00:00 Speaker A
There is an insatiable demand for semiconductors and chips. Because if we envision a future world in which cars, drones, robots, etc. will require increasingly sophisticated silicon rather than traditional sensors, smaller semiconductors, and more sophisticated semiconductor chips. And these systems are powered by AI. Well, the design of these systems creates significant opportunities for many companies.
00:41 Speaker B
right. So there’s a fundamental reason behind why we’re pushing these investments.
00:49 Speaker A
That’s exactly right. Because, as you can see, cutting-edge semiconductor chips are in a period of tremendous demand. Now, if you look at the design of these systems, whether it’s an EV or a robot, they’re complex engineering, design. So it’s also a great opportunity. For example, for a company like Synopsys, the acquisition of Ansys dramatically expanded our customer base. Given the complexity of mechanical, thermal, fluidic, and other electronics, moving from physical prototypes of products to more digital twins of product design is an exciting opportunity.
01:34 Speaker B
Nvidia is an investor in Synopsys. Now, you’re a partner with them and have a long-standing customer relationship. But has that changed in terms of how you do business and how you sell? Has there been any impact on that?
01:57 Speaker A
yes. So, historically, the relationship between Synopsys and Nvidia has been at the chip design level. Almost every chip Nvidia designs uses Synopsys, the entire Synopsys portfolio. Nvidia began expanding its portfolio from chips to systems, data centers, and various applications. Well, the opportunity that Nvidia sees with the new Synopsys with Ansys is how Nvidia creates future solutions at the system level. So today, Synopsys is reselling Nvidia Omniverse, a system-level design environment. This is because there are important channels through which Synopsys is involved in some way in every engineering effort. Well, another part of the partnership is GPU acceleration. It would take forever for AI to simulate these complex simulations, and with GPU acceleration we were able to reduce that time from months to days to hours. This is another part of our relationship and an opportunity.
