Thank you, John David, and the SIA for this splendid recognition. And thanks to all of you in the room for the years of teaching and, most importantly, the trust that I've received from so many of you over multiple decades. Thank you also to the video team that put this together, and most importantly, the people that were in the video. So meaningful. I'd like to recognize just half a dozen people. They all have two things in common: one is they have more skills and talent than I ever had, and secondly, without them, Synopsys would either not exist or certainly not be in the present state. So please hold your applause as I mention them. It is literally 40 years ago that synthesis appeared in the little R&D group ahead of General Electric, and then 18 months later, GE decides to get out of semiconductors and to lay us off. At that point in time, with two members of my team, Bill Krieger and David Gregory, we started to think on this idea of how do we turn layoff lemons into entrepreneurial lemonade. And somehow it succeeded because we talked Synopsys into letting us start Synopsys, initially under the name Optimal Solutions, and from there it was off to the races. The lesson I learned is that no matter how something is truly impossible, never omit to get the courage to try. And this industry has done this over and over and over again. Then about a year after Synopsys was founded, we were joined by Harvey Jones from Daisy Systems, and he became our president and then for a number of years CEO. What he brought was the commercial side, sales, marketing, and he had fantastic business acumen. Over the decades, I've come to appreciate more and more how much I have learned from him. Then early 90s, Chi-Foon Chan joined us from NEC. Many of you know him. He immediately proceeded to essentially scale the trust with our customers and actually did it with Diod, who will be speaking later, who was employee number eight of Synopsys. For a number of decades, Chi-Foon and I worked hand in hand to essentially create the heart and soul of Synopsys. The way I am today, a big piece of DNA is from him. Then many years later, we have another change. We have a new CEO, Sassine Ghazi. I've known him also for a long time, 25 years, and he exemplifies the fact that I mentioned earlier: skills and abilities well beyond my own. He is absolutely the perfect leader for our company, has my full support, and I am very curious to see where we will be in a few years. Let me zoom in a little further to the inner circle. Of course, I am blessed with two daughters that have become strong, independent, and caring women. This is all due to the one person in the middle of this, which is my wife, Esther. As so many of you know, people in our field, it's 24/7 in our roles. The pressure never ends, and there's always one more phone call to do. In many ways, she is the person that has held our family together, made it what it is today, and to great amazement, has managed to simultaneously have her own great career as professor of epidemiology at Stanford. So I am blessed. Thank you.
Now, so many of you in the last few months have asked me, 'Hey, Aart, now that you're no longer CEO, what do you do with all that free time?' What free time? I have a new quest. The quest is I would like to try to understand the systemic complexity of energy and climate. Now, that's not an easy task. It's like learning from a fire hose. And yet, I would love to share a couple of insights that I've gotten in the last few months, although, disclaimer in capital letters here: disclaimer is I'm learning. In everything I touch, there are like 10 or 100 things more that I should really know. My objective has been, whatever I see, simplify to the max to see if I can get to the essence of what matters. For the mathematicians in the room, that would be what are the eigenvectors that determine where this thing is going. In order to understand systemic complexity, it takes three things: understand what's connected to what and find if there are any feedback loops; two, what's big and what's small; and three, what's fast and what's slow. If you know that, you're already pretty close. For the climate, I use three lenses. The first lens is science. Science is truth. By the way, the advances in science have been fantastic in the last decades. The second ring around this lens is technomics. This is a term that I happened to introduce to our industry about 20 years ago, and it balances the fact that invention changes in technology need to always be mirrored in corresponding economic results that balance this out and make it survive. The third ring around this is people to politics to policies. I can share with you that that's going to be by far the hardest one. We all understand that. So let me very quickly summarize the simplest model I've been able to come up with. You'll understand it immediately. Energy is at the center. Energy has one great benefit, and the great benefit is standard of living. It has a big side effect: for most of the energy, it puts CO2 and some other gases in the atmosphere. CO2 becomes a warming blanket on Earth. Temperature goes up. Climate changes. Climate has a big impact on extreme weather. Extreme weather hammers standard of living. That's the feedback loop, the feed forward and feedback loop. In all of that, CO2 is actually pretty important. It behooves us to understand a little bit better. I found one graph that totally captured my attention. It's the density of CO2 for the last thousand years. You start a thousand years ago, and the density is 280 PPM, and essentially it doesn't change at all. Then 1800, Industrial Age, zip, zip, zip, zip, zip, zip, zip. It goes way up to 420 now. That captured my attention, but what really shocked me is when, by accident, using some PowerPoint, and many of you know I'm just inebriated by exponentials, I love them. I happen to have a mathematically perfect exponential, and I could just morph it on those years since 1800. The fit is astoundingly exact. You cannot see the difference. Now we know if there's one thing, exponentials are very powerful but also very dangerous. I personally cannot unsee this graph. So I would like to share with you two numbers today that I hope you will remember. One is one ton, and the other is a trillion tons. Let's start with the trillion tons. In 1800, there were two trillion tons of CO2 in the atmosphere. A trillion, by the way, is 10 with 12 zeros, and a ton is 1,000 kilograms. Two trillion in 1800. Today it's three trillion. The difference between the two, the one trillion, that's your first number. But there's a little more to that. Remember, it's sort of on this exponential thing. Of that one trillion put since then in the atmosphere, half was in the last 40 years. In other words, this is both big and fast. Those are dangerous conditions. Now let me give you a little bit more visceral number. I flew to Europe in the summer. One flight to go there, one ton. Back, two tons. Actually, I flew business class, multiply by three, six tons. It adds up pretty quickly. I didn't do the calculation for Jensen's plane, but okay. The fact is, if you have to remove the CO2 today, you can do it. It costs about $500 to $1,000. In other words, we're a long way off from a big problem. Let me just finish to close the feedback loop. There's a graph that shows extreme weather damage impact. I have it only for the US over the last 40 years, and lo and behold, it's a little noisy, it is an exponential too, and that exponential has now passed $1 billion per year. It is very clear we have a very urgent need for action and innovation. While talking about innovation, what industry could we role model against? How about the semiconductor industry? We've run this bouquet of exponentials like crazy, and I've always wondered how is it possible to sustain this. I think there are two things that our industry does so well: it is invent and improve. Invention is essentially find a new angle, find a discontinuity, and inject some exponential DNA into the problem. Improve, of course, is tune and polish and polish and polish, but it is fundamentally trying to achieve technomic viability. Can you build something of sufficient value so you can sell it, you can make money, and you can put the money back into invention? Let's take an example at the very beginning of the information age, our age: the transistor. You look at the picture of that thing, it clearly needs a lot of polishing and effort. Actually, that's exactly what the manufacturing people did, which is they pushed on yield, yield, yield, and made it smaller and smaller, and then area gradually became PPA all the way. It took 13 years since then for the next very big discontinuity, a fabulous one, incidentally propelled by Kilby and Noyce of all people, which is the transition to the integrated circuit. Take transistors and connect them in the same silicon. This is a very big discontinuity because connectivity is now in the game. Actually, I would propose to you that it is the very foundation of computation because from that moment on, software and silicon become part of the same coin. Now there have been many infusions since then. I don't have to mention them all, but SOI, copper, lithography breakthroughs, FinFETs, EDA. Did I just mention EDA? What was that? That company, yeah, Synopsys. Those guys, they were so damn lucky. They were so lucky. They have their synthesis thing, and it happens to be right between computer-aided design and electronic design automation. We just heard it: automation changed everything because it unleashed the digital design age. Today, looking back, we've probably together increased 10 million times the productivity. So what are the learnings from our industry? Well, there are two in my mind. One is that we have managed to grow systemic complexity with these multiplicative infusions while rigorously, rigorously sustaining technomic viability. So let's apply our lessons to the Industrial Age now. First thing we recognize: boy, they were really, really great at building systemic complexity as well, from engines to machines, automation, and then energy all over the place. They actually fulfilled a great mission. They augmented and scaled human muscle. That's a great addition or multiplication on the human being. But their technomic feedback loop is incomplete. There's no accountability for CO2, no sustainability for the one trillion they put in the air. This brings me to what's called the dual challenge. The challenge is that all of humanity, including especially now our industry, wants way more energy and way less climate change. That requires a massive, massive energy transition. Now it's exciting to see that most recently, just last few months, Amazon, Google, Microsoft, they've all made nuclear PPA commitments. PPA in that case stands for power purchase agreements. It's great because they have a zero carbon commitment going forward. They clearly have the need for computation, but also the ability to invest and pay. Most importantly, it activates a nuclear technomic market. But what I love most is it finally brings impatience into the game. This is us. This is our industry. We have no time for dilly-dallying. I can just see the day where some of those people meet with some people in Washington that say, 'Oh, it's so great what you're doing. In four years, the permitting will be ready for you.' This is more real than you know. So it's super high urgency, which brings the question: actually, what is the mission of our industry? If the Industrial Age literally augmented and scaled the human muscle, the information age mission is becoming very clear: it is to augment and scale the human brain. Can we do it well? Ask Jensen. I heard him the other day say, you know, he's already building intelligence factories. I hope they have no smokestack. But the fact is, what has been launched with this AI, software and silicon compute, is a fantastic coin that is spinning faster and faster. But the coin wants way more compute, which brings me back to us. There are some exponential breakthroughs needed. The good news is I think we have some very big ones already in hand. Remember I mentioned earlier the transistor going to the integrated circuit? Well, now what's happening is the integrated circuit is going to the multi-die, and the multi-die is also three-dimensional. To do that, there have been great advances in connectivity. We can literally now do hundreds of thousands of copper connections per square millimeter, which is about this big. So the coin will be spinning faster and faster. Everyone wants more compute. A lot of people want to actually spin the coin to actually use the AI, and that will demand enormous amounts of energy. Energy that we must assure comes about without CO2. That's just another way of saying that now silicon, software, and energy, that is our new systemic complexity. This brings me to my ask of you. You know, Synopsys for many years used the phrase, 'They who have the brains to understand should have the heart to help.' Today, with the gravitas of the situation, the complexity, this is not sufficient. So I amended it with: 'They who have the brains to understand should have the heart to help and the courage to act.' So some of you may say, 'Why us? Why us?' Because you are masters of systemic complexity. You have lived the most amazing exponentials on record, and you have the courage to lead beyond yourself, beyond your company, beyond your nation, beyond your industry, for the simple reason that you care, that we care. So if we indeed do the impossible, that is augment and scale the human brain, then for sure we can be catalysts to kick ass with the dual challenge. I am so, so grateful and moved by your recognition, and especially the privilege to talk to you about something that matters to me. Thank you.
