per month.

That's right. And that will be the best practice. And it took me a while. Finally, now I seeing 7% or 8% yield per month. So in a way, it's very helpful that you open up the kimono and let people come and help you. And then -- so I think one is 18A. We just announced the Penta Lake, and then I can really count on my fab to produce that. And then interesting enough, a couple of customers are knocking on my door now and say, hey, it seems like your 18A is doing well. We want to be part of that. So I think we are delighted to see the customer want to see that, but we are laser-focused on the 14A. And that will be -- it's very important. It's 1.4, and this is the most advanced. And we're going to be in the risk production 2028 and then we'll be in volume production '29. And like any foundry, I learned a lot, and you need to have not only the yield improvement, you need to have the variation, so they're more predictable. And you also need to have the final product that what is the yield look like and the spin and all the detail. And second part, you need to have all the IP available. If you want to have mobile customer, you got to have all the low-power IP to have. Otherwise, you can't serve the customer. So that's something that is missing in the past. So I really put something in place and so that we can have both and then serving the customer. Good news is a couple of customers are very excited. 0.5 PDK this month, we will have that and the customer can use a test chip to work on us. And so I think good news is a couple of customers are engaging heavily, and we're looking forward to serve them. Hopefully, second half of this year, I will see the volume commitment from the customer, which product they want to have, and I can serve them.

On second half, you'll see the volume commitments on the foundry or on your core products?

On the customer. So in the way, they need to let me know what products and what volume they need. Then I can -- and one thing to -- people will see because, first of all, I'm not going to announce any customer. This is confidentiality. We need to support the customer. And what we're going to do is when you see me starting to put money into subscript is a very important material. And then secondly, some of the CapEx equipment I need to have and scaling it. I mean that I have real customer I've committed to it. That's kind of discipline I have.

So on the fab side, to get to mass scale, what does mass scale look like for you? And what's the time frame that you feel like mass scale would happen where you could be a formidable fab for third-party chips?

Yes. So it's very challenging to operate the 2 because one is on the product. You have to drive innovation, drive the product road map. The other part is really a service business. Culture has to change. And in some way, I kind of tell my team, this is a business of grinding. It's not like you have good innovation, good technology, you people will come. You have to grind until something that you prove the yield, they can count on you to make the production and then their whole revenue, profit depend on it. There's a lot of trust and responsibility, and we have to earn it. So I think those are the things that scaling is important. And that's why I always ask customer, give me the biggest product that you have, the most important product. give me 5%, 10%, 20%, 50%, let me earn it and earn your trust. And then many of them, I work with them when I was running Cadence, so they trust me. So somewhere that I think back to your point, trust is very important for AI. So I think something that even more important in foundry is the customer trust.

Now if you think about the constraints that are there right now, do you think that the energy constraint is with power, cooling, all of that is more severe or right now is manufacturing capacity, which one limits growth first?

I think in terms of the AI, the biggest challenge, I think, for a lot of my customer is memory. Memory, actually, there's no relief as far as I know, when I talk to only 3 key players, 2 of them I talked to very frequently. And then they told me that Lip-Bu, there's no relief until 2028.

Why is that?

Because I think this whole AI is suck up a lot of memory. Our mutual friend, Jensen tonight, you talk to him. And clearly, he needs a lot of memory for his login and the next-generation product. And so I think it's very important to have that memory. If anything going to slow down going to be the memory. So I think is one. Secondly, I think it is clearly from the compute side, I was very happy to hear that customers are all crying for more products, and I didn't prepare the production enough to meet their requirement. And so I think people starting to find out that in application, CPU actually is more useful in terms of performance for all the compute requirement. And in fact, a friend of mine, he mentioned that Moore's Law double used to be 3 to 4 years, and now it's like 3 or 4 months. So the increase of compute is increasing so much. And right now, my biggest challenge is focus on our production, our supply chain, make sure we can meet the requirement. Almost every CEO, they call me, Lip-Bu, can I have more? I'm your friend. I'm your customer, the most important customer, I want to have more of that. So I think somehow it's kind of encouraging for me to see that compute has become very important. And then the other part, very important to me is beside memory, beside the compute and then the other part is the thermal we just talked about, the cooling technology. So in terms of some of the high-performance processor, either GPU or CPU, sometimes you have to guide the gigahertz down because your thermal issue and power management. So those are the ones that you want to find new way of cooling in terms of liquid cooling, air cooling is not cutting it now. So liquid cooling, micro cooling, emergent cooling. So I think those become very important. The other part that you also mentioned, I think something that Cisco has is really good is that interconnect is getting become very critical. It used to be more in the copper and like Kratos Semiconductor and Astera lab by investing, but now moving to optical... And so optical become very critical. And so that's something that is a new wave because the speed and the density become very important. So that's another issue. The other part of the constraint is the software. And then so if you really want to address some of this like the Moore's Law, you need to really look at the whole full stack. So not just the silicon and you need the cooling and then you need to have interconnect and then the other part is the software. The open source, I'm very strong belief in it. And then, of course, the crude compatibility is very important. And even more important, right now, it's a cluster of GPU or CPU and then it becomes the clustered manager, the software. And right now, sometimes if we have a problem, you don't even know where to look for it. And now there's a lot of new start-up coming to me, they said, Li-Bu, that will be an area that we want to work on so that we know exactly how to solve some of the clustered issue that you're going to face. Kubernetes is great, but you cannot find the real issue there. So I think those are kind of interesting being a venture capitalist and running CEO of Intel, it gives me that kind of perspective of what are the new things coming and quantum computing is another big area coming up is around the corner. And so something that is interesting to see after AI, we talk about agentic AI, the next big wave is the physical. The next thing is going to be quantum. So I think that's kind of exciting.

And so you talked about open source and talk to us a little bit about like your perspective on open source in the United States? How important is it? What needs to happen?

Yes, very good questions. I'm very passionate about the education. And I'm involved with MIT, CMU and Berkeley and others. The key part is one thing that I worry a lot is the fundamental research we're starting to not continue. A lot of university, the best professor being recruited out to Asia to Europe. And so I think the fundamental research, some of the public companies like Cisco and ourselves, we have some short-term midterm requirement. You cannot invest into long-term 10 years, 20 years from now. And so that part, to me, is an outcry on foundation research. The other part is the open source. I'm a big fan of open source. And frankly speaking, a couple of people that good -- very knowledgeable people that told me, Lip-Bu, we are behind China now. And so that's something that we have to pay attention. I think DeepSeek is just a wake-up call.

But don't you think like to some degree, some of the models that are emerging in China are just pure distillations or the models that are here? And so at some point in time, if all you're doing is distilling the models, then the moment -- they can't really get that much further ahead. Or you don't think that's the case. They'll actually figure out a way to start creating original?

Yes, very good question. I thought that initially, I thought that they will be falling behind because they don't have the access to the most advanced GPU from NVIDIA, most advanced processor from many different players. But you will be surprised. And recently, I was just try to recruit some of the top talent in CPU architect. And I found out that Huawei have 100 CPU architect, top notch. I was shocked. And so when I talk to them, why are you going there? And they said, even though we don't have access to the best tool like EDA tool from Cadence and Synopsys, but we have the pan way to do it, and we can do it. And I said what about ASML equipment that you guys don't have. But I said well, we are quietly building on it. And so to me, is they are just shortly behind us. And then if you're not careful, they just -- they ahead of us.

And what they've done is they've spent the calories on infrastructure optimization because they don't have the right chipset?

Correct.

And so like if they are at 7-nanometer and we are 2-nanometer, what they're offsetting that with -- and they have unlimited power and they've got engineering capacity that actually creates the caloric redirection towards making sure that you you drive a certain level of infrastructure optimization.

That's correct. I think the one thing that we are behind is -- I think all the AI cloud, you need a lot of power, right? And then if you look at U.S., the regulatory approval, and it just takes longer to get that. In China, if they decided to have it, they quickly can get all the approval and get it done. So that's something that we have to pay attention. We may...

You're doing this within -- you're investing in companies. What -- do you see open source development changing in the U.S. materially? Or do you feel like it continues on the foundation model side where it's going to be largely closed source and not open rate's open source models?

Good question. Some companies, they call it open source. And when they become successful, they become closed source. And then so they block it out. So I think we have to continue encouraging open source. I think that's the best way of not repeating everybody's effort and so that we can really drive more successful improvement and quicker.

You almost need a business model where something else is able to go out and fund that, because if you go just with open source, the training costs are so high that the economics don't work out, whereas in China, it's different because the government subsidizes a lot of that.

That's correct.

How do we handle that? What's the game theory on our side? What do we do?

I think a couple of my friends are putting a lot of effort in terms of rebuilding that open source community and even funding some of this -- the best AI researcher to really do that, they even from a new institute rather than just university to fund some of this program. And I think I really encourage a jump on it because this is something that badly needed. Same thing for semiconductor, I used to be the only guy venture investment and until this AI take off, everybody knocking on my door what is the next big deal that you are doing. And until this AI take off, everybody knocking on my door. What is the next big deal that you are doing. And so I think overall, and I'm glad to see all my brother and sister from the VC side starting to put money to VC to co-invest with me. I think in some way, I think we have to continue doing that. And then the other part is on the foundry side, it's very important to have a U.S. manufacturing foundry. That's why I decided to come in and double triple down. It's a long-term business, but we just have to really do that because the industry need that and the U.S. need that. So I think overall, not just the process, also the advanced packaging and that becomes -- really become the bottleneck and something that we have to really continue to drive system wafer kind of packaging arrangement. And that's why we are investing in some of that and then some of the new technology to drive the packaging so that we can really help enable the AI driver and then to really take off.

Does Intel build GPUs in the future?

Yes. And I just hired the Chief GPU architect. And then so he's very good. I'm very delighted he joined me. And it takes some persuasions. And then I told him that not just CPU, GPU is also very important, different or different application workloads. And so you have to really optimize. So I'm not hung up with just Xeon 86 and also embrace RISC-V and you got to be more flexible. And the key thing is more that it's kind of more the software layer that you have to drive down from call it the software 2.0. It's define the software, you dry the hardware.

So Intel is going to build CPUs, they're going to build GPUs. They're going to have their own foundry to build those CPUs and GPUs, and you're going to have a foundry that's going to be made at scale available to other manufacturers, and you will make sure that you partner with the other GPU providers.

That's right. And some new material like the glass is a very good insulator. So we have doubled down on glass. And then the other part is artificial the diamond. And that's another good glass. So I think you have to go through the different chemical table and find out what are the new material like gallium nitride is very good for RF and switch area. And so that is interesting. So I think we have to look at different new material we have to look at CMOS is a little bit run out of steam. So you need to look at some of the new material. And that's why it's very important for me is I have continued to have that curiosity. So starting to look at some of these new things, things are a little bit short term, midterm and longer term and how you're going to make the impact to the industry.

So Lip-Bu, you've got enterprise audiences over here. You've got CIOs, you've got Chief Information Security officers, there's 10 million people that are probably watching -- going to be watching this. What advice would you have for people on how they should be thinking about AI and how they should be thinking about scaled infrastructure build out. What would you say to them?

Yes, it's a very good question. So I think we all get excited and also a lot of pressure to adopt AI and then to the enterprise. So I think it's very important to think about what is the problem you try to solve. What is the outcome you want to look for. And then -- and also some of them that just like Intel, we have a very legacy IT infrastructure. I just recruited the best CIO that I can find and I brought her on board. And I kind of told her that, look at -- I think it's a good time to look at the foundation, what are the changes we need to make. You don't just put on top of the old legacy, it's not going to work. And then you have to really undo that and then embrace some of the new AI tool pro function by function to really drive the augmentations. But more important is what are the process that you cannot drive the metric to success. And then frankly speaking, a friend of mine, we're just talking actually is MIT professor on the MIT CEO Advisory Board. And one just mentioned about -- if you look at all the AI, the study that he study is that basically the productivity of the global economy is growing very small percentage. So we still have to adopt more broadly so that we can really see the productivity go up with agentic AI with agent and enroll... So we still have to adopt more broadly so that we can really see the productivity go up with agent AI with agentic and then roll actually

Actually the lowest it's been in compared to back in the 1800s it was very eloquent...

I was shocked to see the productivity that he showed me the curve. I said, wow, I thought that would be much higher. So I think that's something that we have to think about what is the end outcome that you want to have. And then go back to foundation, how do we drive that -- and then meanwhile, give ourselves enough accountability that able to really drive the productivity of the enterprise that you can measure, you can present to your Board, hey, by doing this, I invest this new technology, actually improve my productivity and improve our revenue growth.

Lip-Bu, Intel is a national treasurer, so are you. Thank you for being here.

Thank you for inviting.