Hi, I'm Prith Banerjee, senior vice president of innovation at Synopsys. I'm honored to be at Sachin Sahel's O Chak De Show. Enjoy.
Hello everyone and welcome back to the O Chak De Show, where Silicon Valley's first business, tech, and self-improvement podcast for teens, hosted by a teen, me. I'm Sachin Sahel. I'm a 19-year-old award-winning entrepreneur, podcaster, author, and student from the Bay Area, and I interview remarkable and influential entrepreneurs, executives, investors, leaders, and inspiring individuals from all walks of life, so we can learn from their stories and level up ourselves. I'm also the co-founder and CMO of 3Doshas.com, a coaching company transforming lives with 3 Doshas ancient science from India. And the purpose of this show is to inspire you to go for it, which is what the Punjabi word O Chak De means, which is the word my podcast merch is, what I'm wearing right now. Today, our very special guest is Dr. Prith Banerjee, who is the senior vice president of the Synopsys Innovation Group and is a member of the executive leadership team at Synopsys. Prith was the CTO of ANSYS, which was acquired by Synopsys for $35 billion, where he led the evolution of ANSYS technology and championed the company's next phase of innovation and growth. He's also ex-senior vice president of research and director at HP Labs, and he was Accenture's managing director of global technology R&D, and he also was Schneider Electric's EVP and CTO. So, before tech, Prith was a professor of electrical and computer engineering and the director of computational science and engineering at UIUC. He was also the dean of the College of Engineering at USC and the chairman of the Electrical and Computer Engineering Department at Northwestern University. He's also a serial entrepreneur and started a company called AccelChip, which was bought by Xilinx. And he holds a B.Tech in electronics engineering from IIT Kharagpur, where he was awarded the President's Gold Medal, and he also has an MS and PhD in electrical and computer engineering from UIUC. So, Prith, welcome to the O Chak De Show. How are you and what's new and exciting?
Thank you very much. I was so excited to come to your show, Sachin. I've heard it, seen it. Thank you very much. And so, today is a great day for Synopsys. We are celebrating our 40th anniversary. And we, as a leading company in the world of electronic design automation, IP, hardware acceleration, and simulation, I'm delighted to speak to your audience today. Thank you so much.
And I just want to say before we start with the interview, I really appreciate the opportunity. It's great to be here at the Synopsys headquarters in Sunnyvale at this beautiful studio. So, you're helping my dream stay alive, so I really appreciate it. Thank you so much for doing that. Let's start off with the first question. I want to take it all the way back. Can you talk about your teen years? What were you into? And what were you passionate about? And what drew you to tech and wanting to become a professor, entrepreneur, tech exec, board member, and more?
So, in my teen years, I grew up in Kolkata, India, and I went to Don Bosco School in Calcutta, Kolkata, and again, I was drawn into science and engineering, and I used to do science projects like kids do, and then I was fortunate to have gotten into IIT Kharagpur, Indian Institute of Technology Kharagpur. And my main thing that I want to talk to your audience about is in Kharagpur in the first year, you submit, I applied for this Jagadis Bose National Science Talent Scholarship, which is a very prestigious scholarship in West Bengal. And I participated in a science project that was to do an electronic flow meter. I mean, at the time, you have sort of water going through a pipe, right? And so, electronically, how can you measure it? And so, I used Bernoulli's principle and all that kind of stuff, and I was ranked first at JBNSTS. So, that really motivated me to go into science and engineering and all the wonderful things I've done in my life.
I find your career so cool because you started off as a professor, and then you went to tech. We're going to talk about that, but let's talk about what you're doing right now. You're currently the senior vice president of innovation at Synopsys, and you're a member of the ELT. Can you explain your role and responsibilities at Synopsys in a simple way for my teen audience?
Sure. So, Synopsys is the leading company for supporting our customers across disciplines in the world of electronic design automation and engineering simulation. We are a company of more than 9 billion in annual revenue. We have more than 30,000 employees. So, we have some absolutely amazing products, products that allow you to design electronic chips, products that allow you to design sort of automobiles or aerospace airplanes and so on, right? But that's today. So, we have amazing products for today. My role is to look in the future, 3 years, 5 years, 10 years into the future, and imagine what kinds of products our customers would need and what kind of products Synopsys would build in the future.
That's an amazing role. Honestly, innovation is one of my favorite words, actually, so it's cool that's what your role is exactly. I have a question about some of the companies you've worked at. You've been on a lot of iconic organizations, Synopsys, ANSYS, HP Labs, Accenture. Are there any patterns or lessons that stand out from working across so many different companies and cultures?
So, yeah, I've worked at, as you said, HP Labs, Schneider, ABB, Accenture, and so on, right? The main thing that I've done, these are large multinational companies. They have some absolutely amazing products. These companies like HP used to be a hundred billion-dollar company. ABB was a thirty-billion-dollar company. Schneider, a forty-billion-dollar company, right? But these are large companies, multinational. ABB was in Zurich in Switzerland. Schneider was in France. So, the thing that comes across is in these companies, whether they're in the US or in Switzerland or France, they're all trying to innovate. They're trying to create the next opportunity, trying to anticipate what it is the customers would need. And so, they're all looking for an organization like a CTO office, which would imagine the world out there, talk to customers, and build these new products. And innovators everywhere, whether it's in Switzerland or France or US, they're all the same. They are always passionate about the new thing. And that's what excites me about this new job at Synopsys.
I love it. Speaking about your job at Synopsys, what is the Innovation Group? And like, what does innovation truly mean to you, not just as like a buzzword, but in real day-to-day work?
So, for you and your audience to understand, let me kind of tell you about what Synopsys products enable, right? So, you are imagining a product like a car in the automotive world, or an airplane in the aerospace world, or a gas turbine, right? These products, it used to be all mechanical products in the past. But now, increasingly, they are what is called software-driven. So, software-driven vehicle, right? So, that Tesla car has a hundred million lines of code on that car, right? So, it's software-driven. Then it's silicon-enabled. So, there's a chip on which the software runs, right? And then it is AI-driven, right? So, all the latest work on AI, the agentic AI, it's all of it. So, three key parts: software-driven, silicon-designed, AI-enabled. So, we enable our customers in these different verticals, like automotive, aerospace, etc., to build these amazing chips, these electronic chips having a hundred billion transistors, a trillion transistors, right? Then the software that runs on the chip, and the software that runs on the chip to control the hardware, right? So, that you can do the autonomous driving cars, right? All the Waymo cars that you see here in San Francisco, right? Imagine the amount of automation that is there. The amount of compute that goes onto those chips and so on. So, how do you design and verify those chips, right? So, Synopsys allows our customers to design those electronic chips, to validate those chips on platforms like ZeBu and HAPS. And then, once you have those chips, you write the software, you can test the software interacting with the mechanical parts, the fluids parts, and so on, and then work inside the environment. So, we call ourselves as you can build a digital twin of that product in that environment before the product is even made into a prototype.
How cool is that? That's very exciting. I think I also found interesting how the way you got here was through ANSYS, which got acquired by Synopsys for $35 billion. You were the CTO there. What was that moment like for you when the whole acquisition happened and stuff? I'm just curious.
So, it was an absolutely amazing thing because at ANSYS, as the CTO, I was working on the system, the engineering simulation part, right? So, dealing with the physics of structures, physics of fluids, and so on. But we always missed the part, 'Hey, I'm building all these physical parts, but the physical part needs to interact with the software part that runs on the chips, right?' So, we were always partners with Synopsys, right? So, because of my work, we used to work very closely with Synopsys. But once the acquisition happened, we said, 'Wow, this dream of this intelligent product design can be now implemented.' And you asked the question about what does the Synopsys Innovation Group do? So, that group, my job is to look at the future, what kind of products should be designed in the future, drive our long-term technology strategy, talk to customers and partners about this vision, and engage in external thought leadership in conferences and talking to people like you to inspire the next generation of leaders in this amazing journey of Synopsys.
I love it. It's so amazing and I think innovation is just what it's kind of cool because your job is like you're the top person for what are we going to do and how we're going to do it and what are we going to build? So I find that really amazing. Another thing you talk about a lot is you talk about re-engineering engineering. What does this concept mean to you?
So what that means is, I mean, look at how a car was designed maybe say 20 years ago, right? It was just a mechanical car. I don't know if you have an old car in your garage, but it's a thing with a manual steering, a manual brake, a manual window, and everything was manual. Then the whole world became power windows as electronics, right? When you push that button, how do you think that that electronics works? Like there's a piece of software that is enabling this to work, right? So these products now have, as I say, software enabled. As I said, there are 100 million lines of code in the software. These things are getting incredibly complex, right? So in the past, you had a mechanical car, you ship the car, that's it. Then the car company, be it Ford or GM, had no clue where it landed, right? And if something, you couldn't do an upgrade on that car. But if it is a software product, as you know, you can do software upgrades. These products now have the ability because they're connected to the internet to do over-the-air updates. So you can ship a car with a level one autonomy, for example, right? Where that car has a capability to do sort of maybe cruise control, automatic driving, right? You say, 'I now want to enable it to do self-parking' without changing anything in the car, you now have the level two self-driving part. Then you say, 'I want to do fully autonomous.' So essentially the same car, but over the years, the car is getting better and better. And not only that, this car, depending on how you're driving it, right? The car is adapting and it's learning more about it. So it's an incredibly complex world of products, right? It is, as I said, software enabled, AI driven, and silicon designed. Now, it used to be the case that a new car could happen every maybe five or six years. That is now saying, 'Hey, six years is too long. We should do a new car every two years.' Oh, no, I need a new car every year. So the pace of innovation is getting faster and faster. And the complexity of these systems, right? If you look at just electronic chips, when I used to teach VLSI design at Illinois, it had maybe 10,000 transistors in it. Then it went to a million transistors, then 10 million transistors. Your dad, when he, I guess we are talking about your dad, right? Working at Intel, there were 100 million transistors, a billion transistors. These days you have 200 billion transistors in chips from say Nvidia. We are going to go to trillion transistors. Now you have a trillion transistor chip with 100 million lines of code on it, right? With all this AI power, it is so complex, right? The complexity is amazing and the pace of innovation is incredible. So now you look at an average engineering company, you have maybe 10,000 engineers. If you have to do that same job four times as fast, you need 40,000 engineers. If you have to do now this thing but 10 times more complex, you need 4 million engineers. You need 10 million years. I know you studied at San Jose State. These universities are not graduating students fast enough, right? So therefore, in order to solve this, you have to re-engineer engineering. Instead of having the engineering done with the traditional tools, with the linear thing saying, 'Oh, my pace of innovation is increasing, I need to hire more engineers. I need to do it more complex, hire more engineers.' Instead, leverage AI, and I'm sure your audience has heard about this concept of agents and agentic engineers and so on. So we at Synopsys have just announced this thing called the agentic AI workflow, a name called agent engineers, which is trademarked. The idea is that this agent engineer will act as an engineer, but the sort of low-level engineering jobs, right? So that the engineer like you, when you graduate, right? You will be able to work with these agentic engineers to do really complex workflows. And that's re-engineering engineering. Without that, you would not be able to do these really complex intelligent products.
Wow, it also sounds really cool. It's just say re-engineering engineering. I'm not that technical, but I do know a little bit, so I have to rewatch some of the video to understand everything you said, but I get what you're trying to say and I think it's really cool. AI, like you mentioned, is moving incredibly fast right now. From your perspective, what should young people understand about it? Both its opportunities and its responsibilities.
Absolutely. That's a great question. So the way AI works is you have to sort of train an AI model, right? And you look at sort of the foundational models like ChatGPT and so on, right? It looked at all the words in English language, all the poetry and so on. And now with AI, you can generate new things, right? So you can actually be an artist, right? We are talking about music and so on, right? So if you're a musician, you learn to play music and now you have to compose new music and so on. So in this new world, AI is your assistant and whatever job you do, you are now, you are a podcaster. You can be a much better podcaster with AI. I am an engineer. I can be a much better engineer with AI. People used to write programs in the past, right? Manually coding the programs in C or Python. Now people are using tools like Cursor or Claude and so on, right? And they're using it to be a lot more productive in the world of programming or in the world of chip design. Any field you pick, right? AI can be your assistant. So that's the good part. The bad part is what we have to be concerned about is as you are creating, suppose you are creating new music, right? We were talking about Indian classical music. I say, 'Hey, develop a new music that sounds like sitar, like Ravi Shankar, right?' And then it's created that and then you claim that to be your music. You are actually infringing the copyright of Ravi Shankar who created that music in the first place, right? Or you say, 'I want to draw this thing in a picture that looks like Picasso and so on, but it should look like me doing this.' You are infringing on Picasso's thing. So we have to figure out, right? The AI companies have to figure out, and there are discussions going on as to say, 'If you are using GenAI leveraging somebody else's things, right? How do you compensate? How do you take care of IP?' And this is a really interesting discussion. So we need to come up with governance mechanisms, accountability mechanisms, and make sure that it is safe, right? You should not do things because of it you create unsafe stuff, right? So you have to have the human in the loop to make sure that bad things don't happen through AI. But in general, it is a wonderful technology for your audience. You should look at it, but you should pay attention to AI governance, safety, and accountability.
