Ladies and gentlemen, welcome to the Synopsys Earnings Conference Call for the Q3 of fiscal year 2023. At this time, all participants are in a listen-only mode. Later, we will conduct a question-and-answer session. If you would like to ask a question at that time, you may press star one on your telephone keypad. To remove yourself from that queue, it is star one again. If you should require during the call, please press star zero, and an operator will assist you. Today's call will last one hour, and as a reminder, today's call is being recorded. At this time, I would like to turn the conference over to Trey Campbell, Senior Vice President, Investor Relations. Please go ahead, sir. Thanks, Lisa. Good afternoon, everyone. With us today are Aart de Geus, Chair and CEO of Synopsys, Sassine Ghazi, President and COO, and Shelagh Glaser, CFO. Before we begin, I'd like to remind everyone that during the course of this conference call, Synopsys will discuss forecasts, targets, and other forward-looking statements regarding the company and its financial results. While these statements represent our best current judgment about future results and performance as of today, our actual results are subject to many risks and uncertainties that could cause actual results to differ materially from what we expect. In addition to any risks that we highlight during this call, important factors that may affect our future results are described in our most recent SEC reports and today's earnings press release. In addition, we will refer to certain non-GAAP financial measures during the discussion. Reconciliations to their most directly comparable GAAP financial measure, measures and supplemental financial information can be found in the earnings press release, financial supplement, and Form 8-K that we released earlier today. All of these items, plus the most recent investor presentation, are available on our website at www.synopsys.com. In addition, the prepared remarks will be posted on our website at the conclusion of the call. With that, I'll turn the call over to Aart. Good afternoon. We delivered outstanding results in the Q3, exceeding the midpoint of all our guidance targets while reaching another quarterly revenue record. Revenue of $1.487 billion was in the high end of our guidance, with non-GAAP operating margin at 35.3%. GAAP earnings per share was $2.17, while non-GAAP earnings per share was above our target range at $2.88. We generated $560 million of operating cash flow and ended Q3 with a backlog of $7.1 billion. By now, you have all seen our other news. Before I address our segment results and outlook, let me warmly welcome Sassine Ghazi to the call. Today, we announced that the Synopsys board has named Sassine as Synopsys President and CEO starting January 2024, and that I will take the role of Executive Chair of Synopsys board at the same time. I'm absolutely thrilled with this transition into the CEO role for Synopsys for Sassine. Sassine is uniquely qualified. He's a proven operational leader, a technology innovator, and a trusted partner to our customers and ecosystem friends. He's so much more than that. He embodies our values and culture and inspires our company, including me, with his results-focused leadership. Sassine, welcome to your first of many Synopsys earning calls. Thanks, Aart. I'm incredibly honored, humbled, and profoundly grateful to the board and you, Aart, for placing your unwavering trust in me. You built Synopsys from a disruptive startup into one of the world's essential semiconductor ecosystem companies. I'm so proud to have been a part of that journey for the last 25 years, working with you, our leadership team, and the many colleagues across the organization. I'm determined to build upon our strong foundation, drive innovation, and propel Synopsys to even greater heights of success. I look forward to engaging with all of you moving forward and to the continuing partnership with Aart. Thanks, Sassine. You have my full support. Now, let's turn to what we're seeing in the market. Technology industry trends are playing to our strength. The AI-driven Smart Everything era is putting positive pressure on the semiconductor industry to deliver more. Despite economic challenges, semiconductor design starts and R&D investments continue unabated. Our relentless innovation drive has made Synopsys a catalyst for our customers' success in this new growth era for semiconductors. In fact, the market is playing out much as we expected when we planned the year, and we are executing accordingly. Based on continued strong design activity, our high confidence and high confidence in our business, we are raising our full-year revenue guidance range to between $5.81 billion and $5.84 billion. We are increasing our year-over-year non-GAAP operating margin improvement expectation to 200 basis points. This is approximately half a point up versus prior guidance. We are raising our full-year non-GAAP EPS range to between $11.04 and $11.09. Shelagh will discuss the financials in more detail. Prior to giving color on our segment results, let me update you on our AI progress. By now, I hope that we all understand that AI can and does and has further potential to unlock massive new productivity gains. While we continue to embed AI in everything we do, not surprisingly, one consistent question most of you are asking is how we'll monetize our AI leadership. Let me address that question head-on through the techonomic lens of product differentiation and business model framework, including some early proof points. For AI monetization, we see three distinct value streams. First, through our design participation in the explosive growth in demand for AI chips. Second, by pervasively embedding our pioneering AI across our full EDA stack, which we call Synopsys.ai. Third, through AI-driven efficiency transformation as we optimize and automate our own internal workflows. Let's start with AI chips. Use cases for AI are proliferating rapidly, as are the number of companies designing AI chips. Novel architectures are multiplying, stimulated by vertical markets, all wanting solutions optimized for their specific application. Third parties estimate that today's $20 billion-$30 billion market for AI chips will exceed $100 billion by 2030. In this new era of Smart Everything, these chips, in turn, drive growth in surrounding semiconductors for storage, connectivity, sensing, A/D and D/A converters, power management, et cetera. Growth predictions for the entire semi market to pass $1 trillion by 2030 are thus quite credible. We are uniquely positioned to benefit. In the semi ecosystem, Synopsys is the leading EDA provider to AI chip designers. Designers are requiring unmatched capabilities in design tools, particularly at the most advanced process nodes. They also need our leading interface IP portfolio, as AI chips are banking on enormous amounts of data, driving new, faster, and lower power interconnect protocol. Synopsys excels at this. In summary, AI chips are a core value stream for Synopsys, already accounting on a trailing 12-month basis for well over $500 million. We see this growth continuing throughout the decade. Let's move to our second value stream, Synopsys.ai. This is where, starting in 2017, Synopsys, incidentally led by Sassine, pioneered AI-driven chip design, and we have relentlessly advanced the state-of-the-art ever since. Using our AI to automate entire design subflows, our customers report schedule reductions from months to weeks, while simultaneously also achieving better results in terms of speed, power, and area of the chips. In February, we reported that our customers had passed 100 commercial tapeouts using our AI. Today, the tally crossed 270 as adoption continues rapidly. Nine out of 10 of the top semiconductor vendors are using Synopsys.ai in production, and the 10th one is already testing our solution. What makes this doubly relevant is that the worldwide semi industry has a significant resource shortage. Third parties estimate a design engineering gap of between 15%-30% by 2030. Even the multiplicity of national CHIPS Acts recognizes this, and AI and design automation will be critical to help bridge the gap. That's why the industry's first AI-driven full EDA suite, Synopsys.ai, comes in. Initially launched in 2020 for design optimization, we have since added AI-driven tests and verification flows now in commercial adoption. Usage is expanding rapidly as customers are seeing stunning results. In the last quarter, our customers have demonstrated up to 10x faster turnaround time and double-digit improvements in verification coverage. Customers are also reporting more than 20% silicon test cost reduction. Recently, we engaged Synopsys.ai for analog and custom design. One of our top customers used our AI-optimized Custom Compiler to achieve a 6% performance improvement over manually crafted custom circuits. Further, further completing our Synopsys.ai stack, more AI-driven manufacturing flow extensions are coming soon. Back to economics. Synopsys.ai revenue is just starting to ramp, early proof points give us high confidence in its long-term growth prospect. We've moved from project-based experimentations to customers now adding Synopsys.ai subscription. Synopsys.ai has driven more than 20% value increases in several recent digital implementation renewals, often leveraging significant growth for the underlying core tools used by Synopsys.ai. This quarter, we saw multiple full flow displacements to Synopsys.ai, driven by up to 10x productivity differentiation versus the competition. Brings me to Generative AI. Over our history, key disruptive technologies have catalyzed innovation opportunities for Synopsys to deliver leaps in productivity. GenAI is such a technology. Anchored in 35 plus years of experience in developing model-based solutions, now with unparalleled data assets, assets portfolio, we intend to harness GenAI capabilities into Synopsys.ai. We see this delivering further advances in design assistance, design exploration, and design generation. On the design slope spectrum, from optionality to optimality, in other words, moving from many options in early architectures to highly tuned, error-free tapeouts, GenAI techniques will augment the exploration, accelerate design choices, and automate some design generation. This will further broaden the intelligence dimensions in our Synopsys.ai. These new capabilities represent additional customer value, opening multiple new monetization opportunities. We will elaborate more on our roadmap in the coming quarters.... Which brings me to our third monetization value stream: operational efficiency transformation. GenAI isn't just an opportunity for our customers. We ourselves fully intend to eat at our own AI restaurant, so to speak. We see significant operational efficiency and automation potential in processes across the company, so that our employees can focus on higher ROI tasks. Our experimentation is in full swing, and we are rapidly learning the strength and challenging of these new approaches. Overall, fast progress on our AI journey, and it is great to have Sassine on the call for Q&A, as he is very focused on our AI business strategy and monetization. Let me now give some color on our segments of Design Automation at roughly 65% of our business, Design IP at about 25%, and Software Integrity at around 10%. Starting with Design Automation, we saw strong revenue momentum, and the segment delivered its first $1 billion quarter. Fusion Compiler momentum continues to grow, with increased customer share and Synopsys-enabled customers taping out first to a number of leading manufacturing nodes, including TSMC N2 and N5A, Samsung SF3, and Intel 18A. Fusion leadership at advanced node has also translated into key HPC core wins at both semiconductor and hyperscale companies. Transitioning to multi-die chip design, our 3DIC Compiler platform continued momentum across verticals, achieving deployment on the industry's first advanced 3D stacked heterogeneous design for smartphone. We also expanded our multi-die ecosystem enablement, including qualification for leading foundries, latest multi-die flows, and support for key 3D design standards. Of note, we deepened our collaboration with Samsung Foundry to accelerate multi-die system design for advanced processes. Let's move to verification, where the need for acceleration is paramount. In Q3, we won a ZeBu hardware-assisted verification engagement with a RISC-V AI chip provider, and saw HAPS deployments for prototyping AI chips at a large hyperscaler and a large HPC company. Synopsys Cloud continues to deliver substantial differentiation and time-to-market gains for our customers. Our SaaS solution, which accounts for 70% of our cloud users, continued to gain strong adoption, with multiple AI chip startups leading new SaaS deployments. Turning to Design IP, which is roughly 25% of our revenue, we had an excellent quarter working closely with some of our partners to enable the most advanced process nodes in the design ecosystem. Just this week, Synopsys and Intel announced a very significant expansion of our long-standing strategic partnership in EDA and IP to speed the design and manufacturing of advanced SoCs and multi-die systems for Intel processes. This comprehensive agreement enables Intel's internal IDM 2.0 team and their external foundry customers to accelerate chip and system design with a powerful portfolio of essential IP developed by Synopsys for Intel 3 and 18A processes. Synopsys IP is now key to ramping and filling multi-billion dollar wafer fabs as the advanced node IP supplier of choice for customers and the manufacturing ecosystem. Further supporting this, in Q3, we also announced the industry's broadest portfolio of silicon-proven IP for TSMC's N3E process, as well as an extensive portfolio of IP for all of Samsung Foundry's advanced process technologies. In automotive, autonomous driving ADAS systems continue to drive strong demand for our IP. This quarter, we exceeded 30 design wins in 5 nm and won our first 3 nm design at a marquee automotive OEM. All in all, we have won IP sockets on more than 100 ADAS chips. Third, the Software Integrity segment, which represents 10% of our revenue. Against a continued challenging macro environment for enterprise software, the business delivered solid results. The imperative for security and quality in software has always been critical, and with the rise in Gen AI-generated code, big new risks are emerging. Racing forward, we continue to develop innovative new solutions, like our AI Code Analysis API offering on our Polaris SaaS platform. AI Code Analysis API enables developers to automatically submit code snippets from code assistants, such as GitHub Copilot and ChatGPT, to receive instant feedback on whether the code may originate from risky open source project. In summary, we had outstanding Q3 financial results and operational execution and are confident in our strong close to the year. We are raising our guidance for full-year revenue and year-over-year op margin, as well as non-GAAP earnings per share expectation. We have a resilient business model, and our customers continue to prioritize investments in the chips and systems that position them for future growth. We continue to invest in technology leadership, multi-die design solutions, state-of-the-art IP, and the leading-edge AI-driven EDA suite to help catalyze this decade of smart, secure, and safe products. Last, but certainly not least, I am just delighted to welcome Sassine as our new CEO. I would like to thank our employees and our partners for their passion and commitment. With that, I'll turn it over to Shelagh. Thank you, Aart, and congratulations, Sassine. I look forward to continuing to partner with you as you transition to CEO and scale the company to the next level of growth. On to results. Q3 was another outstanding quarter with record revenue and earnings. EPS was above the high end of our range. We continue to execute well, which is a testament to our execution and leadership position across our segments, robust chip and system design activity by our customers, who continue to invest through semiconductor cycles, and with $7.1 billion in non-cancellable backlog, the stability and resilience of our time-based business model. With our continued confidence in the business, we are raising our full year targets for revenue, non-GAAP operating margin improvement, and EPS. I'll now review our Q3 results. All comparisons are year-over-year, unless otherwise stated. We generated total revenue of $1.49 billion. Total GAAP costs and expenses were $1.19 billion. Total non-GAAP costs and expenses were $963 million, resulting in non-GAAP operating margin of 35.3%. GAAP earnings per share were $2.17, and non-GAAP earnings per share were $2.88. Now, on to our segments. Design Automation segment revenue was $1 billion, up 23%, driven by broad-based strength. Design Automation adjusted operating margin was 41.4%. Design IP segment revenue was $350 million, up 12%. Adjusted operating margin was 24.7%. Software Integrity revenue was $133 million, up 12%, and adjusted operating margin was 16.9%. Due to continued macro impact on this segment, we now expect Software Integrity revenue growth in 2023 to be below our long-term guidance of 15%-20%. Turning to cash, we generated $560 million in operating cash flow and used $300 million for cash for stock buyback. Our balance sheet is very strong. We ended the quarter with cash and short-term investments of $1.8 billion, and total debt of $18 million. Now, to guidance. As we have previously communicated, we had expected a strong H2. We are again raising our full-year outlook for revenue, non-GAAP operating margin improvement, and earnings. For fiscal year 2023, the full year targets are: revenue of $5.81 billion-$5.84 billion, total GAAP costs and expenses between $4.544 billion and $4.564 billion, total non-GAAP costs and expenses between $3.78 billion and $3.79 billion, resulting in non-GAAP operating margin improvement of 200 basis points. Non-GAAP tax rate of 16%. GAAP earnings of $7.85 - $7.96 per share. Non-GAAP earnings of $11.04 - $11.09 per share. Cash flow from operations of approximately $1.65 billion. To targets for the Q4. Revenue between $1.567 billion and $1.597 billion. Total GAAP costs and expenses between $1.184 billion and $1.204 billion. Total non-GAAP costs and expenses between $1.005 billion and $1.015 billion. GAAP earnings of $2.17 - $2.28 per share, and non-GAAP earnings of $3.01 to $3.06 per share. Consistent with prior years, we will provide additional comments and guidance for 2024 when we report next quarter. In conclusion, we delivered record quarterly revenue and earnings. Based on our outstanding results year to date and strong outlook, we are again raising our targets for the full year. We continue to see strong momentum in the business, reflecting our leadership position across our segments, robust design activity by our customers, who continue to invest through semiconductor cycles, and the stability and resiliency of our time-based business model. With that, I'll turn it over to the operator for questions. Thank you. Before we begin the Q&A session, I would like to ask everyone to please limit yourself to one question and one brief follow-up to allow us to accommodate all participants. If you have additional questions, please reenter the queue, and we'll take as many as time permits. With that, it is star one to ask a question. We'll take our first question from Jason Celino with KeyBanc Capital Markets. Great. Thanks for taking my question. I, you know, frankly, I don't know where to begin. You know, Aart, what a run, and Sassine, well deserved. Maybe Sassine, sorry, sorry to put you on the spot here, but can you just frame your vision around AI and, and how closely you've been working with the AI strategy? Sure. First, thank you, Jason. As Aart mentioned, actually, the AI journey for Synopsys started around 2017. I was the general manager of our EDA business at the time, and no one in our industry was talking about AI in 2017 for EDA applications. Around the 2020 time frame, we actually had the customers using it in early production stages, and now, as you saw the number, many, many tapeouts. At the time, we started with the design space as the early stage of high impact using AI. As you have seen us talk about the last couple quarters with Synopsys.ai, where we're expanding the impact into test verification, analog, custom, manufacturing, et cetera. Aart mentioned in his remarks that we have customers at this point buying our AI solution as part of their subscription license. You know, when a customer does that, they already see the value and the impact, and they're willing to pay for it, and that's the stage we're in at this point. Okay. No, that's great. My brief follow-up, I think it was mentioned that in some renewals you're seeing a 20% increase because of AI. Is this mainly driven from the tools themselves, or is this more related to the upsell of the core because of the compute? Thanks. I'm sorry, the 20% increase in what? I, I missed the first part of the question. I think Aart mentioned that in some renewals you were seeing 20% increases in value. I was just curious on, you know, the drivers of that, or maybe I misheard. We are seeing absolutely two, two factors. One, there's a pull-through of the technology that our AI system uses, like Fusion Compiler, PrimeTime, et cetera, et cetera. The customer is adding money, new money in the agreement based on the AI system that we are selling them. It's not only an upsell and a pull-through of the license, it's incremental value that the customers are adding to their renewal with Synopsys. Okay, great. Thank you very much. Thank you, Jason. We'll take our next question from Gary Mobley with Wells Fargo. Good afternoon, everybody, and thank you for taking my questions, and, congrats to both, Aart and Sassine on, the transition. Thank you. I want to pick up where, where the last discussion point left off. I wanted to maybe probe into, you know, maybe how many renewals have come up since you went from on a per design subscription for AI tools to it rolling into baseline license renewals. I just want to get a sense of how many of these license renewals are now including AI. As you know, an average EDA contract is about three years. 2020, when we started with customers, and we have number of those customers included it in their renewal. So we're already in that first stage with number of customers, including it in their three-year contract. Okay. Thank you for that, Sassine. I wanted to change topics and move to the different trends in the operating margin for the different business segments. I know that you called out in the past quarter-to-quarter volatility in the op margins for the IP business, but we now have a trend with the trend downward for the past two quarters. Maybe if you can speak to, speak to that, specific to the IP business. Then conversely, you're showing nice gains in the Software Integrity business with seemingly not much revenue ramp. Maybe you can speak to the undercurrents there and, and as it relates to OpEx controls on the Software Integrity side. Sure. So I think it is, you know, this is the change that Aart and Sassine drove in the organization, so that's why we've got this, more comprehensive segment reporting, and you're able to see what, is going on in our, our three large segments. If I talk about Design IP specifically, we, we really think about that business on a long term. As Aart talked in his prepared remarks, we're building out, an IP portfolio for each new node, for each different foundry, for each different customer. Think of us as constantly investing in IP, and when we're signing contracts with customers, we're signing an agreement for a specific amount of dollars with a specific term. When the customers pull down the IP, is, based on when their design is needing to integrate that IP into the design. Over time, we expect that IP op margin is slightly below our corporate margin, and what you're seeing is what we've always called lumpy. You're able to see what lumpy looks like now with our new segment reporting. The expectation hasn't changed, and as we're looking out, we're seeing customers deep into their designs, and we understand the timing of when the IP would be pulled down. We feel strongly about that business, plus it's an incredible strategic asset for us to be so deeply involved and engaged in our customers' design. We've got strong view of... a positive view on that op margin. For Software Integrity, we've talked about, we've been focused on improving the margins in that business as we scale the business, and you're seeing some of the pull-through for that in the Q3 timeframe. Thanks, Shelagh. Thank you. We'll take our next question from Joshua Tilton with Wolfe Research. Hey, guys. Thanks for taking my questions. First, Aart, I guess, not I guess, but you'll definitely be missed, and congrats, Sassine, on, on the new role. It's not like I'm completely disappearing, right? Just to be clear. Thanks, Joshua. Miss more your voice on these earnings calls. It will, it will, it will definitely. Oh, yeah. I guess, like, my first question is just it seems like as of January, we're going to have a bit of a new regime in place. Maybe what are some of the things you can either do differently or just some levers that you feel that you could pull, to maybe drive some meaningful margin expansion, in the model come next year? Joshua, you know, I've been part of this company for 25 years, and the last three years, it's really been the start of what we call, like, a momentum journey, and we'll continue that pace of the journey moving forward. What Aart and I, when I was appointed to COO and then later President, we really set out three vectors as priority for the company. The first one is focused on the growth ambition. The second one is scaling and how do we scale efficiently as a company. Three, technology, leadership and innovation. And if you look at the results, they're really amazing. Over that period of time, we were able to grow revenue 17% CAGR, 700 basis point in non-GAAP operating margin, and 26% CAGR, EPS. Doing all of this while pioneering industry first technologies like the AI solutions that we are talking about, plus 3DIC from a multi-die, both IP and the design tools, et cetera, et cetera. As we look ahead, January 1st, as you commented, it's just a continuity of that pace at a time where the market, the semiconductor chip activity is so exciting, driven by the AI demand that requires more compute, either data center, cloud or edge, as well as everything going smart. Smart Everything in, in a car, in a home, in the industry, et cetera. It's, it's really continuing that pace of momentum we created on all three vectors. I would add that we're committed to both short and long-term operating margin improvement. That's what you're seeing, the improvement in the H2 of the year. We of course, will guide 2024 next quarter, but our long-term guide is at least 100 basis points improvement a year. We're, we're committed to that. Super helpful. I think just a quick follow-up to that talk track. You know, when you guys started buying up all these SIG assets, I think, the bullish take was, you know, we have this portion of the business that's growing a lot faster than the core EDA, and we could see this nice mix shift effect as SIG becomes a bigger piece of the total pie. I guess, how do we think about when, as from an investor perspective, we should kind of expect SIG growth to be back above the corporate average? Like, maybe help us out with a little color there. You know, the thesis behind SIG remains very strong, which is software quality and security. Actually, right now, you can argue, and the, the future is, is as strong or stronger with AI-generated code and the need for any developer to ensure that it's secure software that are using in, in their product. What happened over the last 12 months or so is not unique to Synopsys, as you're seeing it in the industry, especially at the, the, the software enterprise industry, is a slowdown, and that headwind, is really what you're seeing right now. As Shelagh mentioned, even though we're not speaking about long-term projection, and guidance for any part of the business, but, we are... Last quarter, if you recall, we said we'll be at the lower end of 15%-20%, and now it will be, slightly below, that number. It's not due to the portfolio or the execution, it's truly the headwind we're facing in the market. Makes sense. Thanks, guys. Thank you. Thank you. We'll take our next question from Joe Vruwink with Baird. Great, and, you know, big congrats to Sassine and Aart. I maybe wanted to start, just Aart, in, in your opening comments, the three sources of monetizing AI, you know, AI chips and that market opportunity. That's more market growth for customers, your AI products, that's wallet share for Synopsys, and then how you can employ AI internally. I take that as meaning higher margins. I guess when you just add all of those things together, can you maybe comment on how it could start to influence your long-term financial framework? Because a lot of these things were certainly early days or, or not as present, you know, back in 2021 when the framework was first debuted. Well, you know, you, you have our basic, financial outlook because we have communicated that we're focusing on number one growth and continued gradual improvement of operating margin. In many ways, this is against a backdrop that is fantastically exciting because there's going to be a wave of, end users, and I mean with that, you know, systems companies that all want to have AI, that all want to have chips that are way faster, way lower power, way, way more data. In other words, you know, the, the entire industry around us will be unhappy with semiconductors because they want more. There is nothing better than that because that is what, in the early days, drove the whole, Moore's Law at super high growth, and we have a similar feel going on right now. You may say, "Well, but is the technology not limited?" Well, no, it's not. What has changed is that the architectures are all changing, and that the ability to bring chips immensely close together, including stacking them vertically, is now suddenly opening up. Still difficult, still expensive, but, you know, that's what FinFETs were before, too, and then suddenly, out of nowhere, there were over 10 generations of it. I think this is exactly the space that we've entered. That's another way of saying design is going to become more complex, more engineers are needed, and given that, you know, the world's supply of engineers is somewhat limited, more automation is the only answer to solve this. Again, not any different than in the 1980s, 1990s, 2000s, and we all feel this drive because the notion of Smart Everything has shown itself as relevant. Now, a little portion of that is, well, how smart are we on the inside? You know, there's a lot that we can learn, and obviously, anything that we can automate or accelerate in our processes directly goes to the bottom line. At that point in time, Sassine's job is to figure out how much of that money to the bottom line goes directly back into AI research, right? That circle is very active. Okay. That's, that's all great. I wanted to go back, Jason asked about the, the renewal anecdote. I, I think that's a pretty interesting one. I, I guess my question is the, the 20%, is that pretty typical or emblematic of what place and route has been seeing so far? Maybe if it is, how do you see renewals evolving as customers get more experience, more proof points on things like test, your new AI verification, analog, kind of the, the full Synopsys.ai suite? What, what could that mean for a typical renewal? Yeah. In, in the early stages of AI, what the customers were struggling with were two things: One, I may not have enough compute, and two, I may not have enough licenses, EDA licenses. On the compute side, there are multiple ways that can be addressed, but most of our customers figured it out given the value that they were able to see. On the EDA side, the reason we started with project-based, we were really trying to figure out with the customers, what's the combination of number of licenses needed for an AI job? Because AI, it's pulling far more licenses of the technology that is under the hood compared to a engineering individual engineer effort. After we learned from that experimentation, let's call it around 2020, and customers wanting to scale it up, we started providing it as part of the subscription license in order to enable broader and easier adoption for the customer. With that came monetization to Synopsys. As I said, incremental monetization on two sides: more selling of the licenses, plus selling the AI technology as well. We have now actually many, still early stages, though, when I say many in terms of renewals. Remember, those are three-year cycles of renewals, and 2020 was just around the corner in terms of renewal cycle. We have many customers that they have gone through renewing their subscription license with Synopsys and added more technology that's pulling and the AI license. Great. Thank you all. Thank you, Joe. We'll take our next question from Vivek Arya with Bank of America Securities. Thank you, and best wishes to both Aart and Sassine on your new roles. Thank you. Thank you. Welcome. I had a near and a longer term question. On the near term, Design IP, when I look here today, if the model is right, your sales are basically flattish so far this year, I think maybe up 1%. I'm curious why is it well below your long-term growth expectations? Then when can we see this business get towards your target, which I think is to grow it kind of on a mid-teens annual basis? It is a lumpy business. As I described before, the, you know, the contracts we sign with the customers, we have a term and a dollar amount, and then the timing of those pull downs is really based on customer design. We're, we're confident in our long-term growth in that business because of the, you know, contracts we have signed with customers. Vivek, it is lumpy because it's really dependent. We're delivering IP all the time, constantly refreshing and delivering new IP blocks, and then it's really the pull downs are based on the customer design schedule. ... and we see robust chip activity, and we expect, customers, pull downs over a near-term horizon. Right. For my follow-up, I'm trying to think of what is the right way to think about your sales growth for the next two to three years. Can it stay mid-teens? Will it decelerate, right, to low double digit? Will it accelerate? Because AI is growing, but that's only 10% of your sales. Is that really enough to help Synopsys continue to grow at this mid-teens pace? Because when I look at a lot of the other parts of SEMIs, right, whether it's consumer or, you know, parts of industrial or traditional data center, they have really slowed down. I'm curious, is this AI enough to help Synopsys continue to grow its sales at kind of this mid-teen space over the next two to three years? Thank you. Just one comment, Vivek. You're asking, of course, the question that you should ask at the end of Q4, right? That's when we give guidance for the coming year. At the same time, overall, as we mentioned, we are in a market that we perceive as strong for us. We don't see any big changes. From year to year, of course, there's variability, but too early to really talk about that. Fundamentally, you know, what we said in preamble is that fundamentally, we have a degree of momentum that shows us that we're in a very strong business at a good time. I wouldn't think that there are any major changes. At the same time, again, we're declining too far out guidance here. Right. without giving guidance, Aart, I guess what I'm curious about is your insights on the growth in the business, excluding AI, because you gave a $500 million- Oh! number over the last month. Sure, sure. Your total- Yeah, yeah. Okay, a good point. Sorry, I didn't catch that. You know, outside of AI, the business is, is just strong across the board. You know, we talked earlier about IP. You know, the, these agreements that we made over the last quarter are very powerful for a long period of time, and they establish us as a provider that is, one of necessity for foundries to be successful. Remember, for, for foundry to be successful with a new node, it takes fundamentally four things. One, you have to have, of course, the technology. That's their job. Second, you need to have the capacity. Third, the EDA tools, which turns out we are always on time. Fourth, you need the collection of IP ready to go, because otherwise, the end users can't do design. The fact that we have strong agreements to provide this to the leading foundries in the world, is fantastic, and that gives us a degree of stability, but also potential further growth. That is very, very good. Thank you. We'll take our next question from Ruben Roy with Stifel. Thank you, and my congrats as well to Aart and to Sassine. Aart, I hope we get to see you playing the guitar more going forward from here. I, I wait to see you at the gig. You'll see me there, definitely. Sassine, I wanted to ask on AI as well, around the sort of how you're viewing the pervasiveness of AI. Aart talked about the $100 billion market potentially in AI chips by the end of the decade and, you know, 10% of a $1 trillion semiconductor market. Early days, but do you think for now that AI embedded tools are slated, you know, better for a certain portion of semiconductor design market? You know, clearly, Generative AI as a design helper or mechanism, you know, can be pervasive across the entire gamut of semiconductor, I would think. You know, for now, is, is that the right way to think about it, is this kind of large designs with very complicated place and route, or do you think it'll be more pervasive than that? You know, it, it will be more pervasive than that, but it, it will definitely be, in the stages of the design. If you think of the design as, three stages, there is the front end of the design, then there is the implementation/optimization of the design, and the sign-off. Where we started with DSO.ai and is in the physical implementation, because of the space of optimization is so large, it was such a perfect opportunity for an AI system to look at that large space of optimization and find the right parameters to, to, tune, and then give you the, the most optimized, physical implementation. As we expand into test, for example, and reducing the test pattern or verification, improving your coverage, analog mixed signal, it's a whole other place where there is plenty of opportunity to innovate in that domain, and you go into manufacturing. They're all prime and can leverage AI for both productivity as well as the quality of the result that you get. Aart mentioned as well in his script as three stages of design assistance, design exploration, and design generation. I want to say some of those are ambitious, meaning this is where we can see the technology heading in the next one, two years at various level of R&D in some cases, and customer discussions of where do they see, the high impact as well as where do we see the technology available today from AI models, et cetera, et cetera. And it, you know, you can open up the door to how do you protect your IP, the customer IP, how does the system learn? The opportunity is definitely in early stages in terms of impact of AI overall on the chip design Very helpful. You know, if I may add something, because I, I, I love what Sassine just has said in terms of this opportunity. It is important to understand that what we have done is we started actually with the single hardest problem, which is all the stuff that sits before tape-out. Tape-out is when the design is done, and it gets sent to manufacturing. Well, the one thing you don't want to happen is any errors in that. So as you add more and more and more detail, you're coming to this notion of the absolute necessity to be as close as you can to zero errors. That's why Sassine mentioned not only the design, but also the, the verification steps, the sign-off steps, and we have integrated all of those under our AI. I think it's gonna take a long time before many of the other techniques get close to that. We are gonna, of course, put those around. it broadens our opportunity space, as Sassine has said, but the core of our pioneering was really, we can do it and get correct chips out. that is challenging. Yeah, it's a very interesting discussion. Thanks for all the detail, guys. If I could ask what I hope is a quick follow-up. Some of your semiconductor customers have started to show their own accelerated compute platforms as platforms for EDA tools and, and, you know, in those demonstrations, more efficient than your current standard server farms running EDA. What's your feeling on that? Y- do you view that, obviously early days, but as an additional acceler- accelerant to EDA use or semiconductor design activity out there as, as the overall productivity could get faster as we put some of these new systems in place, you know, for your tools? You're right. It's the right observation. Think of it as another tool that you can use to accelerate a workload. We were primarily CPU, then we introduced some GPU acceleration in a number of simulation functions and verification and some other methods. Yeah, Ruben, you can think of it that way. Got it. Thank you very much. Thank you. As a reminder, everyone, please limit yourself to one question. We'll take our next question from Jay Vleeschhouwer with Griffin Securities. Good. Thank you. Aart, first, I've always enjoyed our, our more than 100 quarters of dialogue, and Sassine, I'm sure you'll look forward to another 100 quarters of multi-part questions on the conference call. But, for the two of you, let me ask a product roadmap question, and it does relate to AI. As you may recall from your last analyst meeting back in 2019, in answer to a question at the time, sorry, answer to a question at the time about what you thought the longevity or useful life of your new data architecture or new platform might be, having just introduced, you know, Fusion on top of it and DC NXT, for example, on top of it, you answered about a decade. I know that was an approximation, but the question is. Do you think that AI, as you embed it in your own products, extends that useful life of that architecture that you introduced a few years ago? Might it, on the other hand, require you to accelerate a rebuilding of the architecture as you completed a number of years ago? You know, Jay, excellent question, and I remember that discussion as well. When we introduced NDM at the time, if you remember, for our digital platform data model, it was around the 2015 timeframe. When you look at the decade, it's right around the corner. It, we, we continue, and this, this was really the, the primary foundation to build Fusion, where you bring PrimeTime, Fusion Compiler, StarRC, et cetera, the whole digital platform on one unified data model that is helping us accelerate our innovation pace and rhythm, because tools are connected, and we're able to move much faster in delivering a new technology, new products. As you can imagine, the team is constantly looking, is there a more efficient new data model that we can build on? You mentioned the 2019 investor day. Maybe I'll spill the beans. We will have, hopefully, in the H1 of 2024, it will be great timing to talk about how we see the future, given all the very exciting areas of technology, innovation, and the market around us. I'll take our next- What he means is an investor day. What did I say? Investor day? You didn't say an investor day at that time. That's what you meant, right? Oh, okay. Yeah, investor day. Sorry, I was too excited. Thank you. As we'll take our next question from Charles Shi with Needham. Hey, thank you for squeezing me in, and congrats to Aart. It's really been my great pleasure and honor, actually, to work with the luminary of the EDA and semiconductor industry as you are. Also congrats- I'm blushing. Yeah, thanks. Congrats to Sassine as well. Looking forward to, working with you, in the future. Maybe my question, wanted to, ask again on the IP revenue. Seems like, so far this year, it's been tracking to, like, single-digit growth this year. It doesn't sound too right, because your long-term guidance is kind of like in the mid-teens. Unless we are you expecting we get a big bump in Q4, or we're gonna be tracking the low, long, that long-term guidance? Maybe next year we should expect some of above the long-term guidance kind of growth. That will be my first question. Thank you. Yeah. Thanks for the question. Yeah, we do anticipate a very strong Q4. Our model that we have, we think is well intact, and that's a long-term model. When you look to the quarter and quarter variability, we don't as much manage it in the 90-day increments. We're managing it at the full year and 12-month increments, and we do expect a strong Q4 in IP. We'll take our next question from Gianmarco Conti with Deutsche Bank. Yeah, Hi, Aart, Sassine, Shelagh. Thanks for taking my questions, and congrats on yet another strong quarter, and to Sassine. Perhaps starting with SIG, could you explain whether the new go-to-market strategy is bearing some fruits? Exactly, I know you've mentioned this before, but maybe kind of can go a little bit more into detail into what exactly happened this quarter with regards to the marginal slowdown. Is this simply part of the macro demand that you have previously flagged, or is there something else in the mix? Conversely, what is driving the high margin for this division right now? Thank you. Yeah, we, we set out two priorities for SIG about a year and a half, two years ago. One is building out our Polaris platform, which is an integrated SaaS, which is the static and dynamic software composition analysis, and it's a cloud native, cloud-ready system. So from a go-to-market point of view, we're still in a transition phase, transitioning our customers to Polaris, while we're selling Coverity, Black Duck, et cetera, all the other point products that they can be primarily used on-prem. So that's from a technology platform point of view. From a go-to-market standpoint, actually, we've done a fairly good job in putting the right investments. How much do we do direct? How much do we do through distribution? And we're still on that journey of evolving our go-to-market. Where we're seeing difficulties right now is the negotiation with the customers. Given the headwind, they're ending up being a shorter renewal and taking longer to close. That's really the more-- the impact we're seeing. Not just from a value, market share, et cetera, et cetera standpoint, it's just the budget is tighter in particular for our enterprise customers. Just to comment on the operating margin, we're committed to improving operating margin. We had set out to do that this year to improve year-over-year, and we feel well on path to that. Obviously, the strong results in Q3 give us confidence on the full year. Operator, we'll take one more question. We'll take our final question from Blair Abernethy with Rosenblatt. Well, thanks very much, and let me offer my congratulations on the transition as well, gentlemen. Just on the IP business, I'm wondering if you can give us a sense of where you're seeing, you know, the biggest opportunity over the next, say, three to five years. Is it, you know, 3D multi-die interconnects? Is it AI chip Design IP? Just sort of how are you thinking about, you know, your investments in this segment? You know, on, on questionnaires, one would feel I'm all of the above. Meaning that, you know, the, the continuation of, of technology development is still very fast, even for individual chips. Therefore, with those come, come new speeds, new bandwidth, and constant new demands. You're absolutely right to throw in the, the, the, the 3D aspects, because one of my perspectives on that, it is precisely the fact that 3D has improved dramatically in terms of the connectivity, both in number of spin counts and the speed of, of on the pins, and the decrease of energy to switch a pin that actually opens that domain for a decade of, of success. The fact that AI is in the midst of that is what's a little bit different about AI processors is just the bandwidth and the enormous amount of data that needs to constantly, in many cases, dynamically be treated, while the car is driving, so to speak. So all of these things are wonderful for our fields because that says, well, do a lot better. While the word better, of course, has many variations, we all know that means that there's more design happening and more new chips, more differentiation among the end customers among themselves. So these are positive words in our field for sure. Thank you so much all. Look forward to talking with you over, over the coming days. With that, I guess we close the call. Thank you for your attention. For those of you that will connect with us later on today, we're ready to talk to you. Again, have a good rest of the day. Thank you. That concludes today's presentation. Thank you for your participation, and you may now disconnect.