Thank you all for joining us here on day two of the Morgan Stanley TMT Conference. I'm Lee Simpson with Morgan Stanley. Before we start I want to read a couple of safe harbor disclosures here. The discussion here with Cadence will contain forward-looking statements. It'll make use of certain non-GAAP financial measures. Please see Cadence's most recent 10-K, 10-Q, and website for a discussion of risk factors and their use of non-GAAP financial measures. Please see Morgan Stanley research disclosures disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions on that, please reach out to your Morgan Stanley representative. With that, I'm really thrilled to introduce Anirudh Devgan, the company's CEO. Joined Cadence in 2012, became CEO towards the end of 2021, following in the large footsteps of Lip-Bu Tan here in the audience. Cadence is just an incredibly well-positioned company in my mind. Kind of walk us through, since you took over as CEO, and just maybe your observations over the past, you know, decade or so of being at the company, your overall strategy and vision for the company. Absolutely. Good to be here and thanks for your interest in Cadence. We basically make products, mostly software products, to design chips and electronics systems. Almost any chip design in the world uses some form of Cadence software. Then more and more, you know, our customers are also system companies. About 45% of our revenue is coming from system companies, you know, like car companies or phone companies and things like that. In terms of our strategy, you know, the first thing is to make sure we are good in our core business. Make sure our core EDA products are best in class. We have the most diverse portfolio, you know, for analog chips, digital chips, you know, memory chips, all kinds of chips. We have a pretty broad portfolio in our core business. That's always number one, right? Without being excellent in core, you can't really expand. The second part of that is these system companies. Okay. Like I mentioned, a big portion of our customers are system companies, and they are designing more and more silicon. That's a new business for Cadence. Along with them designing more silicon, we are also selling newer products to them for what we call not just EDA, but SDA, System Design and Analysis. This is simulation products for thermal simulation, power simulation, electromagnetics. That's a huge market. That adds about $8 billion-$10 billion of TAM to our core EDA and IP business. That system can provide a lot of growth for us. That's the second part, apart from our core business. The third growth area is all data and AI. There's a lot of opportunities to not only help customers design AI chips, but apply AI or AI and optimization to improve productivity of our own products. You know, like these days, the chips are about, you know, they have like 100 billion transistors in them, right? These chips, 1 inch by 1 inch. By 2030, they will have 1 trillion transistors, they are a lot more complicated to design. The chip complexity and system complexity is gonna grow up by 30-40x. There's a lot of opportunity to apply AI and get, you know, more benefit to our customers. At a high level, we wanna make sure we are good in our core business, which is EDA and IP, expand into system, both silicon design and System Design and Analysis, and then apply AI to our products. Right. fantastic growth drivers- Mm-hmm. obviously, overlap well with a lot of the secular- Mm-hmm. themes out there in the marketplace. When you just step back and look at those three opportunities that you have, where do you think you're best positioned today, and where do you think there's still more work to be done to have the position that you want in the market? Well, I think we are well-positioned in all those three areas. I mean, the good thing is not to depend on one type of growth drivers. These are three big kind of growth drivers. I mean, EDA, we are very well positioned in our core business, EDA and IP. You know, there are several reports saying we are the, you know, the largest core EDA company. In terms of EDA, we still have a lot of growth in, you know, a couple of companies, big companies that traditionally didn't use that much Cadence. Now we are engaged with them. There's a lot of opportunity in, even in core EDA to grow. Systems, I think, is still in the early innings. You know, in terms of system companies doing silicon, I would still say this is still second innings, you know, for baseball game analogy. Typically, the customers do some chips, and if it works, they do more chips, and then they do more kind of in-house chips. It's still very early on in the systems journey. Our, kind of simulation portfolio, we generated about $400 million of revenue last year out of $3.5 billion, so that's about 12%. The market is huge. The market is $8 billion-$10 billion. Still we are in the very early stages on the, on the system side. AI, we're just getting started. I mean, even though we launched our first products two years ago, I mean, some of the deployment takes time, and it's going to be... What I like about our position is that there are multiple growth drivers, and at the same time, we are very financially disciplined. Not only our revenue growth has improved over the last several years, you know, it used to be about 7% revenue growth few years ago. If you look at now, our three-year CAGR is 15% revenue growth. Okay. Our margin used to be, what, 26%, what, five, six years ago. Now our non-GAAP margin is 41%. There are only a handful of companies that can grow 15%+ and have margin of 40%. Our incremental margin is 50%, so if we generate $100 million more of revenue, we want at least $50 million of profit. I expect that to continue going forward. Not only we have a lot of growth drivers and revenue can grow, but we'll make sure that the EPS grows even faster given our focus on financial discipline. Yeah right. Fabulous business model, for sure. Yeah. Let's, we may come back to EDA, but let's focus probably more on systems. Mm-hmm. On the AI side of things. Mm-hmm. On the system side it's been my observation and I've, you know I've been doing this for four decades, is that as we've seen the complexity of semiconductors increase, at the same time we've gone through a lot of consolidation in the semiconductor sector by itself, and therefore its scarce resources, and therefore I think systems companies definitionally have to have more semiconductor capabilities. How do you think about their problems and challenges to go design these next generation, really complex devices versus that of a traditional semiconductor company? Where is that, you know, how does that opportunity sort of fit in with Cadence and your growth and sort of modeling around that? Absolutely. I mean, Cause when we are fortunate to work with a lot of system companies that designing silicon, what I would say is that probably three main reasons they do it, okay. The one is, you know, if you do some custom silicon, it's better for something. You know, either it's better in power or performance because you can customize, you know, more data based on what the application is. There are a lot of examples, even like when you watch YouTube and it loads faster, you know, there is some video chip that's making it load faster. If you drive a car, you know, there's an AI engine which is faster than. That's always, there's a lot of room to do a custom chip. The second reason is for schedule, right? If you have certain release, you know, every year, Cadence of products, you want to control your own schedule. Third reason, which I think often sometimes overlooked, is if there is enough volume, it's actually cheaper to do it in-house. You know, that volume may be different for different industries, but it's definitely true for cars and phones and, you know, computers and data centers. For those three reasons, you know, this is almost a irreversible trend. I believe we have crossed activation barrier of that. There will be more and more chips designed. The good thing there is that in those companies, the system companies, they're starting from scratch, so they're always open to new ways of doing things, you know. They're also, you know, resource limited, at least when it comes to silicon design, because they haven't done that in the past. Sometimes we do strategic services to get them going, you know. They often are more open to, you know, AI-based tools. They also do more hardware platforms like Palladium and Protium, because you, if you're a system company, you naturally have software stack, otherwise you're not a system company. These days, to bring up the software stack, you need these emulation and prototyping platforms. It's a big tailwind for the entire industry. Cadence is a unique position because we are also leadership in advanced packaging. You know, not just core EDA and IP, but advanced packaging. All the system simulation tools we have developed over the last five years. Naturally, if a system company is doing silicon, whether it's a car or a data center company or a phone company, you know, they're also doing the mechanical design, thermal design, and electromagnetics. There are software components, there are mechanical, electromechanical components. All this is good for our business. Right. Seems like, just the overall kind of content that you might have. Mm-hmm. With a systems company would just definitionally be higher, I would think, as well, just because the efficiency they could have, it's probably hard to be as efficient. Take an example of an Intel that is gonna be designing CPUs for a lot of different users versus someone like Amazon or Microsoft or Google that's gonna do it for their own usage. Is that a, is that a fair thought, you think? Just your ability to penetrate those companies and sort of get more content of Cadence products and capabilities into those systems companies would just naturally be higher. I mean, our semi customers are very good also. I mean, some of them have evolved and some of them have become almost like system companies. I think I gave example of growing up in India, you know, you could barely get, like, a phone line, you know. Only few people where I grew up had, like, real phone lines, and there was, like, a one year wait to get a phone. When the cell phone came, right, they basically skipped over landlines and just went to the cell phone. Okay to me, I think that's a better analogies to the system companies because they don't have a lot of legacy of design. When they start, they can start with the latest what is available. I think some of the semi companies have also done very well in moving to that, you know, latest. Since you're starting from scratch, you're typically more open-minded. This also happens in newer geographies, you know, like China or Asia, because they're designing, or, you know, India, they're coming up from. They just go to the latest technology. We have a greater opportunity to provide a fuller portfolio for that reason. Yeah. Right. How about just there's so many secular demand drivers- Mm. -out here. We're still relatively early innings of cloud. Mm-hmm. Obviously, AI is still. Mm. very early, autonomous everything. When you look at these type opportunities, do you think that your growth rate could actually accelerate just 'cause your opportunity set would seemingly be larger, bigger TAM, bigger SAM, and so on? You've obviously had great growth here in the past handful of years, but when you think about the opportunities ahead of you, which to me are probably greater than ever before, how do you think that overlays against your type of opportunity set? Yeah, it's a good point. Of course, we guide like one year at a time. What we say is, like I said, the revenue growth went from 7% to... We always like to look at three year CAGRs because most of our contracts are three year in duration. Last year, we had a fabulous year of 19% revenue growth. If you look at a three year CAGR, that's like 15%. I think what we aim for is sustainable double-digit revenue growth, okay. 50% incremental margin. I think with both those things, you know, you can provide a lot of profitability growth and EPS growth. We are also returning about half of our cash. You know, we generate, of course, a lot of profit, half of that back in terms of share repurchases. Revenue can grow double-digit. You know, profit can grow more than that because the margin always improves every year. EPS can grow more than that because some of the shares we are buying back. I'm confident in that long-term model. You know, double-digit is already good. Of course, we try to deliver better than that. I think for the investors, that's already a that's our base plan of double-digit revenue growth, 50% incremental margin, and at least 50% of cash flow in buyback. Right. Maybe we can shift to AI. Mm-hmm. obviously, it's been around for a long time, as we well know. Yeah. It's clearly, you know, seen exponential type of just excitement, I think, as it's gotten more into the consumer market and things like ChatGPT. Mm-hmm ... have become buzzwords and so on. Mm-hmm. Just talk about what you're doing, your Joint Enterprise Data and AI solutions, so JedAI. Talk about that. Talk about just overall bringing AI into your product portfolio and how you think it's how the opportunity of- Right AI really impacts Cadence in the future. AI is can be transformational. Of course, there's a lot of hype on AI, you know, like around everybody. Everybody calls everything AI now, you know. That's one issue, so. What we used to call statistics or computer science a few years ago is now AI. You know, I took one Stanford course on AI. It was great, by the way. I'm from CMU, but I love Stanford. Half the course was on regression. If that's AI, then I was doing AI. Then we joke around that, you know, like now if statement is AI too, you know. It's like it's artificial and it's somewhat intelligent. Then if you use the else statement, then it's reinforcement learning because you learn from the if statement. This is a little bit of like AI washing going on. Okay. Part of it are transformational. You know, part of it are transformational. What I always believed, we didn't call it generative AI five years ago, but you know what? If you look at fundamentals, right, there is like, three kinds of sciences. This is like classical stuff now. You know, my dad is a mathematician, so they only talk in like 100-year increments, okay? The classical science is like geometry, right? That's like 2,000 years ago. That's science of place. Okay. The next science is science of space. Okay, that's derivative. That's Newton, right? That's calculus. That's 400 years ago. Then there is science of pattern. Maybe AI is science of pattern we have been waiting for, right? These are three fundamental sciences, and they can last for hundreds of years. You know, look at calculus. You know, a lot of our computers now is differential equations, like discrete differential. I believe that AI can be transformational, but that doesn't mean you don't need like geometry and calculus. Okay. Sometimes people apply AI to, you know. There are certain things you need which are inside out, like from the physical sciences, so physics and chemistry and biology, and then data science is AI from outside in. Okay. What I always believed is you need the internals to be good, and then AI can be used for optimization. That's what we have done for last five years. To give you example, right, you know, we have, for example, optimization tool, Innovus, which is one of the flagship tools. but it runs like in the history of our, you know, software, it's one run. You know, like you give it input, it gets you output. It gives you a very good output. If you look at the customer, they are not running it one time, right? They're running it over and over again. Typically what the customer does, they run something, then they change, and they run it again. They change, they run it again. Okay? Cadence and our industry never provided any automation in that workflow because always single run environment. Okay? The reason for that is there was no mathematical way to transfer knowledge from one run to the next run. Okay? Now with reinforcement learning, you can actually do that. We actually build We have a JedAI, which is our data platform, and then we have AI tools on top like Cerebrus and Verisium and Optimality, and I'll talk to you more about that. What that does in this example is instead of the human searching the design space, you know, you do it mathematically using reinforcement learning. Over 200 runs in this one particular case, instead of doing it. Either you can do it exhaustively, run all combinations. That would be 4 million runs. It's almost impossible. If you do it mathematically with reinforcement learning, over 200 runs, and that takes like about one or two weeks versus one or two days per run, you know, in about 3x, 4 x more the effort, you can get much better answer. And also much shorter because the human would take like six to 12 months to do that. It's a huge advantage. You still need the base engine. It's not like. Then you add AI for optimization. The real value of AI to me is to get away with the mundane tasks and focus on higher value tasks. That's what you happening in generative AI. You can't, you know, if you're a Shakespeare, no problem, you know. If you're writing a regular poem or email, you can write that with ChatGPT, right? The real creativity will still be there. What we can enable with AI is for the designers to move up the stack, and instead of one designer doing one block, one designer can do five blocks, or they can do architectural decisions rather than, you know, a lot of the customers are running these tedious tasks with our tools. That's a huge opportunity. That's a huge productivity improvement. I always believe that AI for optimization is the real value, which is what we are seeing now. Yeah. Right. Where do you think you are on that curve for your products that are incorporating AI to make your customers more efficient, more productive? We have, like, more than 30 projects, okay, for, like, over the last five years. Before I answer that question, okay, one thing is very important to, for you to realize is what is your core competency, right? From a Cadence standpoint, what is a core competency? Our core competency is what we call computational software. That's CS plus math, computer science plus math. That's what, you know, my background and that's why we have, you know, out of 10,000 people, there are 9,000 engineer, you know, 6,500 people in R&D. That's their background. When you apply that to silicon, you know, that's EDA and IP, you know. You can apply it to system, that's simulation. If you applied that to data, that's AI. We have a lot of expertise we can bring to AI. For example, AI, the classical training algorithm in AI is nonlinear conjugate gradient, for example. We have used that in Innovus placement for more than 10 years. Some of the algorithms can be, are well known in EDA, can be applied to AI. Now, in our journey, you know, in terms of R&D, we have a lot of capabilities. In terms of products, the first products were launched about two years ago, and the response is phenomenal because of the benefit they can do. About last year, we had this data platform, because very important to have the data platform, which we call JedAI, you know. We have JedAI as a data platform because like I said, in the old days, you know, EDA tools and all these tools were built for single run, you know, like OpenAccess, which Cadence pioneered. JedAI is for multi-run, you know, not just one instance of the design, you can have multiple instances. You have the data platform, and then you have apps on top. The key apps are Cerebrus, which is for implementation, Verisium, which is for verification, Optimality is for system design. We have launched three big products, and we will launch two more this year for PCB design, PCB and package design, and for analog design. I would say that in terms of products, relatively soon we will be very complete. The adoption is good, but I think it'll take multiple years of adoption as, you know, as people, you know, evolve their design flows. That's good, right? I mean. Right. Okay. Before I open up to the audience, maybe we can talk a little about simulation, 'cause that's-. Mm-hmm. I think a really interesting area for Cadence. It leverages so much of your core competencies and capabilities. Talk about your vision behind what you're doing there, maybe some of the acquisitions you've done so far, and maybe what else is kind of the opportunities you see ahead for that simulation business. Yes. Yeah thank you for that question. Like I said, I mean, we look at the world in three concentric circles. The silicon circle, the system circle, and then the data circle. The perfect example is like electric car right? You have all the navigation data, then you actually have the physical car, hardware, software, electrical, mechanical and then the chips that drive it right? When we do computational software for silicon, that's EDA, right? When we go to the system level, the next level up, there's a lot of software business. Actually, there's about $50 billion software kind of for systems. For us, you know, we want to do the computational part of it because that's the, that's our core strength and that's what is going to grow. The computational part of the system business is system simulation. You know, things like finite element, CFD, you know, electromagnetics, you know, designing cars and planes and thermal. That's about $8 billion-$10 billion market, and that's why about five years ago, we invested significantly in that space. Okay. There is a coupling of like 3D-IC also couples the silicon and system together. We are doing pretty well. You know, that's growing like 27% last year and is profitable. Our advantage is that not only we can couple semi and system together, but the algorithms in EDA were always much more complicated because you're designing like chips with 100 billion variables and that Moore's law is changing every two, three years where the system side has been more static and less kind of innovation. We can build that R&D intensity we have on the chip side and apply it to the system side. There's a lot of potential to couple this, these things, and it's gonna happen. I mean, this merger of silicon and system you see happening now, I mean, we saw that, you know, five years ago. The question is, who's gonna do that? I think it's very difficult for the system companies to get into EDA, whereas, you know, we are swimming downstream when we go from EDA to system companies. The customers want that, right? You know, you remember like a few years ago, you know, you go on the plane, and you couldn't take your Samsung phone because it was melting or something like that. That's the connection of silicon and system, and still that problem exists. I feel very good. Again, I think the other good thing about simulation, you know, of this $8 billion-$10 billion market out of the $50 billion market, is simulation, always you can have multiple simulators, you know. Our competitors in that space, I wish them well anyway. I think we are much better, but you can have multiple choices. Whereas some other parts of the system market, like when you do, like, design of buildings or design of mechanical design, those are more UI-based products, you know, like PowerPoint. Then you don't want multiple choices. We don't want to do things which are not computational. The simulation is computational. The customers will have multiple choices. The other thing I like about system simulation is that. There is R&D synergy because of the math that is similar. There is customer synergy. 45% of our customers are system companies. The margin profile is even better than EDA because we want to grow in areas that have good margin rather than other way around. We started with simulation, so we have about $400 million in revenue. The other thing that is interesting in simulation is that, you know EDA, what people don't realize, 1/3 of EDA is simulation. You know, we do a lot of optimization like place and route, but you have to simulate first before you can optimize. EDA simulation is also very profitable. That's the most profitable part of EDA is always simulation. The other thing EDA or chip design is good at is optimization. This is the history of chip design, right? There is very little optimization in system design because they could barely simulate like a wing or a, or a, you know, car. You know, like, we have this partnership with McLaren, you know, F1. By the way, that makes me very popular at home, you know. Yeah. We have this partnership with McLaren. I visited McLaren. It's a beautiful car, and we are doing all this CFD simulation for them, right? The range of the car and the speed of the car depends on how good the shape is. If you look at those fins in the front, they have very sophisticated fins, but a lot of them are designed manually. You know, first of all, you can barely simulate the whole car, then you don't do enough optimization. Whereas with now Optimality and AI, you know, the EDA or chip design has a huge history of optimization. We can automatically design those things. I think that can also provide a huge benefit to the system simulation side is couple that with optimization. Yeah. Yeah. It's huge opportunities. It leverages your core competencies against these massive, you know, growth drivers in the marketplace. Let me see if there's any questions in the audience. Yes. How do you think about? There's a mic right there behind you. Thank you. Hi. Thanks for the opportunity. How do you think about China? How do you think about the way you kinda deliver product there? How do you think about it in, you know, if there's some sort of continued battle with China, their ability to kinda compete and your ability to kinda provide solutions? Yeah, China is a great market. If you look at over the last five years, it has done pretty well for us, right? We expect it to grow well. I think, and they have big investment in semiconductors. You know, they have more than, I don't know, 1,500, 2,000 companies. That's one other good thing now is each country is investing in semiconductors. Even India, okay, and, you know, Israel and EU and U.S. I think China is gonna be a good opportunity. Now. You know, we follow all the U.S. regulation. I think more of the issue in China is the U.S. has some regulations. Those are mostly targeted towards manufacturing, and we, you know, we work with the government carefully, and so they're not as material to us on the design side. A lot of design in China, even like, there were some reports yesterday, I think the U.S. government is trying to restrict certain very advanced things for military use and other things. A lot of the design is, you know, cell phones or, you know, TVs and electronics and washing machines. Even that's not even the intention of the U.S. government to affect. All that requires design of chips and design of electronics. I talked about the same things that are true in U.S. and Europe are true in China with merger of system and semi. Then, you know, the other question we get asked is, are there, is there local competition, you know? You know, we are used to competition, right? There is some local competition, but, you know, we are investing significantly in R&D, right? About 35%-40%. You know, if a system company is designing chip, whether it's in U.S. or Europe or China, they want to use the best technology, right? As long as we have good products, we will do well in China. Can you just size the China revenue, not from, you know, from global companies, but just the indigenous companies in China today for you? Our China revenue is about 15%. Yeah. Okay. Most of it is local. I mean, some of this is multinationals there, but yeah. Okay great. We're just about out of time, you've covered a lot of great ground here in terms of the capabilities of the company and really how it overlays against the opportunity set in the marketplace. You've obviously spent a lot more time as CEO now, in the past, you know, year and change. What's the one thing you think that investors just underappreciate or just don't know about Cadence in terms of your capabilities and opportunity? Yeah, that's a great point. I think what I would say that investors and public at large don't realize how essential we are to the whole semiconductor and electronics ecosystem. What I joke around sometimes is that if we didn't have our kind of software, we'd all be riding horses, you know. It'd be like, it'd be like Game of Thrones or something like that. It'll be cool, but it won't be as productive. I think what people don't realize, we are, you know, essential to the design of chips and electronics, and we have the luxury to participate all over the world in all verticals. It's having like I really love my job having like a front view seat of all the innovation happening globally, all the major players in the industry. That's a great position. Yeah. Married against a business model that gives you phenomenal visibility- Exactly. Versus almost anything else out there in tech land. Anyway, thank you very much. Yes thank you. Thank you all for coming.