Why does Cadence matter, and how are you redefining its role in the industry?
Essentially, Cadence develops software that designs the chips powering much of today’s technology. These chips, which contain billions of transistors, are far too complex to design manually, so they rely on highly sophisticated computational software like what we provide. Our software is used to design a variety of chips—from digital and analog to memory chips—and almost every chip designed today involves Cadence’s tools in some form. Over the past decade, we have undergone a significant transformation, aligning ourselves with the top companies in the industry. The semiconductor market is ever-changing, and we have focused on staying relevant to the most influential players like NVIDIA, Qualcomm, and other leaders in AI and mobile technologies.
What are the key areas driving growth for Cadence right now, and where do you see the company heading?
Silicon is becoming more pervasive, and AI is a significant driver of that growth. While data centers are currently at the forefront of AI development, I see the next big phase as what I call "physical AI," which will integrate AI with cars, robots, and autonomous systems. This is just beginning with autonomous vehicles, but I believe industrial robots and other automation technologies will soon follow. We’re positioning ourselves to support this wave of innovation through our tools and R&D. Beyond that, I see life sciences as the third horizon for growth. We recently acquired a company that simulates molecules, which requires algorithms similar to those used in chip design. I believe AI will revolutionize the life sciences industry, combining biology with math and computer science to drive advancements in medicine. This transformation will likely take five to 10 years, but we are already preparing for it.
What does the future look like for these emerging technologies by 2027 and 2032?
In the short term, over the next two to three years, the demand for AI in data centers will continue to grow significantly, with some companies expecting a tenfold increase in their AI workloads. This phase represents what I call horizon one—focused primarily on AI for data centers, phones, and laptops. Between 2027 and 2032, I see horizon two coming into play, where AI and semiconductors will be crucial in autonomous systems, including cars and robots. Industrial robots, in particular, will become more widespread, and we’re already seeing this trend with companies like Amazon, which use robots extensively in their factories. Finally, within the next five to ten years, I expect life sciences to be a major area for AI applications, marking the start of horizon three. The integration of AI in this field will revolutionize how we approach medicine and biology.
In the context of Cadence, what keeps you up at night?
The main challenges for us revolve around three key areas: team, technology, and customers. While customers are crucial, without the right team and technology, we can’t deliver what our top clients expect. Talent is particularly important in the software business, where the contribution of a single top performer can be 10 to 100 times greater than the average employee. Maintaining an environment where the best talent can thrive is essential to our success.
How do you attract top talent, especially when competing with startups offering exciting missions and visions?
Talent attracts talent. One of the key factors in attracting and retaining top performers is having an organization where everyone is surrounded by high-caliber individuals. When you have A-players, they bring in other A-players, and that culture becomes self-sustaining. I constantly review my team to ensure we are bringing in and retaining the best. People come to work not only for the company but also for the people they collaborate with. It is similar to the camaraderie you see in the Marines—people fight for their team as much as for the larger mission. Compensation is another crucial factor. Startups often lure talent with promises of bigger paydays, but we offer competitive stock options to ensure that top performers are well-rewarded for their contributions. While compensation at large companies can be linear, we have made it a priority to offer nonlinear rewards through stock options for top talent.
How does Cadence stay at the forefront of innovation in a fragmented industry, and how do partnerships contribute to this?
The U.S. tech ecosystem—and now the global one—has evolved from vertical integration to horizontal specialization. We are best-in-class when it comes to design software, but we collaborate closely with partners like TSMC, which is a leader in manufacturing, and companies like NVIDIA, who excel in product design. This horizontal collaboration allows each partner to focus on what they do best.
We invest heavily in R&D—35 to 40 percent of our revenue is allocated to it, one of the highest among S&P 500 companies. Beyond internal innovation, partnerships are key. Our partnerships with companies like TSMC and Samsung Foundry allow us to work on solving the most pressing problems they face, meaning that we are not solving yesterday’s problems but rather anticipating future ones.
What major problems in the world do you believe Cadence can help solve in the next three to five years?
One major area where I believe we and our partners can have a huge impact is in reducing the power consumption of data centers. Data centers consume an enormous amount of energy, and we are already talking with companies about the possibility of placing nuclear power plants next to data centers to address this issue. The inefficiency in power consumption is stark—while a human brain can learn to drive in 20 hours using only 25 watts, AI systems currently require millions of times more power to perform the same task. Solving this issue is not only critical for the future of AI but also for the environment.
Another critical area is life sciences, where the drug development process takes far too long. It takes about 10 years to develop a drug, and that's because most of the work is still done through physical trials. In chip design, 99.9% of the work is done virtually, and we aim to bring that same level of efficiency to life sciences through our simulation and AI technologies.
What does the U.S. semiconductor ecosystem need to prioritize to keep accelerating?
Design is crucial because it funds manufacturing. The U.S. has maintained leadership in design, with companies like Apple, NVIDIA, and Google leading the way. If we lose our edge in design, no amount of manufacturing can compensate. The strength of U.S. companies lies in their ability to innovate at the design level, and this is something we need to protect and maintain.
As countries like India, China, and others push towards semiconductor manufacturing, it’s important to remind them that without strong design capabilities, there is nothing to manufacture. Manufacturing is important, but design is what drives the entire ecosystem. This focus on design must remain a priority for countries aiming to become major players in semiconductors, whether they are producing chips or using them in their own innovations.
How is the relationship between semiconductor and system companies evolving, and what impact will this have on the industry?
The semiconductor industry is merging with system companies, transforming the landscape. Companies like NVIDIA, which started as a semiconductor company, are now considered system companies. At the same time, major system companies like Apple, Google, Meta, and Microsoft have built large in-house silicon teams. These companies are now significant players in the semiconductor space, with 45% of our business at Cadence coming from system companies and 55% from traditional semiconductor companies like Microchip.
This shift is seen across industries. For example, Tesla and BYD are designing their own chips, and the amount of silicon in cars is skyrocketing. It is no longer just semiconductor companies driving innovation; system companies are now heavily involved in chip design. The industry is growing from both angles, and this evolution needs to be highlighted when discussing semiconductors and their future.
