Gus Richard: Yes. Thanks for taking my question and congratulations on the results. On the Industrial Automation, you’ve got a partnership with NVIDIA on AI. And sort of one of the limiters to penetration is the lack of a VAR channel, having to have to work with people to implement this stuff. Does multimodal AI or AI in general sort of simplify the implementation? Can you simplify the programming implementation of robotics with that infusion of AI?
Greg Smith: Yes. So for sure, the great thing about AI; there are two primary benefits to AI. One is that it’s far easier to design a solution that is able to deal with variation, whether its part variation or location variation or other uncertainties that exist in normal manufacturing environments. The solutions end up being far more resilient, so that means that more people would be willing to adopt them. As I always say, people don’t want to put fragile things into production and AI will help make things more robust. The simplicity of developing things is definitely a huge benefit of AI. So the demonstration that we did at GTC was a pretty sophisticated visual inspection application. And because we were leveraging a really powerful AI stack from NVIDIA, we were able to put that together in less than two weeks.
It was a very fast turnaround to be able to build that solution. And we expect that both customers and customers and especially solution providers are going to be able to leverage that and create solutions to categories of problems that will help drive growth.
Gus Richard: Got it. Thanks. And then on the semi-test side, you’ve got sort of – it’s going to be a while before we get to 2-nanometers yields at 3, I don’t think we’re that great. And the AI accelerators are reticle limited. How are you seeing the expansion of use of chiplets sort of beyond AI accelerators and servers and FPGAs? Is that beginning to broaden out?
Greg Smith: Not really. I mean, well, one thing is that most of the advanced packaging capacity in the world has been consumed by the people who are doing cloud AI, high-performance computing. So there’s more demand than there is supply for it. So I think that’s limiting it to the markets that are willing to pay the most for the ability to do it. I think that it’s possible that chiplet technology will migrate out of high-performance computing potentially – I mean it could potentially migrate into some mobile applications. I think that’s going to be a relatively slow process because the price points are very, very different. And then I think for industrial and automotive AI applications, it’s likely to be a long time before you see chiplet technology in there because of the reliability and temperature range questions.
It’s a much more challenging environment to try and put packages. But that’s kind of my view. I think that there are people that have a more aggressive view in terms of where chiplets will go.
Gus Richard: Got it. Thanks so much.
Operator: Thank you. We have time for one last question. The next question comes from the line of Steve Barger with KeyBanc Capital Markets. Please go ahead
Steve Barger: Hey, thanks. I’ll be quick. Greg, you said share gain opportunities in HBM are good. Is that primarily due to you having capacity to support a fast-growing addressable market? Or is there something unique in your current or future testers that will make you a supplier of choice for some variations of HBM?
Greg Smith: I think it’s definitely the latter. So we believe we have a differentiated solution, both in terms of ability to support data rates out through HBM4 and also in terms of being able to use same platform across multiple insertions. So we think that we have an ability to deliver more cost-effective performance test of HBM, and we believe that we’re going to make some progress there.
Steve Barger: Understood. And for the large account channel in robotics, you said there’s a gestation time before revenue was this largest ever MiR order a function of work prior done to the pivot? Or did it come after? And then to your point about being more immune to cycles, is that just because large accounts are more likely to invest through cycles and are less swayed by near-term conditions?
Greg Smith: Yes. So let me take the large account question first. And I need to apologize to Brian because I didn’t answer his question before. So the largest order that we’ve ever gotten from MiR, it came from an automotive customer. And it is also our historically largest customer for MiR. By no coincidence, it’s also a significantly large customer for UR. So we have been selling them robots for a long time. The one thing that has happened since we established our large account effort is that we’ve been applying many of the strategic account management techniques that we’ve been using for decades in semiconductor test towards addressing those accounts and really organizing ourselves around the way that those large accounts acquire new equipment and also how to take care of the equipment that they have. So, I think it’s certainly an account that predated that effort, but I think our ability to serve that account has improved with this effort.
Steve Barger: And then just about being more immune to cycles, is that because large accounts will invest through cycles? And so that pivot will make you less cyclical yourself?
Greg Smith: I think actually, the large accounts may be the segment that will continue to be sensitive to end market conditions, because large accounts will work off of budgets. And if they don’t provide budgets for automation, then those purchases won’t happen. The thing that we’re really trying to do is make sure that we are adding enough new opportunities to drive growth even if end market conditions are weak. So a key part of this is being able to find and find and serve customers that have these problems. We have 95% of this market that is as yet unserved. So there is plenty of opportunity. And the key thing that we’re trying to do is to pick our shots, pick the specific industry verticals and the specific applications that are likely to be driving growth independent of the aggregate macro conditions.
Steve Barger: Understood. Thanks very much.
Operator: Thank you. Ladies and gentlemen, we have reached the end of question-and-answer session. I would now like to turn the floor over to Traci Tsuchiguchi for closing comments.
Traci Tsuchiguchi: Great. Thank you all for joining us this morning for our first quarter earnings call. We look forward to being in touch with you all as through the course of the quarter. Thank you. Good day.
Operator: Thank you. This concludes today’s teleconference. You may disconnect your lines at this time. Thank you for your participation.
