Applied Materials, Inc. (AMAT) Earnings Call Transcript & Summary

Well, good morning, everybody. I'm Mike Sullivan. I'm the Head of Investor Relations at Applied Materials. And once again, I have the honor of being the first to welcome you to SEMICON West. It's my pleasure. We really thank you all for being here. Applied has a very long tradition of hosting a technology breakfast at SEMICON. We've been doing it for years, and we've been looking forward to seeing you pretty much all year and spending time with you. A big focus of this year's SEMICON, of course, is really understanding what is the state of the AI build-out and what does it mean for companies all across the entire technology ecosystem. And the figure of merit that everybody is focused on is tokens per second per watt. And when you look at today's presentations, what you'll see is that ultimately, AI -- every AI system and every AI chip depends on 2 ingredients, made of 2 key ingredients, and those are transistors and wiring. And what you'll see today is that over 60% of the transistors and wiring, 60% of those materials are put there by Applied Materials. And what that means is we have an enormous opportunity and responsibility as a company to make them even faster and much more energy efficient. We know the entire AI ecosystem is waiting for breakthroughs and inventing those and accelerating those. It's a challenge that we love. It's a challenge we accept. And you saw a video a second ago. Yesterday, many of us were in Sunnyvale, California for the unveiling of the Epic Center. All of the world's top chip makers were there, Intel, TSMC, Micron, Kioxia was there, Hynix, Samsung, all there talking about how they're going to be working with us to develop these innovations and accelerate them and bring them to market together. So we're extremely excited about that. And so what I wanted to do just now quickly is give you today's agenda. Traditionally, what we do at SEMICON West is we focus on our core semiconductor products group, and that's Prabu, Raja and his team. And of course, they're here, and they'll be speaking. But this year, we're doing more. So we've invited Gary Dickinson to give you an update on the state of the industry and on our strategy. In addition, we've asked Keith Wells to join us this year for the first time, and he's going to give you insights into our fast-growing process control business. And we've asked Tim Dean to come and explain how we're accelerating the growth of our services business. Usually, at SEMICON West because we're in quiet period, our CFO is kept hidden in Santa Clara. But this year, we've invited Bryce Hill to talk about our financial progress as a company and our plans and targets for the future. So we're going to be giving you a lot of new data today. Then all of our presenters, they're going to take the stage to answer your questions. And I've got 2 final quick housekeeping items for you. Number one is, as I mentioned, we are in our quiet period. So if you have near-term questions, we're going to answer those for you by next month on our earnings call. And finally, I've already had people saying, where is the presentations, where are the slides? I can't find them on your website. Please know that you don't need to write anything down. We have a tremendous amount of new information. A lot of the forecast that we had in the past have changed. Many of them have increased. So there's a lot of new data. There are new financial targets. All of those are going to be available on our website as Brice concludes his presentation, that's going to be at about 9:45 a.m. So please relax, -- you don't need to write anything down. I promise you it will be there at 9:45. And that's about it for me right now. I'll come back and help you with the Q&A. But in the meantime, thank you again. It's so great to have you with us. And I'd now like to welcome to the stage, Gary Dickerson.

Well, thanks, Mike, and thanks for all of you joining us here today. This is an incredibly exciting time for Applied Materials. So many of you probably remember, 9 years ago, -- this thing is -- there we go. 9 years ago, we had our AI design forum and many of the top innovators in the data center were at that event. And over the last decade, Applied, we anticipated that AI would be the major driver of the industry, and we've been creating enabling capabilities to position us to grow quickly going forward. And that's what you're going to hear today. So AI is driving the global economy. It's driving the semiconductor industry. The fastest-growing wafer fab equipment segments in the industry, driven by AI, our leading-edge foundry logic, DRAM and advanced packaging. And in all of those areas, Applied is #1 and positioned to outperform. And you'll see that today in the subsequent sessions. And one thing that I've been in the industry for a long time as an innovator, I'm engineer. I love innovating with all of our partners. The -- always there's a focus on technology innovation and performance innovation. And especially for AI, innovating in chips and packages for tokens per second per watt is a race for every one of our customers. They're racing for every new inflection to be first to market with design wins. And so we have these incredibly deep relationships. I'll talk about that today with all of these leading companies. But the thing that I would say has changed more than I've seen any time in my career this year is the focus on capacity innovation, yield and output innovation. We're in an environment where demand is much bigger than supply. The chips have never been more valuable. So yield innovation, more good chips per wafer, higher-yielding packages is incredibly important, and that creates great opportunities for Applied Materials. We have been creating advantages that position Applied Materials with the most enabling technologies, and I will describe that in materials innovation, Mike talked about over 60% of the materials in the chip are coming from Applied Materials. Integration innovation is incredibly important. Mike talked about EPYC, and we had all of the key R&D leaders through the technology stack on Sunday, yesterday morning, it was really amazing. We had hyperscalers. We had the top companies designing next-generation AI servers. We had all of the top chip manufacturing companies, design companies, materials companies. And one of the things that for me was very notable, every single one of -- and these are the top R&D leaders in the entire technology stack that were there, which is very rare, if ever, to have all of those people in one room. And what they said is it's not good enough to innovate on just components. you have to innovate from a system level. And we talk about high-velocity co-innovation coming together because the workloads are changing very, very quickly and the need for higher velocity innovation has never been greater than today. So this integration innovation capability that we built at Applied Materials, certainly, it's co-optimization through that whole tech stack, co-optimizing with all of the technologies. Mike talked about how Applied is the leader in transistors, wiring, advanced packaging, again, co-optimizing across that whole flow is incredibly important. Applied has leading innovation -- integration innovation teams working 10 years out in the future, co-creating those future chip and packaging architectures from a system standpoint. Again, that's never been more important than today. And as I mentioned, good chips per wafer, yield in advanced packaging is incredibly important. And Applied has leadership in the highest resolution materials analysis. We're 2x bigger than our nearest competitor in e-beam, which Keith Wells will talk about later today, is incredibly enabling to accelerate innovation for transistors and wiring and high-speed memory and advanced packaging. So these capabilities are tremendous. And then Tim Dean, who leads our services business, will talk about how we've created advanced service technologies with AI that will accelerate more good chips per wafer and more wafers out. And then we'll also talk about Bryce later will talk about value creation. Applied being positioned to grow very quickly in wafer fab equipment, over 20% increase in the coming years in revenue per tool in our services as we're accelerating R&D, enabling more good chips per wafer, enabling higher wafer output. Again, just for me, I'm meeting a lot of these top CEOs every month, top R&D leaders constantly. I probably will see all the top CEOs in the next 2 weeks. And that's because, again, they're all racing to drive performance leadership at these inflections. And I have never seen the pull stronger than today in yield innovation. The top priority for them is good chips per wafer and more wafers, especially again when the chips are so valuable. So you'll also hear about how we're growing our gross margins and operating margins through the day today. So I've been again in the industry for a long time. I've always thought what we do is incredibly cool. I believe that we deliver miracles all the time in the semiconductor industry, but there was a period of time where there wasn't growth in wafer fab equipment. There was a period of time when you have the transition from 200-millimeter to 300-millimeter, then Moore's Law started slowing down and more of the growth was driven by power performance area cost and time. You see a 14% compound annual growth rate. We're not going to give a specific WFE forecast today. But what I would say is that I have tremendous confidence computing demand is going to grow at a tremendous rate. The compound annual growth rate is going to be very strong. So very confident in that. And you'll hear today also how Applied is using AI across everything that we do. The pacing factors are fab space, certainly supply chain components, energy, financing, some of those factors will impact the rate of growth. Value pricing can increase the rate of WFE growth. But again, I have very high confidence as we're working across this whole ecosystem and technology stack, and I see how we're using AI inside Applied Materials, it is fundamental to our competitiveness, and I'll describe that also, and Brice will talk about this later today. You'll also hear from our Chief AI Officer, who started his PhD at 16, brilliant guy. We formed an AI leadership team 3 years ago, very clear ROI inside Applied, and we'll describe that. Okay. Leading edge foundry logic and DRAM compute memory. This shows the percent wafer starts for mobile, PCs and data centers. And what you can see in just a few years, there has been a tremendous inflection. A few years ago in leading-edge foundry logic, mobile was the major driver of wafer starts. Now data center has crossed over and data center is growing at a tremendous rate going forward into the future. In DRAM, you see the same thing, data center, high-performance computer really driving wafer fab equipment starts. So the great thing for Applied Materials is that in both of these segments, we are the leader. We are enabling the key inflections for performance and power and the rates for our customers for their design wins. And I think as all of you know, the chips in the data center are huge. They're at the reticle field limits. So that drives tremendous growth in wafer fab equipment, and this is going to continue to accelerate in the coming years. New AI applications driving growth and diversification. And again, yesterday, we had key R&D leaders that are responsible for innovating with the next-generation AI servers. We had hyperscalers. We had really all of the companies that are leading the AI technology stack at this event yesterday morning. It was really amazing. And what they talked about was that workloads are changing very, very, very quickly. There is a tremendous need for improvements in token per second per watt or tokens per jewel, one of the R&D leaders talked about. And what we've seen from a standpoint of Applied Materials in calendar '26 is a significant growth in Agentic AI compute demand. And so we've increased our wafer fab equipment forecast going forward because of this increasing demand. And then on top of that, in the future, you have physical AI. And on the right side of this chart, what you see is the mix from a silicon area perspective. So you're going from more GPU-intensive architectures to in Agentic, a more CPU-intensive architecture. Now for Applied Materials, we're very agnostic about this mix. What I will show is that more of these devices are moving to the leading edge faster, and that's where Applied Materials has higher market share, and it positions us well for significant growth going forward. Okay. This is an AI factory pod. How many people here know what a pod is? Okay, not too many people. So a pod is a modular building block for an AI factory. And so what you see here, this contains all of the components that go into a pod. And a Genty AI consumes about 2 to 4x more wafers than a generative AI pod. And then this next chart Basically, you'll see that the number of wafers is increasing, 2x and 4x, depending on the configuration. This is really Ruben and Ruben Ultra. And then you look at the device mix per pod, 85% of the content of the Agentic AI factory is leading-edge foundry logic, DRAM and advanced packaging with -- from a standpoint of wafer starts. And so Applied Materials, what we've talked about earlier this year is about 80% of the incremental growth in WFE this year is in these 3 segments. And we see this growth continuing forward. So our position inside these 3 segments is very strong. We have, as I mentioned earlier, these deep co-innovation relationships with all of these leading customers. And we -- again, we have high clarity because we're co-creating these architectures with these leading companies. When I'm meeting next week, I'll be with CEOs and R&D leaders, when we're meeting, we're focused on the top 5 to 10 enabling technologies for next-generation technology nodes. They're laser-focused on that. And Applied Materials has the majority of those enabling technologies. Again, we have integration innovators that are working in trusted, deep partnerships with all of these leading customers, enabling the higher velocity for these inflections. And the focus on improving the tokens per second per watt in the data center is driving more chips to the leading edge. That's what you see here, how long it takes for different generations of technology. And so what you see here, server CPU, GPU, networking, ASIC, all of those chips are moving faster to the leading edge where Applied Materials has a very strong position. So I talked about this earlier. The race for AI computing leadership is the most important race in the global economy in the semiconductor industry. And as I mentioned, there's this technology race with chips and multichip connectivity is incredibly important, how you connect all of these computing components together. And Applied, as I mentioned, we have the deepest, the strongest relationship in co-creating innovation in these areas. And as I talked about earlier, never in my career have I seen a stronger pull from customers for more good chips per wafer and more wafers faster. And that's what's on the right side of this chart. And again, Applied Materials, -- over many years, we've been building leadership capabilities in materials innovation, uniquely integration innovation with our connected and co-optimized technologies, our integration innovators and our innovation platforms. That's exactly what EPYC is all about. I'll talk about that in a minute. And then yield innovation, I'll talk more about that. Most critical technologies for AI computing road map are shown here. Again, there is a race with all of these companies producing these technologies to be first to market with design wins. It is a very exciting race. We love co-innovating with all of these partners. Applied is the leader across all of these different areas. So this shows leading edge foundry logic from 5-nanometer to 1.4 nanometer. You see mobile, high-performance computing and data center. And remember that data center is driving more and more wafer starts going forward -- and here, what you see is that wafer fab equipment per start is increasing node over node. You see Applied's addressable market growing to more than 50% through this time period, and you see our share of served market growing when Peru, which is 1 of the most brilliant and trusted innovators in the industry is up here next, he'll tell you how we are enabling these inflections, how Applied has built over many years, capabilities that are unique to enable these technology inflections. And then if we look at advanced DRAM, same thing, what WFE dollars per wafer start served market growing to more than 60% and and applied gaining share in served market node over node. And this is maybe for the people that aren't deep into the technology, you have these different technology nodes. 6F squared is a certain technology for DRAM, compute memory, then you're going to 6 square CMOS bonded to the array, 4 square, 3D DRAM, all of these things, things -- the main thing, as you move to these future technologies, especially as you're going more vertical Applied is in a tremendous position -- those of you that have been around for a while know that we gained around 10 points of overall DRAM share over a number of years. And we are growing quickly in this segment and with these 3 companies that are all Epic partners, we have incredibly deep co-innovation relationships. Again, over 60% of the served market in leading-edge foundry logic and in DRAM Applied has the most enabling materials innovation technologies. We have unique integration innovators. And for our customers, again, it is a race for who will be first to market with the best technology for design wins. So great opportunity for Applied going forward. This shows the WFE market segments, percent of total wafer fab equipment, the technologies inside those market segments from Applied Materials, and then our positions. So if you look at, again, enabling these major inflections enabling the race for better chips, better packages and deposition applied is about 2.5x larger than our nearest competitor. In material modification, and Prabu will talk about this. Next, we are greater than 2x larger than our nearest competitor. In e-beam, which is 200x higher resolution than optical, you can't fix what you can't see. Keith will show how that business is growing over 50% this calendar year. And that technology is incredibly important to accelerate innovation and transistors and wiring and packaging, again, 2x approximately larger than our nearest competitor in e-beam. And we're a leader in conductor etch in foundry, logic and DRAM. So this enabling portfolio is why customers are working so closely with Applied Materials to co-innovate. And I can tell you, again, when I'm with these R&D leaders, when I'm with the CEOs, it is so much fun. Again, I really believe we create miracles all the time. We make them nearly impossible, possible. And so having this technology portfolio that we have created over a number of years, positions Applied to be incredibly strategic for our customers and for fast growth going forward. So I've talked about the materials innovation. And the ability with these technologies also to connect everything together, that's important. I've talked about integration innovation with co-optimization of these technologies. And you'll see integrated platforms where you're taking multiple technologies and connecting them together under vacuum for better electrical performance, applied as unique in those capabilities. We're unique and the integration innovation teams that we have at Applied Materials. We built these teams over 9 years. They're world-class and engaging with all of our customers. And then the innovation platforms, I'll talk about Epic next, how that fits into this race and integration capability we have -- as I mentioned, we have the highest resolution, a material analysis capability with e-beam, and we have AIx. AIx is actionable insight acceleration services that are accelerating good ships per wafer and wafer output. I'll talk about that also in just a minute here. So eBeam is a business for Applied Materials, high resolution, about 20x higher resolution than optical. You can see into advanced structures in ways you can't see any other way. Keith will share with you today many applications that are accelerating R&D, innovation with our customers and accelerating Applied's R&D velocity across our entire portfolio. So this is an incredibly important technology, strong pull from customers growing more than 50% this year and will continue to grow at a very high rate going forward. In eBeam, again, Keith in his metrology inspection business, later today, he'll talk about 3 growth engines. Optical is growing over 50% this year. We have a lot of a pipeline of enabling technologies that we're bringing to market that business will grow fast next year and also going forward. eBeam, growing over 50% this year, also growing significantly. And this acceleration across the entire portfolio with this unique technology is incredibly important for Applied Materials. And again, all of this data, AI, you need actionable insight and actionable data -- this gives you massive actionable data that you can feed into AI-enabled servers, that's what our AIX platform is to accelerate yield, good chips per wafer. Wafer output and accelerate R&D. The service business I have to say I love Tim, I love all of our team. Tim is fantastic. And he, again, is so deeply connected with our customers. All of them are in a race every chip is worth a tremendous amount of money. So more good chips per wafer, more wafers faster is really what we're driving in our service business. And we created this actionable insight acceleration server platform many years ago, we've been innovating with advanced sensors in our platforms and today, we have over 37,000 chambers connected inside customer fabs with AIx. The majority of those are remotely connected. And what we're seein and this is also where we're deploying these advanced service technologies, AI with predictive diagnostics -- we can match the chambers faster. Tim will talk about that later. That's really critical for good chips per wafer. Again, there's many innovations that we're driving here. This business growing more than 20% this year in the mid-teens going forward, and again, just tremendous, tremendous value for our customers. EPIC, we have all of the top leading companies that are in the race for AI compute innovation as part of Epic. And what we do inside of EPIC is we are working with customers through the technology stack, partners through the technology stack many nodes out in the future, N+1, N+2, N+3, Ns 4 and co-creating these architectures. I've already shown how Applied is the leader in material innovation, integration innovation, yield innovation. So our customers, they're bringing their top innovators to co-locate with Applied Materials innovators and for them, it's early access to these innovations. We have an incredible pipeline of innovations. Our teams are amazing in delivering innovations that are critical for these fast-growing segments that are enabling AI improvements. And so our customers want early access to those innovations and then integrate that into their devices. So having those innovators co-located is a really big deal. Inside of EPIC also, what we're doing is we're running loops. We have over 100 test vehicles. We have customer reticles, and we can innovate in the transistor very fast. We can innovate in wiring very fast, in modules in high-speed memory or in packaging very fast. So again, for customers, what's really important is being first to market with leading next-generation technology. And then after that performance innovation in the chip and the package, they want to transfer that technology first time right into their R&D facilities and then ramp yield, good ships for wafer, packaging yield as fast as possible. It is a race for every 1 of these companies. For Applied Materials, we're designed in earlier, with our products, systems and services. We also have incredible visibility to what matters, where to invest, where not to invest, because we're co-creating 10 years out into the future with this platform and with the relationships that we have with customers. And for the customers and for Applied Materials, we're driving R&D productivity and efficiency. Okay, let's hear from customers Micron engineers and researchers will work side-by-side to the Applied Materials teams to co-innovate the manufacturing technologies needed to scale next-generation memory economically. By aligning our road maps and bringing our teams together, we can move faster from research to commercialization. This center is a milestone in on equipment R&D, bringing together global team makers, time companies and world-leading resorts to design the future of semiconductor AI is driving the need for breakthroughs at both the device and package level from faster transistors and better interconnects to advanced packaging. Meeting this challenge requires trusted partners working closely together. And EPIC gives our teams the opportunity to work side by side on new materials and process technologies, the brightest mines from AMED and SKs, we tackled the toughest highest value inflections in the AI memory road map grows HBM, DRAM and that. combining this memory expertise with AMED equipment and manufacturing leadership is how we will jointly navigate the incredible complexity of AI remorse. The next frontier of AI will be defined by how seamlessly we integrate compute, memory and connectivity into high-performance systems. By pairing applied materials, engineering and manufacturing capabilities, with Broadcom system and custom silicon design, we are bridging the gap between hardware requirements and packaging innovations. This will accelerate the path from concept to production for next-gen AI systems.

Okay. Again, all of our partners are incredibly excited about Epic and our ability to co-innovate faster together. So let me just spend 1 slide on materials innovation in adjacent markets. We recently updated -- I believe, in our last earnings call that this business is around these businesses are around $400 million per quarter in terms of run rate, and I wouldn't model anything near term beyond that. But let me describe these 2 businesses that are in this other category. Our display business is a little over 20% operating profit today. We've announced recently this MAX OLED technology. And what's important here is this technology enables OLED to go to larger display sizes. IT, TV, automotive, and eliminates the fine metal mask, which has been the major technology constraint. We're working with leading display companies to implement this technology Again, the key focus here is the same thing that I talked about earlier is bringing those yields up to the tipping point for this technology to move into high-volume manufacturing -- so we're making progress. But again, I wouldn't model anything different today. Our SAM goes up significantly as OLED adoption increases. And 1 thing also about our display business. We are bringing our leadership and display deposition and eBeam into semiconductor panel packaging. And that will be worth a significant amount of money, not in the display business in our semiconductor business going forward. And then the other area, just very briefly, very early on, again, I wouldn't model anything at this point. Applied has announced recently this since brand. We've created waveguide technology that has the leading optical performance at the lowest cost I can tell you there's a tremendous amount of innovation in this technology for AI glasses. And around 90% of the flow to build these waveguides our applied custom innovations. Here, the strategy is to sell waveguides and eye pieces. But again, for both of these businesses right now, I would still model the roughly $40 million per quarter, and I think Bryce later will talk about combine these businesses in our future view are over $2 billion. They are multibillion dollar upside, but I wouldn't model this yet. And then, again, I -- as I said earlier, I've never had so much fun. I love working together with all of our partners. And next, Prabu will talk to you about our semiconductor business -- as I mentioned earlier, Peru is 1 of the most brilliant and trusted innovators in the entire semiconductor industry. I talked to him probably 5 times a day every day, 7 days a week because again, it's just we love this innovation. So now let me turn this over to Prabu. Thank you.

I think it's always difficult to keep up the energies. I don't like to come after Gary. It's difficult to keep up the energy. I think if you really look at those -- if you are to look at those, I always think about, if I have to do 1 pad, what do we do, 1 page, my message is, we saw this AI inflection early. We invested in this influxion early. And we built our AI compute leadership over many, many years, over more than 10 years. Now it is the opportunities. It's a big tailwind for us. This is a simple message. We built this readers. I spend lots of time with our customers and discuss on what I have very different -- now I'm going to tell you why I'm confident that we're going to outgrow the market, we are going to gain the share. That's what my presentation is about. Really look at those -- the foundation is a is all about power, performance and bandwidth. That's what it's all is about. The foundation for this AI compute is leading high-speed memory advanced packaging. When is a leading logic transistor and more wire, high-speed memory is DRAM, high-speed DRAM and a high bandwidth memory and packaging is all about chip-to-chip wiring. Really look at all these 3 segments, the fastest-growing segments now today and like I said, we are #1 in each of these segments, and we are enabling this segment. That's why I'm confident about these 2 points or more than 2 points of share increase. So talk about advantages. What is your main advantage. Really look at those. Like I said, we saw the influx early, the investor in the early. That's why we are #1 in each of these segments. Leading ag logic, DRAM and advanced packaging. We built broad and enabling portfolios for these inflections, and we can connect them in unique ways to solve technology challenges, which no 1 else can do because of our broad portfolio, because we know how to connect them. We are building EPIC, new R&D collaboration model with our customers -- this is for faster innovation to customer commercialization and a higher innovation success rate. I will go through in details. Our leadership is built over years, not today. If you really look at those, we invested in R&D centers. We invested in capabilities, and we built partnership over years. And if you really look at the R&D center, come back to R&D centers. We saw the packaging inflection much, much earlier. We invested in the packaging R&D center in Singapore in 2001. We saw the materials inflections, materials engineering, and started this material slab with the in-U.S. -- in Singapore 2018. Also, you can see the full flow lab in meta-centric now the EPIC, you take into a whole new level, all about high-velocity co-innovation with our customers. That's what our customers know it. We also built unique capabilities with innovators who could connect all the way from materials to process, to equipments to device to systems. They understand better, they know how to connect it. And we build a partner see for complementary capabilities. basically is a good example. You don't have bonding and we built with -- for a die-to-wafer bonding we built a partners. And also we occurred companies. We know panel is coming. We are core companies, Tango, PVD panel next and also plating panel and also cigarette for x-ray and if relates provides us great foundation for our future growth AI is driving market enable WFE, the fastest-growing segments are fondilogic, DRAM and advanced packaging. We are #1 in each of these segments. In the past, year, Applied Materials has outperformed the market in all these segments. In the next 5 years, the market outlook is even more favorable of incremental WFE growth will be in these segments -- Sorry. Yes. Like I said, it's all about power, performance and bandwidth. There are architectural inflections that will enable these devices, power performance and bandwidth in logic. You can see get on or out, better transistors, more transistors and more wiring, backside power, even more wiring, DRAM going through the inflection, high-bandwidth memory, even 6 scare, a lot of innovations left, 4 of current 3D DRAM for higher density and lower power packaging, system-level packaging, 1,000x more IOs and lower power. Applied has leadership in all these inflections. Today, I will show you how we are growing our sham and share in these critical inflections. Really, they look at this. All the infants are going tread. One thing, if you look at common in last everything is going ready, which means more materials in generic. This gate all around transistor, example is a case study for materials engineering in Acton. Gary talks about magic. This is where it is happening right now. Really look at those. You think of it what a gate on cancer looks like in the picture -- in reality, how it looks -- this is how it looks like at an atomic level, or term by auto, how it is arranged. And I really look at those, where is the complexity between the 2 nanosate 10-nanometer space, 100 an storms, 10-nanometer. There are more than 5 distinct materials, 1 on top of each other. Each 1 of them want to 2-nanometer thickness. Now when you look at those, the interfaces between these materials need to be engineered for best performance. interface dominate, interfaces are thicker than the materials itself. So you've got to play with the interfaces. That's where materials engineering coming in. Every angst matters, every no matter, even depositing it, modify, analyze every young star matter, and you need this atomic level precision at an industrial scale. That is commercialization. This is the power of our unique and connected portfolio. Really, Gary talked about this slide. Applied has a broad portfolio across depositions, edge, modifications and metrology and the inspections. We are leading in many of these technologies, and we have a unique way of connecting these technologies for a better device performance. Like you saw on the last page, we understand this inflection better, and we know how to address them by connecting our technologies through co-optimization and integrations. Cooptimization where independent technologies are optimized for a better performance. You saw the last page, integration, where multiple technologies are integrated in 1 tool under vacuum. You saw last page, different materials or more, the interfaces or 1 nanometer thickness, they cannot be exposed to yet. If it exports is gone, you don't see that. That's what need to be integrated. Here is that -- and also where we don't, however, we are extending these technologies to our partners where we have complementary technologies. These connected solutions industry's most critical challenges, example, co-optimization. This is 1 transistor contact. I can tell you, this is 1 of the most critical step in the device. Traditional staff, it takes 3 steps to do that. You will see that yet deposition and Epi deposition. Traditional model, if you do, it limits the transistor performance. you don't get good performance, let me put this way. In the new corporate what we do, where edge CVD are improving their performance very significantly. The #1 bottleneck for our customers today is transistor performance. Device makers target 15% performance not over node. It's a full load, I'm talking about. This coat solutions, delivered 5% performance gain. This alone delivered 5% performance there. Value for our customers device performance. And yes, value for Applied. Cumulatively, these products will deliver over $2 billion revenue for Applied over until 2030. Another example of wiring. This is why we consume 50% of the chip power today. As the wires become smaller, node over node, resistant goes up and further increase the power consumption. And our portfolio defines wiring road map. Our portfolio really defined worrying road map. We talked about the 3 solutions if you put multiple steps, they cannot be exposed to her. This integrated solution, this product is a good example. This integrated IMS solution reduced the resistant node-over-node. I've been in PVD. This is for many, many years. Every year, we are the bottleneck for wiring. We find a way to remove the bottleneck and we make it happen. You can see node over node. These copper wiring products will deliver $3 billion revenue, 2026. This is just 1 of our integrated products. Our integrated solution portfolio revenue grew 20% to 30% of our system revenue today. Let me tell you how important Applied Material is for a compute. Over 60% of the materials on a chip today are created by Applied Materials upon. We have leadership products in transistors, wiring and advanced packaging, not just a new product going back to decades. In the last 12 months, we launched 13 new products for these 3 segments, transistor wiring advanced packaging. Apex takes it to a whole new level. If you really look at those, innovations from the universities on materials, all the way to the commercial chip, 8 to 10 to 15 years. That's too long. It's a sequential process. It's very slow. It may not work anymore. In the Epic, what we do is a parallel model compressing the time 2, where you can see that materials products and development of customers all work together to solve a problem. So look at the customers and partners, universities, co-innovate with us under 1 roof, parallel development, value for our customer earlier access to materials, earlier relative to technologies. This means for them faster innovation, faster R&D, faster ramp and faster commercialization, HVM. For Applied it will tell us that to invest R&D dollars efficiency. And more important, we are designed in early in our customer. Imagine these kind of complicated, complex structures. We are descending much earlier with our customers under advanced nodes. Now we talked about unique advantages. Let me talk about what are the big opportunities we have. AI is driving more demand for applied logic transistors unwiring technologies. Why? Larger die, more transistors better transistors and more wiring. Our leadership in logic transistor and wiring. These technologies are moving to memory enough. Also, our leader in wiring technologies is extending to packaging. On chip wiring is moving to chip-to-chip wiring right now. And all of this will deliver strong SAM and strong Saad growth for Applied Materials. Here is an analysis of modern mobile chip versus AI training chip and agent chip. Three key observations. The logic silicon area transistor grows 70x from mobile to agent. The number of logic transistor grows 2x mobile to Ragentek. The number of wiring layers triples. Remember, wiring is 1 of the Applied's largest business. where we have a very strong product. This is how AI compute is driving growth across our businesses. For decades, be innovated logic and wiring technology. I keep repeating logic and wiring technologies. AI is all about moving data faster and with a lower power. Because of that, our leadership technologies in transistor wiring are moving into memory right now. DRAM is more aggressive, most aggressive in adopting these technologies, transfer technologies, moving from planar to high metal gate, then moving to FinFET. In DRAM, the number of wiring layers are more than doubling from conventional DRAM to HBM DRAM. Also remember, NAND is following transistor technology, DRAM, both in wiring. Wiring, in fact, it's more right now, you can see 5 to 10x. These inflection will increase applied salmon chat. Let me now show you how our SAM and share are growing in each of this node. I really look at the leading edge, the same -- the sham growth around, from 12 million note to 15 billion 1.4 nanometer and our share increases by 3 points over this transition. In DRAM, we said in the past, that of Spire will be around $6 billion. Right now, from -- you can see that from 6 to 4 of Square, I think we are increasing -- increase -- and even for 3D DRAM, even more, revenues even more. And we expect to increase our sham share by 5 points. Wiring. I talk about wiring. Adrian and I can talk about wiring. We are #1 in on-chip wiring over many, many, many years. We are taking that leadership position from on chip wiring to the chip-to-chip wiring connections, high-bandwidth memory, 3D IC logic the same technologies we use to drive copper road map inside the chip are being adopted to connect the chips using micro bumps, you see bumps, using TSVs, using audios. Because of this, our advanced packaging is now expected to grow more than 5 billion within a few years. and we expect to outgrow the market in the next 5 years. Let me give you 1 example of our leadership in the packaging in. Applied enabled 3/4 of the packaging process steps from TSB formation to micro bombs, both front side and backside of the wafers. We are #1 HBM packaging with more than 60% Sam share. HBM continues to grow, and we expect to grow over -- we expect over $1 billion this year alone. The next big packaging inflection is hybrid bonding. Really look at those people don't realize that there are many steps you can think of it as 3 groups. The process before bonding, the bonding itself and the process after bonding, we call postponing. Applied Materials portfolio addresses 80% of the steps across all these 3 areas. In pointing, we partnered with basic where we have died to wafer bonding, we call it connect integrated tool. Our portfolio is just as strong in both pre and post bonding steps. Hybrid boarding is already being adopted in HVM, 3DC logic and also co-packagertics, the next big opportunities in HBM. Hybrid bonding will double our SAM as compared to microbumps and TSV. Another major inflection transition is silicon wafer interposers to panel. I repeated many times. Earlier, I told you we invested in packaging earlier 2012. That has given us leadership portion in wafer-level packaging. Today, we are doing the same -- exactly the same panel packaging. Earlier, we saw the inflection early. We're investing in early. Applies already built a broad portfolio for panel inflexions including both organic and inorganic, such as recently we talked about but next for panel copper plating. And also, a few years back, we or panel PVD company. We saw this early, and we are investing early. We are very well positioned with our customer and confident to further grow our share. I will close today with a few words on our growth opportunity in ICAPs. An important part of ICAP, what we don't normally talk about, important part of data center, data center build-out is power and photonics. These are growing very rapidly, and we expect over $1 billion revenue this year. Overall, I see that ICAP's market is growing this year, benefiting from 28-nanometer tranches. A lot of these nodes are transit 28-nanometer, where Applied is a really good push with the high-k metal gate transitions. In the future, we expect the physical AI to be a big growth driver for ICAPs. To summarize, AI is growing AF to much higher levels and applied SAM is around 55% of the WFE market. Next, our all of the AFF growth we expect through 2030 to be where Applied has #1 leadership positions, leading edge fondlogic. DRAM, advanced packaging. I say show you a priority is increasing both our SAM and our share in all these 3 segments, 3 areas. As a result of this, Applied expect to gain over 2 percentage market percentage mark points of APL by 2030. See this growth includes our performance -- outperformance in metrology and inspection market, which Keith will now discuss. Thank you. Now over to Keith.

It's great to be here this morning. I'm Keith Wells. I'm in charge of our Image and Processing Control group, but you can kind of think of me as the M&I guy at applied. That's what I do. So we drive all the M&I business within Applied, and that's what I want to talk to you about today. So we have 3 thesises that are driving our growth in M&I. First is we see remarkable growth in optical inspection. We're -- I'm going to go into this in a little bit more detail in a minute. But this is a very, very big market. It's $9 billion. Today, we only serve about $2 billion of the $9 billion market with our products. And what I set out to do when I came to Applied 6 years ago was to create a complete portfolio so that we could address the $9 billion in this market. And it takes a few years. This is not simple to make a lot of these technologies come to market. We won't really talk about these today, but I can assure you that in the next few years, you're going to see new products introduced in the optical market to go after this business and capture more of this TAM. Second, thesis around our growth as we are the leaders in eBeam. And I'll give you many examples through the presentation today. Gary talked about it, Prabu talked about it. We'll show you in real concrete terms why we are the leader in eBeam with our technology. And then finally, you've heard it throughout the presentation today. We're going to talk a little bit more about how synergistic we are to help drive the semi systems business, and how that will result not only in growth for our business, but growth Probus business. So let's go into a little bit more detail. So first of all, Gary already told you this, but in optical inspection, we grow 50% in revenue from 25% to 26%. We see very strong CAGR going forward in this segment. customers want alternatives, we're providing alternatives, and we're benefiting from that. We also see positions, as I said, in the segments of these markets that we don't participate in today. There are 7 billion of additional TAM out there that we can address, and we will be introducing new products over the next few years to address those. It won't be easy. But in some cases, this is owned monopolistically by other companies who fundamentally or customers are pulling very hard to -- they want solutions. They want alternatives. So I think that's a very strong thesis to our growth plan. Second is eBeam. So again, 50% growth between 25% and 26%, mainly driven by the need to drive yields, very important. And we see strong share gains over the next 5 years in this segment. And what we did a few years ago is that we brought out cold field emission technology, which is very high brightness electron sources, coupled with high-energy electrons -- and by doing that, we were able to gain 2x in revenue over our nearest competitor. That technology, those architectures created differentiation and have really driven this business. And we intend to keep our leadership in electron optics by reducing many new tools over the next few years and introducing them. And finally, the big theme here is how do we co-innovate. How do we work together with the semi systems with our AGS group to give them thousands of data points, so they can do experiments. They can increase the R&D pace by 3x. We now can do that in EPIC that will come online, we'll co-innovate. I'm very excited about this. We are the only company that has both advanced process, advanced metrology and the ability to test it in labs. There are no 1 else out there can take those 3 things and put them together. I'm very excited about it. And what you're seeing is the financial results from this. We expect $3 billion in systems and service revenue in 2016 over that and then very high growth going forward. So that's our 3 thesis is. Now let's talk a little bit about the uniqueness. Gary presented this slide. And what I really want to do after I just recap the slide is to go into actual examples that prove our points around this. So huge expansive portfolio, thousands of data points generated by our cutting-edge electron metrology and inspection capabilities going into our analytical platforms and the proof points you see over on the side. One is that we'll do $2 billion alone in e-beam metrology. So the market is voting for this type of capability. In addition, we see the acceleration of both semi systems and AGS innovation. And then as I said, again, finally, when we get to EPIC, I think it's all going to come together, and we're going to be able to move very fast, and innovate faster than any other company out there. But let's turn to some examples. So Prabu in his presentation, talked about how important it is to have high-performing transistors. And so here is an example of how we enable high-performing transistors. Epi is key to the performance of the transistor. And when you do epi deposition, sometimes you get voiding, you saw it on prebudget. You don't want voiding. Now how do you determine whether there's avoiding there or not? Well, what traditionally has been done is at. So they said, explain Tim, you're Gee, you need to tell people what Tims are. So what attemis, as you go into a wafer, you scrap the wafer, you cut a very, very small slice out of the wafer down deep into the architecture, you pull that out, you put it into a transmission electron microscope and you image. And you hope you cut in the right place, you probably get 5 to 8 transistors to look at. It doesn't give you much data. People love it because people love pictures and they feel very good about the picture they see there, and they can see the void in that image, and they go, okay, I need to work on my epi deposition recipes, very slow, very inefficient. Now imagine you have an electron metrology tool that could go to thousands of points across the wafer and detect voice. You don't have to guess where to cut. You can create a full wafer map and that's what we're showing there. a heat map that shows you, look, there are voids in the red areas. They are not voids in the blue areas. So what do we do? We take that information, we start tuning our processes in order to eliminate the avoiding. We do that much, much faster than relying on Tims. And this is what's been driving much of our growth in this area because people clearly see -- they see -- and you can -- if you can see it, you can fix it. And not only is this used in R&D to accelerate R&D, it's also used after the fact in HBM to monitor the process. So it's not just a business about R&D. It's also a business about putting this in line and monitoring it and then getting adoption with wafer starts, more good chips out. Here's another example that Babu gave and how do we help them. This is about wiring. So a very typical thing in wiring is obviously via fill and polishing, right? This happens many, many times in any process. You saw those high stacks that Prabu were showing you in his presentation. So what do you want to do? First of all, you want to deposit your metal and you want that deposition to be uniform and non-pattern dependent. And how do you figure that out? Well, again, what we're able to do is after a PVD deposition, were able to go in and see, are you overfilling, are you underfilling -- or do you have pattern loading effects. You can now, again, with a full wafer map, thousands of data points go in and accurately tune your PVD deposition better than you ever could in the past. No tips. Then the next thing you need to do once you get the PBD done correctly is you need to polish. So you go in with your CMP and you polish it. And the problem is you can over polish or you can under polish. So you can have protrusions or you can have DISH. You don't want either. You want to get the polish right. Again, the provision goes in there takes thousands of data points across the wafer and gives you feedback about how good your CMP process is. We put these together, we greatly accelerate our ability to deliver yield to the customer and ramp the process. And once again, this is an HVM application that people use to monitor the processes. So that's how we're helping transistors. That's how we help in wiring, how do we help in DRAM. So DRAM, as Gary alluded to, is adopting CMOS. But they're adopting it on an older node, a FinFET type device in most cases, instead of a gate-all-around type device. And so when DRAM customers came to us and said, "How can you help us make sure that we're accelerating our logic and transistor learning?" And we said, well, of course, we've done this in the past. And this is an Epi example again. at slightly different Epi structures. But what you're seeing here is you don't want those epi structures to merge. You want a deposit such that they're clearly separated, so you get optimal transistor performance. And we said, well, several years ago, we put together the ability to image an open epi formation, which is what you want or a closed epi formation, which is what you don't want in order to get a good transistor. And we said we can deliver that to you in the matter of weeks. It's easy. We know how to do this. And so both in our labs and at major customers, we now -- they now use this to help tune their processes and look at reducing variability across the wafer. We often talk about yield good, bad die. That's not exactly what yields all about. Yield is also about minimizing variability. So if you have transistors, some part of the wafer that runs slightly faster or slightly slower and another part of the wafer, that's bad. You do not want that. You want all transistors to run the same and the way you do that is to do massive measurements in order to reduce variability across the wafer. Again, another big driver of our business. Now this is a new market. This is exciting. This is where I feel like I can geek out a little bit. Imagine when you saw Pros cross-section of the atomic level gate all around. Imagine if you can go in and measure that non-destructively on the device. And that's what we created here. So we took our CFE technology which is very, very high resolution, and we pointed it down at individual transistors and that will generate X-rays. Now if you put the right detectors around that, you collect the X-rays and you can actually identify very, very sub-instrumenfilm thickness and also composition. And you can do this on device and in line and so not only is it something that we developed in the labs over 2 years with our IMS group and Pabst area, but it's also something that we're now doing out of the customer. And why does the customer want to do this? Because traditionally, the only way you understood whether or not you're making the transistor correctly is to wait to electrical test, which is weeks later, okay? You don't want to wait weeks. You want to make sure that transistor is performing correctly, the variability is low. So while what we're able to do is to give the customer the ability to look at their transistor performance in line weeks before they actually have a functioning device. And so we think that this new market, which we're very excited about, is we're several hundred million dollars and it's not in our P&L today. It's growing, and I'm very excited about this. Now we all talked a little bit about advanced packaging in our presentations today. The thing about Avac packaging is it's all about yield. You're taking now and good chips things that yield it already, and you're going to put them into a very complex package. And the last thing you want to do is to destroy that known good chip and so the intensity of metrology inspection has gone through the roof in this market because people realize the value of known good package is out. And so a few years ago, our customers came to us and said, as these are getting more and more complex, what can you do in the eBeam area? You've got even products in the front end line. Can you modify them and adapt them for the back of the line. And we did that and we're seeing revenue from that already across multiple products. But the other thing that came to us and said is, can you give us a cost-effective optical inspection solution. Some of these the optical solutions are tens of millions of dollars. We want an alternative. We want something that's far more cost effective. And so when we understood that, we started a completely new platform to address this market. This market went from a few hundred million a couple of years ago to now well over $1 billion because customers want to inspect every die for small particles before they place it, because a small particle in the wrong place, Onvia is going to destroy that known good die and destroy that package potentially. So the value of optical inspection in advanced packaging is exploded. We're also not going to talk about it today, but we also have X-ray solutions in this area, too, that allow us to see very subtle effects in the bonding in the advanced packaging. So finally, just to recap. 5% growth in our core businesses from 25 to 26 with extremely strong CAGR going forward, okay? So very excited about that. Two, as I said, in new products, I came to Applied Materials. I worked at KLA for 27 years. I love metrology inspection. I overlap there with Gary. Barry and I worked together there. We're very passionate about this. What we wanted to do was to build out a portfolio. We want to have every product that can address the large markets in optical inspection. Every product that addresses the large market and eBeam technology and then we've got some other things that we're pushing that I talked a little bit about today with advanced packaging, which we see extremely strong growth in and then also the material metrologies and other X-ray applications very excited about what we can do there. And then finally, what we're also doing is helping our partners within Applied to innovate faster, and to bring solutions faster and help with their growth. And it's extremely synergistic, which I hope you saw from the examples today. So thank you very much for having me.

Thank you. And now it's time for Tim to come on up -- all right. Good morning, everyone. Thanks for joining us this morning. It's a pleasure to be here. In Gary's presentation, he talked about AI computing leadership and how there are 2 paths to growth. The technology race, which Prabu and Keith just talked to you about and all the innovations that Applied is bringing to the market, and then the capacity raise, which I'd like to talk to you about now and how the services team enabled by our industry-leading AIx connected platform is helping customers optimize both yield and output with their existing installed base. This is the fastest way to profitability for our customers. And then how as they bring in new capacity, we're able to ramp that capacity faster. So we're driving yield innovation, ramp innovation and output innovation, all within our AIx connected platform. So before I go into the details, I want to spend a little time on the graph here that Gary introduced earlier in the presentation. So many of you are familiar with the S curve for a factory, yield and output on the Y-axis time on the X-axis. And this outlines essentially the life cycle of a product as it moves through a factory. There's the R&D phase where we spend a lot of time with our customers optimizing their process as well as the hardware. There's the critical ramp phase where our customers are trying to, as quickly as possible, optimize yield and output and then there's the high-volume manufacturing phase where we're trying to reduce variability in the factory so that the fab is operating at maximum output and yield. So through our AIx platform, we have created capabilities that help our customers in all 3 phases of this lifetime. And as EPIC comes online, you'll see that we're actually able to advance that even faster. So as fab utilization has improved this year, AIX adoption has increased this year. Our revenue has grown more than 20% in calendar year '26, and we've increased our future model to a mid-teens compound annual growth rate going forward. So EPIC is really going to change everything. It's not just about co-innovation of our new platforms with our customers in the collaboration areas of the facility. It's also about enhancing the co-innovation of our service products with our customers. And how is this different? Because we have customers co-innovating with us in this facility on dedicated systems, we're able to connect our AIx AI-enabled servers to those platforms much earlier than we have been in the past. And we can monitor the tools as they're developing with the customers' recipes to get a good baseline fingerprint of the tools. Our service engineers from AGS will be operating hand-in-hand with customers in that collaboration space, which will allow us to get a good baseline on how these tools operate in production. And then when the tools are transferred from our facility in EPIC to either the customers' R&D or HVM facilities, we'll be able to ramp those processes faster, leveraging many of our capabilities, including crossmatch. So let me talk to you a little bit about how service works in the AI-enabled era. So as all things service starts with the tools. So we have an enduro here. It's got a lot of specialized sensors on the tools and all of our tools generate tens of thousands of sensor parameters, and we feed these into the AIx platform. So what is that platform. It's a platform that focuses on actionable data tens of thousands of sensor means there is a lot of data. We don't need all that data to solve every problem, but we need to figure out which data streams are most critically important to solve the problem that we're working on. We run that through our Insights Engine, which is our analytical tools, our AI-enabled capabilities that are developed by our subject matter experts and we build that on 59 years of equipment design technology, which is our domain knowledge to create a suite of capabilities, which we use with our customers in their facilities. As Gary mentioned, we have 37,000 chambers connected today. About 80% of those are very securely remotely connected capabilities in partnership with our customers we have more than 18 quarters of data that shows consistently that we get 30% faster service resolutions and even less escalations when we compare the same tool set connected to our AIx servers versus a tool in the same fab that's not connected to AIx servers. So what does this mean for customers? It means that as they look at all the variabilities that I mentioned earlier in the factory, whether they are tool matching variabilities, process recipe variabilities, the maintenance, health of the tools, minor part variabilities that might change the output of the factory, when we run them through our AIx innovation engines, we can tighten the distribution of variability across the fab. This drives more output from the facility as well as higher yields on the facility. And I've highlighted a few of the capabilities that we've developed in the AX portfolio today. This is not an exhaustive list. This is just some of the key ones that we're working with customers on today. So let me talk about 1 of those in a little bit more detail, and that's cross match. So Crossmatch is a critical capability, and it works like this. When a fab and applied materials work together to optimize an R&D process, we've done it visually here by moving that gold dot into the center of the target on the right-hand side. So this is the best possible outcome that we can get on a given tool and process. So we define that as a golden tool and a golden wafer. As a customer ramps through that very steep ramp period in the life of a factory, there are $1 billion of opportunities for our customers if we can ramp that fab faster, particularly in the current environment. So we take the cross match capability, and we move all the tools as we ramp them to overlap very nicely on top of the R&D developed process. And that gives us 1 golden tool in R&D moving to multiple golden tools in high-volume manufacturing. We've been able to execute software with our partners in the business units and the product side and we've been able to do this now 50% faster than we've been able to do in the past with this automation, and this drives more good wafers out and more wafers out of the facility for our customers. So it's good for yield. It's good for output for our customers. It's great for us because it makes us much more efficient than we have been in the past in ramping these facilities and allowing our customers to drive to a maximum output. Let me talk about a couple of more examples that we have in the portfolio. Now before you look deeply into this slide, I want to explain what this looked like before we had the AIx portfolio. So this is an example where we have to replace an electrostatic chuck or an ESC over time in an etch process. For those of you that know this process, it's a very challenging environment in the chamber. There's challenging chemicals, which will eventually start to attack the edge of the eCheck, which is what holds the wafer down in the chamber, and you start to get a failure, maybe delamination at the edge of the electrostatic chuck. Historically, we didn't know when this was happening until well after Keith tools would identify the problem through a review process and then they would go back and stop the tool and evaluate whether we need to do a change. All that productivity that was lost and good wafer outs were lost to that cycle time waiting for the metrology to identify the issue. And our first generation of our AIx solution, which is in the left panel, we were able to create a health index by which whenever we saw that challenges at the edge of the electrostatic chuck, we can immediately stop the process, and we wouldn't put that WIP at risk in the factory for our customers. But we knew that wasn't good enough. We wanted to create a second-generation solution, which we see in the middle panel. We took our AI-guided models with our subject matter experts, and we created an algorithm by which we can clearly see how the life of the truck is progressing in the chamber. The little triangle shows when the failure happens. And again, we can now use a time-based algorithm to understand when that will happen in the future. The right panel is a real-life example with a customer on how we executed this change to our AIx platform with this Gen 2 solution. So the triangles represent when the electrostatic chucks actually failed, and the horizontal blue bars show what our prediction model predicted they would fail. And you can see a very high correlation -- in fact, we now have the ability to predict 30 days in advance when a Chuck is going to fail with more than 90% accuracy. So why is this important? For a customer as they're looking at their WIP or their wafers in process and what material is coming to a tool, they can now take an unplanned event, which would be the failure in the past and turned it into a planned event, and they can time that when they have the best lull in their incoming WIP, so it has least impact on the factory. For Applied, it's great because we have a very complex assembly here that we can bring in from our logistics system and we can have a trained engineer there, and we could do a controlled replacement of the chuck as opposed to an unplanned replacement of Chuck. It's good for the customer, it's good for Applied. Let me give you another example. This 1 got to advance here. This 1 is an ICAP example. So this is high-density plasma, HDP, CBD. We've had these chambers in the field for decades. Whenever we do maintenance, there are a number of nozzles around the inside of the chamber that have to be replaced over time. The historical way we did this was we had open up the chamber, our engineer would replace the nozzles, they would close the chamber, pump it down, run a wafer, send that off to metrology, get the results, and then we have the graphic that you see on the left. An experienced engineer would then open up that chamber. And based on that map, they would replace the nozzles in a different configuration to try to optimize the nonuniformity on the wafer. They would close the chamber, pump it down, send it to metrology. This would happen up to 6x with an experienced engineer to optimize the nonuniformity on the wafer. With AIX Pro, we're able to do that now in a single review of the metrology map. So AIX tells us where we should position the nozzles. We go back and we verify that and we take iterations down to 2 iterations, saves about 65% of the time for maintenance and drives more good wafers out for our customers. So it's a great outcome. Let me share a third and final example here, and this is yield innovation. Gary talked a lot about yield innovation and how important it is for our customers today. So in partnership with the equipment team, we've developed a unique sensor that sits on the front end of the etch system in this particular case. That sensor is connected up through the customer's manufacturing execution system and also connected to our AIX servers. And the purpose of this sensor is to allow us to fine-tune the placement in each of the etch chambers. And we connected to the MES so the customer can periodically direct the tool to do this recentering again. And then, of course, it's connected to our AIx server so we can optimize that position with our algorithms. This is extremely important. You can see in the center panel that the edge effects that we see at the edge of a wafer really drive yield fallout. We get these tilted etches, which don't land on their contacts, they result in open and lower yield. In most wafers today, 6% to 10% of the die are on the outside edge of the wafer and yield is lower there. So if we can move those etches to completely vertical, we're able to make land more contacts, get better yield for the customer. When we showed this data to the customer, they immediately fan this out across their entire installed base of these tools, and we have a second-generation solution in process right now. So I've talked to you a little bit about AIX this morning. I'd like you to hear from 1 of our customers, and that's Manish Mattia, who is the President and Chief Operating Officer of Micron Technologies. Please run the video. Micron is a leader in applying AI across semiconductor manufacturing, leveraging more than 1 billion monitoring points across our global fabs. Our partnership with Applied has shown that meaningful results come from combining the best capabilities across both organizations. Applied and AIX leverage unique analytics service engineering expertise and predictive capabilities to solve problems that would have otherwise gone undetected. The collaboration has strengthened yield performance, improved productivity and created a powerful model for data-driven manufacturing excellence. Micron's global adoption of AIX provides significant benefits for our technology development and manufacturing organization. and is a critical component of our valued partnership with Applied Materials. So Manish and Micron have been a great partner as we find AI out into their factories and appreciate him contributing to the presentation today. So I'd like to wrap up with a single oil here. And this is a summary of the business overall for Applied Global Services. You can see we had a long period where there was no growth in the business. And as we shifted to outcome-based services in the mid-teens, we were able to drive a low double-digit growth compound annual growth rate. But as we've moved into the AIX area, we've actually increased the model, and we think long term, mid-teens is the plan going forward. You can also see that we've increased our subscription rates from the low 40% to nearly 70% in the plan going forward in 2030. And the model is really quite straightforward. As the installed base grows, and we're able to put more tools into our service network with AIx enhanced services, we're able to drive more benefits for our customers. And these benefits are in the form of our AIx services, as I communicated today, driving yield and output innovation. So we've got 37,000 wafers or 37,000 chambers connected today. We expect that to grow to over 90,000 chambers by calendar year 2030. And as we drive incremental value for our customers, better cost of ownership, we are rewarded with long-term contracts. They are currently greater than 2.5 years and at a more than 90% renewal rate. In fact, our AIX services are statistically higher renewal rates than our service overall. And this is going to allow us to continue to drive profitability and a 20% revenue per tool growth between 2025 and 2030. So thanks so much for your attention today. I really appreciate it. And next up is Brice. Thank you.

Good morning. Nice to see everyone. Thanks for attending our breakfast, and thank you for your interest in Applied Materials. Today, we talked about how we're growing and enabling the most enabling portfolio in the industry. I'm going to talk about -- put that in perspective from an R&D perspective and then also talk about how we've delivered 10 years of excellent financial performance while executing that strategy. We'll talk about how AI is accelerating our outlook and growing demand across the industry, we are investing to double our lab and manufacturing capacity for the company. We'll talk about our outlook, the targets we have for 2030, growing profitability and shareholder returns. And we'll also talk about our capital allocation priorities and how we will invest going forward, continue to reinvest in the business and continue to grow our shareholder returns. So on this chart on the right, we show how R&D grew over the 10 years from over $1 billion to over $4 billion. Some people asked me when they're asking about Applied Materials, Oh, if I'm interested in the company, aren't I just buying the whole industry because you have a large portfolio. And I wanted to share that is not how we think about adding to our portfolio that we're adding scale or adding size. The way we think about it is what you heard today, being the most enabling company for our customers and for innovation. And I'll just summarize a few of the examples here that we went through a couple of different color codes -- on the blue side, Prabu and Gary both talked about how the company's strategy shifted early on in this time period. And on this slide, we note the PPACt strategy in shifting from in the prior period, making the tools perform better, focusing on the operations of each tool, Shifting to actual chip performance. So the PPAC TV strategy and platform, performance power area cost of the chip, the actual device not just an individual step that we were doing. Prabu talked about transistors. He talked about contact. He talked about wiring all the wiring layers that are in the chips as we work with customers to optimize those as bundles of solution from applied materials that can be reused by the customer, we're really able to help deliver a smaller form factor, lower power, higher performance, which is where you get excellent performance at the chip level from the customers. At the same time, we also hired and built expert integration teams that understand how the chips come together. We built our Integrated Materials systems group where we put multiple tools together in a cluster so that you can build the component under vacuum. Prabu talked about how as we're assembling those materials, they never touch air and those produce some of the highest quality solutions for our customers. We also started the Metalla and the metal lab is where we can do short loops or longer loops. So if there's 22 steps in a process where you're building a part of a chip, we can do all 22, control that for the customer and build the highest-performing solution. So that was really the first major change thinking about the inflection from Moore's Law sort of the shrink environment to no, you have to focus on materials. You have to focus on integration. The second 1 we highlight on this slide in the yellow is the company also understood that the way to advance system performance think about data center AI server systems is you have to put a lot of chips on a platform, on a package, on a substrate. Think about GPUs, CPUs, accelerators, network, stacks of HBM memory, all of these have to go on a package. And so we talked about the Internet capabilities. We talked about panel processing. So the yellow investments that you see on this page where we have a partnership with BSE on hybrid bonding. We recently made acquisitions that help us with X-ray technology and thin interconnects on the packaging, and we had our Tango acquisition, which helped us with our panel platform, continued to focus on what do we need to have in the portfolio to be the most enabling for our customers to solve that next generation of performance challenge. The last 1 we highlight here in gray is the AI investments that we made, the AIx platform is taking the massive amount of data from our tools and producing solutions for our customers that help them drive the tools to the highest yield and highest performance in their factories. We call that actionable insights, and it's -- we continue to add sensors and capabilities to our equipment that give that amount of data that we can use to drive performance for the customers. Keith also talked about how we significantly increased the product road map in our metrology and inspection business, and that's so we can the problems that need to be fixed in our lab, and we can also serve the customers with the equipment they need to see the same things in their HVM. Finally, some of you saw that our EPIC center that we just unveiled yesterday. EPIC is where we bring all of these solutions together under 1 roof to work with our customers on the long lead challenges that the industry had, and hopefully, you had a chance to see that. So with all of this R&D, we feel extremely well positioned as we look forward to new technologies and process technology and enabling our customers. So 10 years of excellent financial performance. The graph on the left, the bar graph shows the revenue growing over the 10-year period. at a 12.2% revenue CAGR to $34.3 billion. Gross margin on the top line grew 680 basis points to 50%. And over the time period that's non-GAAP gross margin. Non-GAAP operating margin, up over 1,100 basis points over the same time period, earnings per share CAGR, 22%, nearly double the revenue CAGR over the time period, benefiting, of course, from buybacks, which we'll cover later, average free cash flow. So the business is a high profit cash flow business. And the last 2 points are really important, I think, for investors and investors that may not know the story as well as others. We can reinvest in this business. We're reinvesting more than 50% of our cash generated back into the business, R&D, CapEx, working capital, small acquisitions to grow our footprint grow our solutions, grow our service capabilities and continue growing the business. So greater than 50% reinvested and -- there's a greater than 30% return on invested capital that we've averaged over these 10 years, and we expect that actually to be increasing as we move forward while we continue to invest in the business. So executing the strategy of building the most enabling portfolio that we described over 10 years, delivering excellent financial results. I'll 0 in on gross margin, of course, there's a lot of interest on the path of gross margin it's indicative of the strength of your product line, which we say is becoming more and more enabling. So 680 basis points over the 10 years the drivers, if I break out the drivers for the change and increase in gross margin, the largest 1 and what I want investors to think about most is the portfolio itself, more and more enabling. Every time we build a solution that is critical and helps the customer innovate. We spent a lot of effort on that, and it's providing value to the customer. And if we do a good job on pricing, we've worked hard on our pricing process for the last 4 years. If we do a good job on pricing for the value that, that tool is providing, then you see the value of the portfolio increasing, and that's the #1 driver of the increase across this time period. Number two, our semiconductor systems business, that's our largest business. It's our reportable operating segment. We report our gross margins for that business. It's over 55% in the recent quarter. So as that business is growing faster as the business has accelerated, that gives us an uplift from gross margin. And finally, we have operational efficiencies -- we've diversified our manufacturing base. We have a large operation in Asia, in Singapore. We've diversified our supply chain that helps us grow and scale our profitability, and that's helped from a gross margin perspective also. Now as we look forward and we get to the end of the presentation, we expect these same drivers to be in place. We expect growth in our semi systems segment. We expect to continue to innovate at the portfolio level and produce enabling solutions, and we expect to continue to expand our manufacturing operation going forward. So we think we're well positioned to grow the value from a gross margin perspective. Switching and thinking about the forecast for a second as we're talking about investing and spending and the financial parameters for the business. On the right side of the page is sort of a fun graph -- more than a year ago, when we were having a conversation, we were talking about a $1 trillion semiconductor industry by 2030. Now you can see that the estimates are between $1.7 trillion and $3. Now fair enough, some of this is pricing at the device level, and you don't need more wafer starts for pricing. But there's plenty of wafer starts required when you saw some of the system requirements at the package level that showed all those devices that have to go into AI systems. -- fabs are being built at a faster and faster pace. And when we look on the left side of the page, it's not just the AI and the semiconductor devices. All of the arrows are indicators that we follow, all of the arrows are pointing in the same direction. Hyperscaler CapEx over $1 trillion, token consumption accelerating the use of AI agents accelerating the cost of those coming down package sizes, the number of transistors on a chip, the number of chips in a package, accelerating and making that package business grow strongly. Fab utilization, leading-edge logic, 100% and DRAM, 100%; NAND, almost 100%. ICAPs are more mature process node, customer processes healthy zone now after a couple of years of digestion. It's a favorable environment for WFE to be sure. We talked about how leading edge logic, DRAM and advanced packaging will be the engines of the growth for the next few years. We talked about our strong position in that. Those markets will be responsible for approximately 75% of the WFE growth looking forward in this forecast range. And with our leadership, we expect to grow our market share more than 2 percentage points. Finally, Gary highlighted, it won't probably be a smooth curve of growth people are talking about in studying data center energy availability. We've said that clean room capacity will be a key determinant of how much equipment can be consumed in any particular quarter. And then supply chain. We've raised our forecast on our supply chain every single quarter this year. Everybody is racing to add output. And those things will determine how smooth the ride is as we move forward to serve this demand function. All right. Thinking about the global investments that we're making. The map gives you an indication. First of all, Epic was our largest investment. Some of you saw it yesterday, but we invest strongly in the United States. So the EPIC center is a headline investment. We're also investing in Arizona, Massachusetts in Texas, Texas where our largest manufacturing site is -- so manufacturing labs, research center, logistics centers, all of these in the U.S. In Italy, in Israel, new manufacturing capacity, new lab space, training center, new manufacturing capacity and R&D labs in India, R&D offices, lab infrastructure and supply chain investments, Singapore, we just celebrated the opening of our second manufacturing facility there and the expansion of our capabilities. That's helping us serve almost the entire Asia customer base from our Singapore operations. And then in South Korea and Taiwan, more customer-facing investments. So a significant amount of reinvestment in the business. We're investing to grow our capacity from a manufacturing perspective and a lab perspective, more than 2x across this horizon, EPIC is a good example of that on the lab side and diversifying our supply chain globally over this time. I don't have a specific target for CapEx, but CapEx was approximately 8% of revenue this year, and we say it will decline as a percentage of revenue as we move through the forecast horizon. Okay. AI. Fantastic results at Applied Materials. We put a few examples here to share with you. So the first 1 in our hardware development, our actual product development we've piloted the use of AI in terms of simulation and helping speed up the actual process and achieved a more than 4x on the pilots that we've run along these lines. We're implementing that on 20 products now, and we'll expect AI and the types of models that help you do the hardware development to massively accelerate the pace of hardware development going forward. On the software side, software development, 100% of our software developers are using the AI method. So faster coding, testing, release cycles, this is amazing to get to 100%. We report the average productivity gain of 44%. But I'll tell you some of the individual projects we see are 200, 300, 400 improvement -- so 44% is across the entire company, just amazing. And then from an adoption perspective, we have more than 80% of our employees using it every single week, token consumption rising fairly dramatically, 45 in 1 year. We feel great. We think it's investable. We not surprised the industry is investing. We're not surprised that the pace of AI data centers required, we're not surprised that any of this based on our experience. And now I'd like to play a short video from Dr. Yu Cao, our Chief AI Officer at the company. Please queue the video.

I am Yu Chao, Chief AI Officer at Applied Materials. Applied created this role because AI isn't a side project for us. It's central to how we design products run processes and serve our customers. Applied sits on both sides of this market. We are a critical supplier to the AI build-out, and we are also a serious enterprise buyer and adopter of AI. Here's what we see inside applied. Every software engineer now writes production code with AI with very substantial productivity gain. And across various organizations, engineers report multiple hours of time savings per week, and they are reinvesting that time into harder problems, not easier ones. Over 80% of our employees use AI tools every single week. We spent real money on this because the return is real. It's a P&L decision made by our management team and rejustify every quarter. As models get cheaper and more efficient, our spending goes up, not down. A lower cost per token doesn't shrink the demand. It unlocks work that simply wasn't economic before. We see efficiency as an expansion mechanism, not a ceiling of spending. For applied the prices acceleration, AI-enabled design is taken years out of our product development -- we're also targeting multiyear compression of the materials discovery cycle. That is a value creation story first, faster time to market, more share and faster time to solution for our customers. with cost savings as a secondary benefit. We are early in the AI revolution. The opportunity ahead of us is larger than what's behind us. And every layer of it starts with materials engineering. Thank you.

Excellent. Thank you, Dr. Chao. So thinking about AI and operating leverage, I shared how we're using AI in some of our product development, software development, et cetera, and seeing fantastic opportunities. When we think about our operating spending for the company, first thing to share for the investors is our operating spending as a share of a percent of revenue has dropped from 22% at the beginning of the 10-year horizon to 17% today. You can see the R&D curve I mentioned before, it was growing to -- growing to $4.2 billion, 72% of our spending. So when we think about adding resources in the company, what sort of investments we're making, most of our additions are focused on R&D and the portfolio becomes -- of spend becomes more and more tuned to R&D as we're going through. In fact, you can see that SG&A, we bent the curve a little bit in the past couple of years. So revenue is growing faster than R&D, but we're continuing to invest. We gave you the focus, which is the most enabling portfolio. We expect that on SG&A, with the adoption of AI and the adoption of automation at a faster pace going forward that will get significant efficiencies from our corporate functions and from SG&A in general, which will allow us to continue to grow profitability and operating leverage. Next, I'll cover our 2030 calendar year targets. So the first 1 on the top left, we've talked about 2 percentage points of additional share. So we're not giving a WFE forecast. And the reason is, of course, that's changing at a rapid rate -- what we are giving you is how we think about it internally and what our own framework is. We expect to outgrow WFE. Our target is to outgrow WFE. We think more than 2 percentage points of share will gain across this horizon. And again, you heard the reasons leading edge logic, DRAM, advanced packaging, as those -- we are gaining share today and as those continue to evolve in technology, like to foresee like the 3D DRAM, like to CFE like to panel packaging, hybrid bonding, we will be gaining share with those transitions as the industry moves forward. So it's not a WFE model, but you can model our equipment business based on growing faster than the industry. For the Applied Services business, Tim talked about a 15 mid-teen CAGR growth rate -- and we modeled that as greater than $12 billion by 2030 with that type of growth rate. And that business, Tim highlighted how it's an excellent source of recurring revenue for the company. Other revenue in our other category, Gary headlined 2 businesses, our display business and the MAX OLED investment that we have that we're looking forward to significant adoption and growth and then the SENS Waveguide photonics business that Gary talked about, we expect those businesses to be more than $2 billion by 2030. 4% non-GAAP gross margin is our target for 2030 and 40% non-GAAP operating margin, representing expanding operating leverage beyond the margin improvement. The bottom left, you see our tax rate, we have a 15% estimated tax rate for 2030. And those should give you the elements of our own targets how we're thinking about the company and allow you to size the company as the market expectations continue to change for WFE. From a capital allocation priority perspective, hopefully, no surprises here. First, just to reiterate the message, we're reinvesting more than 50% of our cash generated back into the business. And I gave you a good perspective on CapEx, R&D, et cetera. We'll maintain -- continue to maintain a strong and flexible investment-grade balance sheet. And then the bottom bullet, we're committed to 80% to 100% return distributions of our free cash flow over time. And you may have questions about what's -- what will be happening with the dividend or what will be happening with buybacks. On the dividend, our Board will make that decision next year per normal. But our history here is since 2005 when the dividend was initiated, it's a 14% CAGR. We doubled the dividend per share over the last 4 years. So a significant focus there. And then from a buyback perspective, over the last 10 years, we decreased our shares outstanding by more than 50%. So again, committed to 80% to 100% distribution of free cash flow going forward. And then just a summary of key messages. So you heard about how we think about growing our R&D, how we focus on what we add to the portfolio. It's about being the most enabling partner for our customers. We delivered 10 years of excellent profitability, executing this enabling model. AI demand is accelerating the whole outlook and certainly the outlook for our business. we're doubling. We're investing to double our lab capacity and double our manufacturing capacity from even today, so higher than the last time I said that. And we're going to continue with our targets to grow our profitability, grow our shareholder returns, continue reinvesting in the business and continue to focus on being the most enabling company. Thank you for your attention. I appreciate everybody attending. And I'll bring -- ask Mike Sullivan to come back up and take us to the next steps. Thank you.

All right. Well, thank you so much for hanging with us here. We're going to bring all of the speakers back out and do a Q&A session. We know you have a lot to do at Semicon West. So we promised to have you out of here by 100 -- and if we run at -- if you still have a question when we're done, we'll ask the presenters to stay here, and we can always help you then if you still have a few minutes extra. So we'll bring out some chairs, we'll bring out the group. Our thought here is we do have, of course, a webcast audience. And what we'd like to do is make sure that we have microphones available. And please don't start to ask a question until the mic is there because our audience won't know what you asked, and we want them to hear it. So we have Mike Runner, Cindy, I believe, on this side. We have Sonal on this side and Marty, my doubleganger is in the middle aisle. And if you have a question, go ahead and raise your hands and let Marty understand and the team understand that you have one, and he will do his best to come out. So please, everybody come on out. join us right. Great. So we have a question right here.

Great. Thank you ever Karia from Bank of America Securities. Thanks for a very informative presentation. Gary, I was hoping to get your perspective on kind of 2 near-term industry debates. One is there's recent news about China perhaps getting to 4x square memory. I was wondering what you have seen on the ground, what is your perspective? And if they do get there, what does that mean for WFE share of wallet for the Western toolmakers -- and the second 1 is this whole debate around memory despecking, right? What does that do? How much of that is real? And what does that do to the overall TAM of memory going forward if there is indeed despecking in some of the new -- so just kind of China and spec.

Yes. I think relative to compute memory and AI. And again, we had the EPYC events over the last couple of days -- and there's just so much innovation that's happening in compute memory. How you also connect it to logic. Again, we were there with all of the leaders that were driving AI server architectures going forward. So I just believe that that pace of innovation is very, very fast. And I believe the companies, the 3 companies that are leading today will continue to lead into the future because, again, there's just so much optimization, those leading companies that are designing those new architectures, what they said when we had that event yesterday morning, and they -- all those people were there, is that they have already very deep partnerships for compute memory for logic innovation, but they need to even go faster because those workloads are changing -- so I have very high confidence there's going to be tremendous growth rates still in compute memory DRAM, and there's going to be tremendous innovation at the component level, in the packaging level and the system level and then the lease backing, Bryce.

Yes, we looked at despecking and our conclusion at this point is DRAM, we expect to still be constrained in what we think the system architects are doing is they're determining that you need less DRAM for some of the different AI workloads. So training was a very heavy different amounts for inference, different amounts for Agentic. So we think what's happening is they're tuning those systems to maximize the amount of output that you can get from a compute perspective for those different workloads optimizing the amount of memory that's used on each of those systems. So that's our perspective. We expect DRAM will remain constrained for a period of time.

Yes. That's right. And then having seen the analysis, the other thing to bear in mind is in the training workloads, they still want as many as tall as stacks as they can get their hands on. The new workloads that may not need as much as that because they can't drive utilization all the way up to the top of the HPM staff, those incremental workloads they are new, and they're additive to the market. And so it's -- everything is increasing. It's not a cannibalization. It's an increase in demand in an area where you may -- instead of having your IO and your storage in the same space, put your storage elsewhere in the system. So it's just a repartitioning -- all right. And then Marty? Yes. Great. .

CJ Muse with Kenner for Strand. First question, Gary or Peru, Much of your discussion on the leading edge was focused on compute and DRAM. Curious if you could speak to how you're attacking optical networking from pluggables to all the way to CPO, wave guide hybrid bonding, new materials. Can you speak to that? And then Bryce, our gross margins only up 400 bps in this 4-year time frame. I would think mix-wise, just from silicon you're up 100 to 200 bps. So we'd love to hear what would drive the incremental? And are you being conservative? .

So I'll start, C.J. Relative to Photonics, we talked about that being a very fast-growing business for us. Photonics and power. There's tremendous innovations that we're driving there. In hybrid bonding, is a very important innovation, more and more vertical architectures, more bonding, better performance, better power and better thermals. I think on some of these architectures, it's not just the better performance, tokens per second per watt, but also yield. And so we're driving -- we have deep partnerships with all of these leading customers. and we're making tremendous progress on the yields. But that really, CJ, is super important on when those inflections happen. So then the second part of the question was... .

Yes. So then we had another question on gross margin for price. .

Yes, sure. So 54% is our target company gross margin. Of course, I remind investors, we're over 55% on the equipment itself today. So 54%, approximately 100 basis points each year, although we're not calling it to be a smooth ride like we talked about. We do have to invest in our infrastructure. I talked about new factory. I talked about new capabilities from a logistics perspective. There's headwinds to manage. So we think that with fuel costs and the like, rare earths and those sorts of things. So we feel that 54% is a good target. It will require us to be continuing to launch new equipment that's more enabling we are raising pricing as part of the process, which I shared to address some of the costs that we're seeing. So CJ, we think that's a good target.

It's Tim Arcuri at UBS. I think this is all great. And I could see how a bar, though, would say they would look at the WFE share of gaining 2100 bps through 2030, and they would look at 2025, and you lost that much share in 2025, and your share in 2024 was down actually off of 2023. So the bear would say, "Well, you're only getting back to where you were in 2024 and 2025. So how would you address that?"

Well, I'll start and maybe somebody would add -- of course, in our math, we're still modeling growth in China and growth in restricted accounts in China. We can't serve leading edge. We can't serve DRAM. We can't serve NAND in China, we're modeling growth there. So you're right, if we zeroed in on all the accounts that we can serve, we'll have a greater share gain than that. And if you look at some of the device end markets, we expect a greater share gain. But if you account for the growth that we're expecting in the restricted markets in China, and again, we're assuming no change in the trade rules, then we think that's a good target for us. .

And I think an interesting point is if you do the math on it, if you look at what happened to us from a trade restriction perspective in 2025, we had access in the early 2020s to 100% of China's WFE market. then the access dropped to 90%. In 2025, it went from 90 to closer to 70, okay? That was a big step down. And there hasn't been a change in trade restrictions that will allow us to go back up to where we were. So if you do the math on this, if you look at our position and you took that factor of trade restrictions out of the equation and then looked at our share, we're actually up and we'll show that to you off-line if you'd like to see it. So we're doing very well where we can compete even in China, where we can compete at 28 nanometers, we're doing very well. And what Prabu also showed you as he showed you, he dissected the growth rates of some of the markets, and he showed you the growth rate of leading-edge foundry logic over a very long-term period and DRAM over a long-term period and showed how we are outgrowing in those periods. So where we can compete, we're doing very well, and we expect to continue to

Atif Malik from Citigroup. I have a question for Keith. Keith, you talked about launching new optical products in first half of 2017. I was wondering if you can pull the curtain a little bit and tell us more about HBM or CVAs. The market itself is very competitive with Nova and N2 and KLA. So what will be the differentiation that LaPrairie bringing in this advanced packaging optical market? .

Right. I think it's a very important point that especially in advanced packaging, the optical inspection market is already crowded. So we would not enter a market unless we understood architecturally how we can differentiate -- and I can't really go into the details. But rest assured, we spent approximately 1.5 years examining what is serving that market today, what the technologies are in play there. And we feel that we're going to bring something to market that is clearly differentiated, clearly sustainable in its overall performance. So we are trying to position the product to have the highest sensitivity at the highest throughput possible using cutting-edge technology. And just 1 other comment there. I think many of those products had been very much restricted in the amount of cost people are willing to put into them because historically, that market has been very cost sensitive. We don't see it as cost-sensitive any longer, just as I talked about today, there's so much money to be made in advanced packaging. The yields are so important that now we're starting to see an inflection where our customers are willing to accept higher ASPs in order to meet the yield demands. .