The Synopsys CEO explains that the company is integrating AI throughout its products to manage the increasing complexity of chip and system design, especially following its acquisition of Ansys, which expands its capabilities in both electronic and physical engineering. He emphasizes that Synopsys’s core value lies in its deep expertise in physics and engineering, enabling faster, more efficient design cycles and addressing industry challenges despite market fluctuations.
The Synopsys CEO discusses the company’s recent focus, particularly its relationship with Nvidia and the acquisition of Ansys. He explains that the engineering complexity in both silicon (chip) design and intelligent, AI-infused systems is rapidly increasing. Synopsys is addressing this by integrating chip design with advanced physics simulation, enabling the creation of digital twins and co-designing electronics with their physical counterparts. This approach is crucial for managing the growing complexity and cost-effectiveness required in modern engineering.
With the Ansys acquisition, Synopsys has dramatically expanded its customer base, especially in industries like automotive, where over 90% of original equipment manufacturers (OEMs) now use their software for both electronic and physical design. The convergence of electronic and physical design is driven by the need to manage complex, AI-powered systems such as robots, cars, and drones. Synopsys’s combined portfolio allows customers to create virtual representations of these systems, streamlining the design process across multiple engineering domains.
The CEO addresses concerns about AI potentially disrupting traditional software development. He emphasizes that the true value of Synopsys’s products lies not just in the software code, but in the underlying physics, algorithms, and solver fidelity. For example, semiconductor companies invest heavily in chip development and must be certain of their designs before manufacturing. Synopsys uses AI throughout its products to automate workflows and enhance digitization, but the core differentiation remains their deep expertise in physics and engineering.
He also highlights the current challenges faced by customers, such as supply chain disruptions, logistics issues, and a shortage of skilled engineers. AI helps augment engineering teams and reduce costs by improving manufacturing yield, particularly in memory chip production. By integrating AI into every stage of the design and manufacturing process, Synopsys enables faster design cycles—reducing chip development timelines from 18–24 months to as little as 12 months—and helps customers achieve better yields and efficiency.
Finally, the CEO comments on recent market reactions and the long-term outlook for Synopsys. He argues that not all software companies should be treated the same, as engineering software is fundamentally different due to its reliance on physics and manufacturing expertise. Despite headwinds like slower growth in China due to export restrictions, Synopsys continues to see strong opportunities across various sectors. The company remains committed to double-digit growth in both electronic design automation (EDA) and intellectual property (IP), driven by the accelerating complexity and transformation in engineering.