Vivek Arya : Thanks for taking my question. I’m probably nitpicking here, but if I go over the last few years, you were able to raise full year sales outlook almost consistently every quarter. And even when I go to the last call, there was a statement about steady growth throughout the year. That’s why I find it surprising, you’re not raising your outlook for the year? I mean 14%, 15% is obviously still very impressive. But what is different or do you think, between this year versus the last few years in terms of how you saw steady upside throughout the year, but you’re not seeing it so far this year.
Aart de Geus : Well, let me just remind you that last quarter, many of you commented that they were surprised that we do 14% to 15% given the uncertainty in the market. I think where we stand right now is that we have a solid understanding of what our customers are doing. — we all understand that there’s still some open questions on the market, but it feels at least in our domain that we were relatively correct in estimating what would be reasonable to shoot for, for this year. And so at this point in time, we don’t see a need to change those numbers. And it’s almost impossible to compare one year to another because all the years are so different. And — but right now, I think we’re on a really good track.
Vivek Arya : Got it. And then as the cost to move to more advanced nodes becomes expensive, is that a positive or a headwind to your sales growth? Does it mean fewer design starts because it’s very expensive to do three-nanometer or two-nanometer design, but then maybe they become more tool intensive. So I’m just curious, how is it netting out for Synopsys?
Aart de Geus : Well, for starters, I don’t think that there are fewer design starts. I think the race is very much on. Secondly, we’ve always believed that complexity is a good thing for us because we are an enabler, and I saw and in all of the people developing the new technologies. But hopefully, they stand at least a little bit of all of us to the fact that we have learned to use massive number of transistors. And I think we have now a fabulous new horizon, which is going from one to multiple chips that are in very close proximity is actually a technology feat in itself. And we’re in the midst of that, and it is really exciting that a number of the top leaders in this field are doing production design with us already. And so this is active learning, and so I’m not worried that it’s going to get in the way on the contrary, I think.
And I’m on record of having said many times now that a whole new age of systemic complexity has opened up and it retains one characteristic from the past, which is there’s unbelievable exponential ambition formulated by Gordon more many years ago. Now in a completely different context absolutely continues. The race is on, there’s new opportunities. So I want to almost say, bring it on.
Vivek Arya : Thank you.
Aart de Geus : Thank you.
Operator: We’ll take our next question from Ruben Roy with Stifel.
Ruben Roy : Thank you. I had a follow-up on the DSO. A question that was asked at the beginning part of the Q&A. And I guess the first part of my question is in terms of implementation of the tool, can you talk a little bit about how your customers guide to see the 100 commercial pays. But I’m wondering about how customers are using the tool? Is it more a cloud-based implementation that your then I have a quick follow-up following that answer. Thank you.
Aart de Geus : Great question. Actually, it’s both. Remember, though, that the most advanced customers, the biggest ones have themselves enormous clouds. But it’s interesting, even there, we see a number of people that say, well, what it had way more compute for a couple of weeks. Could you still better? And the very fact that they are experimenting with that is very exciting because you can still do better. But we have also a number of customers that are now really driving towards wanting to move their company to more cloud-based computation. And we’re completely capable and on top of running it in those circumstances. So I think we’ll continue to see both, but overall, it’s going to be spreading among more and more customers. There’s no doubt about that.
Ruben Roy : Right. Okay. And the follow-up to that is the beauty of AI and Generative AI, we’ve been hearing a lot about it, obviously, over the last few weeks and months is the concept of learning as the systems get more information. And so I would think that, that would tend to mean that as we move forward here and the system gets better on learning, whether it’s fiscal layout or improving some of the sensification that you talked about, that it should accelerate in use cases. Is that the right way to think about DSO.ai?
Aart de Geus : It’s absolutely a good way to think about it because you’re absolutely right. When a product can essentially improve itself over time, what is there to find negative about that? That is great. The results do get better. But generally, it’s not only the product that’s getting better. It is also the product understanding of the specific design that’s working on getting better. And we often forget that, well, a lot of people talk about, is this new design we’re doing and new design we’re doing. In fact, there’s many of these signs are derivatives of already existing designs. And we have fantastic evidence of demonstrating that when DSO.ai was used on an earlier version that it has a lot of stuff that it can learn from that version and directly apply to the next incarnation of the chip.
And that includes, by the way, if that chip needs to go to a different silicon technology or if that chip gets a few other additional blocks to let’s say, personalize it to a different customer of the customer. And I think there is a lot of potential in all of these things to still do way, way, way better, but the advances are remarkable. And we’re tracking this, and we see quarter-by-quarter new breakthroughs in many things. And that’s absolutely exciting.
Ruben Roy : Appreciate that detail, Aart. Thanks.
Aart de Geus : You’re welcome. Thank you.
Operator: We’ll take our next question from Gianni Conti with Deutsche Bank.
Giani Conti : Yeah. Hi, there. And thank you for taking my questions. So maybe starting with FIG. Could you maybe share some more color on its performance this quarter and whether you’ve seen any new wins versus backdrop from clients pushing away maybe some projects that were in the pipeline previously. I’d imagine the professional services arm and maybe some of those initial cities would be those are suffering a little bit more. However, I mean, it’s still great to see that growth is higher from our breakdown as well as margin improvement. So maybe just give me a a little sense of how is that development in terms of projects? And then I’ll ask a follow-up after. Thank you.
Aart de Geus : Sure. Well, in any case, there are always a couple of dimensions to the progress because what has been interesting, we have invested now for a few years in a platform that brings multiple tools together. And the reason this is important is that security problems are not simple to diagnosed, and there are many different types of problems. And increasingly, what the people would want to have that are in charge of security, so more top-down in the company is an overview of which what gets caught where and how do you bring these diagnostics together to have a better assessment of the risks that they have to manage. And so the indirect impact on us who is doing this better and better is the fact that we’re also seeing that our customers are starting to increasingly buy multiple products from us rather than initially buying one that that they may use for a while.
So that is the side effect essentially of ourselves, providing more systemic complexity assessment than before. At the same time, the normal business continues as mentioned in the economic surroundings, what we see essentially is that the levels of signatures needed to close the deal takes a little bit longer. But overall, there’s no doubt that this is an area that continues to grow and has still a lot of potential because a lot of customers are barely at stage one of automating this. And our technology progress is actually quite strong. And so we’re looking at growing between 15% and 20% this year, which is exactly on the target that we had told you before. And it’s exciting. It’s close to 10% of Synopsys. And with a little luck, we will pass $0.5 billion mark pretty soon.
Giani Conti : Great. That was really helpful. My follow-up would be, maybe on DSO.ai. Could you maybe talk a little bit about the training time for existing engineers using the new tool that are only going in new design. Is it time consuming? Or are they using pretty much the same GUI. And also maybe if you could just share a little bit on how does that compare to competition such as to say. It seems like you guys are both doing sort of like a race towards capturing the most amount of the market, and it seems to be a great growth opportunity. So maybe yeah, it’s basically two questions in one about training time and and using same interface dry versus competition as well? Thank you.
Aart de Geus : Sure. Well, on training, of course, there are two types of training, right? There’s training of the tool, this training of the user. And I must say, I have personally been surprised because initially, when we had these fantastic results in early 2020. I thought, okay, well, that’s great, but it’s going to take a while before they adopt it. But the results were so good that people actually couldn’t resist adopting it even not having fully appreciated what it would take to do things, and of course, our own AEs, as Jay mentioned earlier, we are well trained to help them. But initially, we didn’t do it with too many customers. And so that first year, year and half years, we had a limited set of really advanced customers, and we follow the same recipe, whoever runs fast is with us, we will run fast with them.
And so the training has never made it to be a real issue in the discussions we’ve had. Now that doesn’t mean that this is just super easy. It means that I think we are well equipped to take the design processes that our customers have, which we, by the way, know very well and adopt the tool to it and modifies likely the process for the tool. So I think we’ve done well. It’s hard for me to compare to competition, and it always feels like difficult to be objective about that. But I would say that we have the benefit of getting fantastic results already a number of years ago. And we are very, very rapidly moving to next generations of our tool and solution — and the very fact that we are now well over 100 production designs I should tell you that this is not driving with training wheels, so to speak, this bike is going down the hill at high speed has only kids we dare to do.
And I think we will continue to see excellent results. And I think I had also mentioned in the preamble that we’ve broadened substantially the applicability not only in the digital space, but some of the parallel spaces of test and verification and also logic signal. And so these are broad, open areas of opportunity for us.
Giani Conti : Great. Thank you. Appreciate it.
Aart de Geus : You’re welcome.
Operator: We’ll take our next question from Blair Abernethy with Rosenblatt Securities.
Blair Abernethy : Thank you. And nice results. I just want to follow up with you. So DSO.ai question from a Synopsys perspective, is the margin opportunity — is it similar to your core EDA tools? Do you have to put more resources to get this product in the market and ramp it? Or is it along the same lines as your core business?
Aart de Geus : It may be somewhat simplistic terms. I would say when you suddenly have a step that does work in third of the time and gets you another 10% or so better speed and lower power. Margin issues are not really the driver. It’s more like, okay, can they find the budget to keep moving here. And I don’t want to be too light about a statement like that because we work with people for many, many years. And it is very important that we further in ability for our customers to adopt be successful themselves in good and tougher times. But overall, I think there’s no question. These are technical advances of extremely high value, and they directly multiply the opportunity space that our customers have. So I think we will be okay.
