 and to the joining us from around the world. Good morning, good afternoon, and good evening. We're here in Santa Clara. A few of us respect all the protocol of the safety for all our employees. My name is Sergio Villotta. I'm the site manager of Santa Clara ST site. I'm here today with Paul Sayak, our executive vice president of a sales and marketing in Army region. Today we want to welcome all of you to a very special event that is perhaps a bit unusual for our ST office. We have invited a very special guest. ST Americas is honored to welcome Federico Faggin, a pioneer in the semiconductor industry and long time Silicon Valley president. Federico started his career at Olivetti first and then joined ST micro electronics in Agrate. He has made enormous contribution to the semiconductor industry, beginning as an engineer with his development of his first metal oxide semiconductor silicon gate technology. A fair child, he invented the self aligning metal oxide semiconductor process technology and buried contacts techniques that are both widely used today. Federico from his time at Intel invented the first microprocessor, the 4004, which then later developed also the 8080. Of course, as many people here in the valley, that was not enough for him. He started his own company, Xilog, and later he started also Synaptics, another company founded by him. He also serves as a president and CEO of Fovion, a company that made image sensors. His efforts have been recognized and rewarded with many awards around the world, the Kyoto Prize, Japan I guess private award for lifetime achievement in the arts and sciences, and the National Medal of Technology, the US highest honor of technological achievement is also the recipient of the Wallace McDowell award for outstanding contribution from the IEEE Computer Society, the International Marconi Fellowship Award, the Gold Medal for Science and Technology from Italy, and the European Inventor Lifetime Achievement Award, and many, many others. As arguably, he is the father of more secret processes. Federico is here today to share his own experience, and he compiled and he written this book, Silicon, in which he just tells us his life and his journey through the fair phases of his life, from his childhood in a very small town in Italy, through his life as an inventor and designer, to a successful entrepreneurial effort, and now to his devoted to studying the mysteries of consciousness, where he's again creating new models and explanation that are breaking new grounds. So thank you for being with us, Federico. It's a great honor, and I let Paul now drive our Q&A session with Federico. No more about his journey and his new ventures. Thank you. Thank you. Thank you, Sergio. So as Sergio said, we're live from a vaccinated room in Santa Clara, and again, I want to thank Federico for being with us. We were talking before about this being the 50th anniversary of microprocessor, and you being the pioneer of that. I was wondering if you could take us through from your hometown of the Cenza and your studies in Padua, how you ended up coming to SGS Fairchild. Right. So I was born in 1941, wartime. After a year and a half, my father decided to move to a small, to a village, Isola Vicentina, because the Allied forces were coming through Sicily and they were soon to be in the north. So I spent my first six years after that, so from one and a half to seven and a half. In a rural village, where basically in many homes, there were not even electricity. Farmers were still using plows pulled by hawks. I mean, just unbelievable when you think about it with the eyes of today. So anyway, I experienced how people lived 200 years ago, and my first language was the Venetian dialect, so which I still speak very well. As long as it was also with English. Next was Italian. But in fact, the first day of school, I understood half of what the teacher was talking because everybody speaks dialect in the village. So, you know, Italian was a new language for me, so I had to learn that one first. Anyway, so I grew, you know, then we moved back to Vicenza, where I was born, where my father was a professor of philosophy and history at the Geoclassical and also University of Padua. Scholar, my father wrote about 40 books, translated the Enneads of Plutus and wrote about many philosophers, especially idealist philosophers like Schopenhauer, Meister Rekard, so on. So I grew up in a home that was quite culture. My mother was an elementary school teacher, but I didn't care about that stuff. My first love was model planes, and I decided to, I saw one when I was 11, and that's it, was love at first sight. So I had to build myself one, and then two, and then three, and so I still build them and fly them. But I had no money, so I had to figure out how to design them and make them. And I bought a book, first book I bought with my money, and I was self-taught, essentially, except for the book. And that was a fundamental experience, because he essentially gave me a 12, an experience of how you actually build a product, because the product, you first imagine it, then you had to draw it, figure out a plan, you make a plan, then you buy the material, then you construct it, then you assemble it, and then you fly it from A to Z at 12. In fact, I never had any trouble designing anything, because that experience gave me the entire 360 view of how you build products. You have to manage every aspect of it. But it all comes from the mind. It all comes from that moment of imagination, where you now then it becomes the first transfer from consciousness into drawing, which is some memory on paper, and then from there it becomes physical. So that process is the process of invention. I went to a technical high school, to the chagrin of my father, who of course wanted me to study classical IC, but I couldn't care less about Latin, and even less about Greek in those days. And so I graduated the best of the institute by long shot, but the point is that right after I went to work for Olivetti, when Olivetti was a major force in office systems and computers, they had announced in 1959, they announced their first transistorized computer. At the same time as IBM had the first transistorized computer. So they were fairly advanced for those days compared to the US. In a work in Borgolombardo, I started in 1960, toward the end of 1960, and I spent the entire 1961. And I was lucky enough to be given a project that eventually became my project to design and build a small experimental computer about the size of say the 4004 and all the memories around it and so on. So about that much. And I did that, I did about 60% of the design and build the entire thing. I had four technicians working for me, all older than me. So instead of a plane, it became a mini computer? It became, basically it was the equivalent of a much faster calculator, programmable calculator really, but it was a general purpose computer. But the intention was to have it, you know, a fast calculating machine and to see how that would work. So anyway, so that project then, after that project, I decided that it was time for me to go back and study physics. And you were 19 or 1921? And in the end of 1961, I left. I just turned 20 in December. So I decided to go back to go to university, University of Fadua. And I wanted to study physics because I study vacuum tubes in the technical high school. Transistors were fairly new in 1960. And these tools are all these five, five or 10 years late in terms of what they teach with respect to what is the forefront of technology. And of course, transistors in those days were still very slow compared to vacuum tubes. You know, germanium transistors, they had a carol frequency of, you know, about a megahertz or a few megahertz. So it took silicon to really go the next leg. And so I decided, though, that that was the future. It was very clear to me that was the future. So I wanted to understand quantum physics, understand how the transistors really work, not just using it, you know, but how does it work? And so I did physics instead of engineering, which would have been the more natural thing for me to do. And I never regretted having done that because that was really a, you know, gave me some so solid a foundation of mathematics and physics that that, you know, I could do anything after that of technical nature. So after graduation, I went to work for a small company for for less than a year. And then I ended up in 1967 at SGS Churchill. So it was May of 1967, when I started. And with the earlier company called Cheris, they sent me in Silicon Valley in the summer of 66 to learn MOS transistors, because this company had the rap, they were rap of general micro, general microelectronics. It was the first MOS company in the world, starting, I think, in 60, 65 or early 66. And they had developed a hundred bit shift register. Can you imagine? A hundred, they couldn't build it, but they were, they were, they were, yeah, that was. And so, so, so, so I spent a week here with a course on MOS and the products of this company. And then I went back, but then then GME was purchased by Philco 4 that they disappear. And so my job there disappeared. So I went to SGS. And as just virtual, I had just started an R&D facility in those days. SGS was the European licensee of bipolar transistors and integrated circuits from Fertial. Fertial had about 30 percent ownership of the company. And but they were dependent on products from Fertial. And so they decided in early 67 or early 66 to start an R&D facility. I joined them. In my first job since I knew everything about MOS, right, of course, was to, was to develop their first MOS process technology, which I did. I did in about four months. And then I designed two integrated circuits before the end of the year. One was a 16 bit static shift register, which, you know, which takes a lot more transistors than a dynamic one. And, and, and then it sort of a sort of a gate array with metal that you could decide your own, you know, you know, of course, there were only a few gates that probably, I don't know, they were probably the equivalent of 20 gates or something, you know, maybe, no, maybe 40 gates, but, you know, but that kind of thing. And that was the, you know, that, that takes us to the end of, to the end of 67. And then I was sent here for in an exchange of engineers in early in February of 68. Here in Silicon Valley. Here in Silicon Valley to work in the R&D facility of Fertial. And so that I told you my first life. Yeah, Exactly. In Italy, you know, and now we are at the beginning of my second life. And as we look outside and see all these big buildings in Silicon Valley when you arrived here, I think it was quite different though. Yeah, I would have, I would have, I would have been looking at lots of trees of, you know, apricots, walnuts orchards, you know, and prunes and so on. Right? It was essentially mostly orchards here. San Jose, which is a few blocks away from here, was in those days was probably 150,000 people. And mostly, you know, it was in the country, so to speak, in the agricultural area. And so, you know, it was like, you wouldn't want to go to San Jose, right? And now it's over a million people. And so, you know, 50 years have changed this valley in an unbelievable way. So by 1969, you were still at SGS Fertial, correct? And then you made a move outside, right? But, you know, at SGS Fertial, yeah, I was until, until first of July of 68. Because in June, Fertial decided to sell their interests in SGS Fertial. They asked me to stay in those days that was in the middle of developing the Silicon Gate technology, which is, you know, is the technology that really changed the way we do integrated circuits, because it eventually surpassed bipolar. And so we place even bipolar than in 68, represented 95% of the sales. So, so, so the Silicon Gate really was the way, the way to go. In one shot, we had five times the speed and twice the density with the same power dissipation, same design rules. I mean, that's a big change. That was a game changer. That was allowed to make microprocessor dynamic run because the leakage was about 100 to 1000 times less than metal gate, because you could do gathering, which you couldn't do with metal gate. And then, and then, and then the floating, floating gate transistor, so the all the non-volatile memories, they needed Silicon Gate, because you needed a good oxide to protect the, you know, as an insulator of the few electrons that you could sneak into this gate. Right, right. But, but everyone was, was believing dynamic RAM was, was the, the priority, not microprocessor. Oh, in those days, in those days, most people didn't, didn't get it, especially people in the industry, but we'll get it where the, the customers, they, they had a problem, they, you know, before they had to, to make it hardware solution, typically a state machine, to solve the problem. Now they could use the same components and just develop a simple software. So instead of taking two years in order to have a, you know, a prototype or a year and a half to have a prototype, you know, they could do it in a month. So that's, it changed the game. Yeah. So you decided to stay in Silicon Valley? I decided to stay in Silicon Valley because, because, you know, here, here was where the action was. Exactly. And so that's, you know, and also wanted to finish the Silicon Gate technology. It wasn't done yet. Right. In, in, in June, when I decided to stay. So you had the basis of DRAM and microprocessors. So how did the microprocessor side of that evolve? The microprocessor side evolved by, by Intel having a custom deal. And this custom deal was a Japanese customer that wanted to make a family of calculators, desktop calculators and calculating machines. They had developed their own architecture. They had a three chip CPU. They were still using serial memories, you know, shift registers, because in those days there was no dynamic RAM yet. Right. So the only low cost memory, read write memory was the shift register. And, but shift register is difficult to, you know, to, to handle because, you know, it's great for data. If, if you like a terminal or a calculator where you can, you can have circulating data, but, but when you have, you know, when you have data, your programs, you know, what do you do, right? So, so it's kind of a complicated to handle and to, to load programs and so, and so on is, is a complex thing. So that's why they had three chips. But basically those three chips were, were due to two things. One is that the level of integration that was possible in those days was not, was not sufficient. Yeah. And the extra complexity. So, so the, those three chips were reduced to one chip by changing the architecture so that the architecture could, could handle RAM instead of shift registers as, as read write memory, which, which save a lot. But still, you know, it couldn't be done in a single chip. You know, the silicon game was necessary. That change was not done by me. It was done by one of the application people at, at, you know, at Intel, though, you know, the architectural that computer is kind of, you know, is standard in those days, you know, many people knew how to do it. The question was, how do you do it? How can you put 23, 2500 transistor? We didn't know yet. It was between 22, 2500 the estimate in a single chip. Right. They had to be small enough to be, you know, to make money and so on. And so, so that was my task. I handle all of that. It was, you know, I was creating the process, creating the tools, all the things around, all the things around. Yeah. Intel in those days were making memories. They were just beginning. They were, when I joined, they were just in the middle of making the 1103 was the first 1000 bit dynamic run. And what year was this then? What day you joined? This was 60, 1970. 1970. April. April. So you moved to Intel then? Yeah. Okay. Yeah. And that, that was a, you know, Intel was a small company. They had probably 120 people, which, you know, most of them were workers, you know, because they were already in production. They were producing shift registers in those days and a few memories, but memories were still slow to be picked up also because they were slow. Yeah. Yeah. Yeah. Access time, 1.5 microseconds. Yeah. Yeah. So in the book, you were talking about some of the characters you dealt with in launching the microprocessors. Any interesting stories or people, personalities, obviously that you had to deal with here? Yeah. But, you know, I could go on for hours, right? So I think that we have so much to talk about. Yeah. Okay. All right. Yeah. Okay. So by this time, we're around the processor 4004. 4004. And then, of course, 4004 was for it. It was exclusive for customer. But, you know, and nobody at Intel thought that it could be useful other than making calculators and say, no, no, no, this is excellent to make controllers, you know, like microcontrollers. Right. What now you would do with a microcontroller. So, but they won't listen. So I actually developed a tester of the 4004 using the 4004 as the controller of the tester and also the generator of the test pattern of the tester. Interesting. So that, you know, and so I wanted to figure out how a customer would have to use these parts because, you know, a microprocessor, you know, a data sheet is not enough. You need to have some tools, you know, give some help to the customer. And so I figured out, you know, what needs to be done as an engineer using these parts other than, you know, the customer that already knew it was tooled up to do that. It was physical in Japanese customer. So, so with that, I was able to convince my bosses to get back, to buy back the exclusivity so that they could sell the, you know, those four chips that CPU, RAM, ROM and IO. So there was there were four chips that would work seamlessly together. And at that time Bob Noyce was the CEO. And, you know, I even knew that Bizzico was in trouble because Shima, the engineer that was, you know, came over here to, you know, to help out with the design of the chipset, essentially to, you know, to represent the customer because it was an exclusive deal for them, told me that the company was not doing very well. They were paying too much for the chipset. And so I told Bob Noyce that if he would lower the price, he probably would get back. So which is exactly what he did. And so in November of 71, 50 years ago, the 2004 was announced. And I must say, except for the people that knew what computers do, he did very well for the people that had indeed, that has something they wanted to solve a problem. And so it was very successful, highly successful, but very successful. FATI builds for the 2008, it was the next, also that one started as a custom product. It was the first 8-bit microprocessor in the world, which I also directed. Was the customer base for these? It was Datapoint, which never used it. And so Intel bought back the rights for the architecture. And then out of that, I changed the architecture, improved it, and developed the 8080. And it took me nine months to get my managers to let me do it. I figured out what was needed. So the challenges of today were still present. The management is always in the way. Sorry about it. So anyway, so and that, by the way, that was one of the major reasons why I decided to start my own company. Because look, losing nine months in a race, because everybody after the 2004, was the first design to show what you can do with Silicon Gate. When you have a model, before people would say, oh, Silicon Gate, it's difficult to do, who cares? It doesn't do anything better than the others. That kind of stuff. So now they see it, they can test it and say, oh, my God, we got to do something. So when the 8080 came out, which was early 74, and we had lost nine months of lead, six months later, the 6800 of Motorola came out. Was the first microprocessor of competition. Yeah, and it was well done. So we risked losing the leadership that took me so much, my effort to get it out, to do it. Because when I started with the 2004, Intel was six months late, because nobody knew how to do it. And so they hired me to do it, but they lost six months. So this time you created your own? No, I had to work 80 hours a week to make up for some of the delay, because I couldn't make up everything. And so now we lose nine months, because we cannot figure out what to do. I mean, come on. So I decided that's it, that's enough. I'm going to go start my own company. So I started Zilog, and then I came up with the idea of the Z80, which as you know, was still in falling production today. The Z80, actually I was looking back at the evolution of SGS Thompson, and one of the acquisitions made was a company called Mastec. And earlier in this week, I was in our facility in Capelle, which is really kind of a genesis of Carrollton, where we acquired fabs through this company. And one of the interesting things I saw from Mastec is they had a second source agreement for the Z80, and they also had the rights to the X86 architecture. And I find it interesting that around the same time, had they, you know, it'd be interesting to see because you're tied in with both that being the founder of Z80, they went down a path of DRAM rather than capitalizing on the X86, which Intel eventually capitalized on. What would you think, or do you think, Mastec and SGS Thompson could have gone down the X86 path instead of the DRAM? Well, yeah, they certainly could have done probably as good than AMD did, which, you know, as you know, AMD also eventually got the license from Intel. But Mastec was better off process-wise than AMD in those days, so they probably could have done better. Though there was room to maneuver with the microprocessor like the 8086 because, you know, price was fairly high, so you could, you know, you were not so tied to yield. But also, Mastec was a memory company. The DRAM was a little bit... That was it. The DRAM, frankly, they did the best 4K DRAM after the 1103. Right. So Intel had to kind of rush to... But then the Japanese semiconductor came in and they were really, you know, destroy the ecosystem here. The only survivor is Micron. Yeah, exactly. The only survivor is Micron. Everybody got out except for Micron. So the Z80, though, was extremely... But the Z80, you know, but I must say that you probably don't know, but I gave the license to SGS for the Z80 also. Paleto was... Engineer Paleto was the CEO in those days and, you know, and that was probably 77, 78, 77, 78. That's when I gave the license of... And also the Z8 license to SGS. So how did that Z80 success translate then to your next move from the log? Well, then we did the Z8000. And the Z8000 was certainly better than the AD86. But then, you know, but then the problem with Xilog was that we have an investor. They wanted to compete with IBM. And IBM has said no products of Xilog in this company. So they choose the wrong side. Yeah, right. And so, you know, but actually this is true. I mean, that's what happened. And so, you know, basically we were cut off from the most lucrative and deep because Intel in those days, they had lost the leadership of the Z80. The Z80 had taken the market over with the 8080 was just disappearing rapidly. So the Z8000 was much better than the AD86. So really, I mean, it would have been game over if it wasn't for IBM. And then you went into a telecommunication application. Then my next company was, yeah, was Signet Technologies. They developed a very smart telephone for data invoice. You could send the screen and talk at the same time. I mean, something that in 1984 was unheard of. But it was too soon. And besides in 84, the entire communication ecosystem was upset by the breakup of AT&T. And of course, that I didn't see it coming because. And then you went on to fund Synaptics. Yeah, fund the Synaptics, working on neural networks. I wanted to make computers that learn. And it was a time when the people that knew about AI, they were looking at us like, what stupid thing to do. Neuronetros, everybody knows that they don't work, right? Well, that's not true because as you know, starting from 10 years ago, Neuronetros saved the day of AI because up until 10 years ago, AI with expert systems, their own methodology, never could solve the problems of complex pattern recognition. So I was convinced that the Neuronetros could do the job. It could do it very well. And the solution was analog in those days because it was the only way to have the computation of power with two transistors. It could have been done with one, but two transistors multiply, add, floating gate storage, therefore non-volatile storage for learning and storing the value. And you could do billions of operations per second when you couldn't do it in 86, 87, 88, you couldn't do it with digital simulation. So we were making emulators of Neuronetros, not simulators on Neuronetros, which is what people do today. And how did you come up with the name Synaptics? Synapse. Synapse, it's the same. Synapse is that transistor, floating gate transistor was the synapse, was the emulation of the synapse of the Neuronetros. So we're now designing in CMOS process at 3 nanometer. How did we get from here, from 1969 to 70 to now, to this type of 3 nanometer CMOS process technology? Because MOS are surface devices. You can reduce the size of, by power, by power are three-dimensional devices. They are bulk devices. So you couldn't reduce the size. So this reduction, gradual reduction of size was what allowed to go faster, denser, lower cost, combined with larger wafer sizes. So we are talking about a process that essentially for 50 years has been driving this industry. Unfortunately, we are close to the end of this line. So 3 nanometers, the next step is square root of 3, so 1.7 nanometers. I don't know that anybody knows how to do that. And the cost, the $250 million for a lithography machine, when you first created the process, how much did those machines, $25,000? A way for a liner was $25,000. I mean, the contact last were more like $40,000. That's just unbelievable. Anybody could make his own fab now. How can you, you had to shut out $10 billion for fab, right? So what do you do? So you talked about planes. One of the key pillars of ST was Bruno Morari, and he also was very interested in planes. Do you have any, like, personal stories or interactions with people like Pasquale Pistorio or Bruno or with ST? Actually, with Bruno, you know, Bruno, we went to Germany together to present some ideas on neural networks because, you know, at the time when I was CEO of Synaptics, because, you know, he was interested in neural networks as well. And so, you know, we were, there was nothing that I consider proprietary in those days. We were just playing with stuff. So, you know, and I got to know him much more. I only had met him before when I was working in 67, because he was in application in those days. But then he became a force, you know, an innovator within the SGS and ST. And I bought his high respect for him. And Pasquale, actually, at one point, I interviewed him to take over to become CEO of Synaptics. But his wife wanted to go back to Italy. So there you go. That would have been an interesting evolution of both companies. Actually, he would have done better than I because he was senior and he understood much more about, you know, I mean, he had worked for Motorola, so he had a broader view. It would have been the right thing to do. So being here in Silicon Valley for 50 years, I mean, how have you seen it evolve? I mean, we've seen one of the founders like Hewlett Packard, you know, startup here, and certainly HP is a different company today than they were back then. You have, you know, Apple came, left, came back in a big way, obviously. How have you seen the valley here evolve over your time? The valley evolved by fundamentally picking up everything adjacent to semiconductors. Because even HP, HP was instrumentations essentially in those days. Tested measurement, yeah. They had begun to use, to make calculators. You know, they made the first slide rule. But they were essentially an engineering company, but the culture of the company was not really one to spin out companies. And so, you know, so I don't think that in those days, there was a single company that came out of people that work for, you know, for HP. But Fairchild was one of the first companies that was financed by venture capital, but also by, you know, it was a division of Fairchild camera and instrument in those days. And so he had a little bit of money from outside Fairchild camera, the parent company, and money from the parent company. So it was a more entrepreneurial environment and it was really Fairchild, the spun of many children. Right? So, so Fairchild became, and also the technology was moving so fast that the Fairchild could not keep up with it. So, so people were disgruntled. They said, I mean, this is important. We got, you know, so they would start a new company exactly like I did later myself. And this was because of the venture capital or because of the culture? You know, they co-evolved, right? Venture capital co-evolved with the success of these companies. And so the whole thing grew out of there. But then, you know, then the microprocessor came and that really, again, created an enormous number of new applications, new possibilities, you know, with the personal computer being one of them early on. And so all these ecosystem of personal computers, software, software, there was no software industry for because because, you know, there were a few companies that were selling computers and you either develop your own software or you would have the software from IBM. There was no commercial software, no shrink wrap software, right? So, so that was, that was again, so that was a big deal. Then there was another thing that started in the early 70s. It was was Genentech, the first company in biotech. So the a new, this came out of out of Stanford work, Stanford University work. And so that was a new major wave that spun all kinds of, you know, biotech and Stanford, I think medicine said a lot of this as a university, you know, because sun microsystems and others. In some ways, then for, you know, there was a professor called Terman, Fred Terman. He was the dean of the University at one point and he won. It was actually encouraging the students, you know, to stay here, to start activities here. In fact, he encouraged Ulyton Packard, Bill Ulyton and David Packard to start Ulyton Packard in 1939. So the culture he had developed and with the success and the opportunities that were mushrooming, you know, by the end of the 70s, it was really booming. And now, you know, from a portion of Santa Clara County, now Silicon Valley is the entire Bay Area, seven million people. San Francisco, East Bay, South Bay. It's everywhere around here, everywhere around here. So you find buildings like you have outside, you see outside here, all over. And, you know, one thing that I could never have imagined that would have happened is that this valley innovated even in the cars. Tesla was born here. Exactly. And Tesla did the right thing, meaning you start with a fresh piece of paper. Exactly. Instead of bolting an electrical engine on a car that was designed for a gas engine, you start over. You say, this is a new technology. This is how you disrupt. You're not tied to the past. A lot of the German car makers couldn't start with a clean slate. But even the Americans, I mean, they couldn't because, you know, the mindset has to change. And this is the mindset that made the valley successful. The capacity to innovate started here. Not to start with something and figuring out what to add to something that exists. You start here. Yeah. So being an entrepreneur and mentioning Tesla, you have, you know, Elon Musk, you have in the past, you know, different types of entrepreneurs making big contribution. Is there fundamental things that entrepreneurs share together? Or are there different things depending on the timing, the technology, being here in the valley and being an entrepreneur yourself? What are those ingredients that you see? Well, I mean, it's this desire to innovate, you know, and the pleasure to innovate because, you know, it isn't just the desire, you know, and through innovation, you can change the world. Yeah. And so, you know, it's not just making money. I mean, some want to be entrepreneurs because they, you know, that's the only way to get rich. Right. But that's a minority. Here, people come here with their eyes, you know, you know, illuminated. What I can do. What I can do, right? And how can I change, how can I make something that nobody has ever made before? You know, that is what made the valley, you know, the spirit of called entrepreneurship, but also a deeper sense that you can do it. You can make it, you know, and everything is here to allow you to make it, which unfortunately, very few other parts of the world have, you know, the money, the infrastructure, the services, the people that you can hire and take from other people. Sorry. Yeah. Exactly. It's so alright. But there's very few obstacles. I mean, you want to start your own company. You can do that in a few days. You know, there are very few places where there's the bureaucracy is completely removed. Everything helps you instead of hindering you. In some countries, you know, you are hindered. You know, you cannot do anything new because just to incorporate a company takes three months. Come on. Too long. Yeah. So you talk about artificial neural networks, AI. You know, I, there was a very famous, I think, debate between Jack Ma and Elon Musk about what's the future of AI and these types of things. I like this, this TV show called The Person of Interest. And it's following kind of this idea that once created by man, artificial intelligence systems can start to take over public and private data systems. What's your thoughts on this? How do you see this evolving over the next 20 years? How much time do we have? I don't know. We have to catch up. Okay. But what do you think? I mean, what is the short answer? Never. AI will do much better than we do with our rational mind, but the rational slash mechanical mind. But we are conscious being. And consciousness is not a property of computers. Yeah. Okay. Consciousness is a quantum property. It's not. It is a property of qubits, which are entangled. Yeah. And entanglement is the difference between quantum and classical. In classical, you have bits. In quantum, you have qubits. The best that you can do, moving from quantum to classical, is a qubit, which is an infinity of states. There will be points in a surface of a sphere that will be, you know, it's called the block sphere. Okay. So those points in the surface of this sphere reduce in this physical one, this space time, zero and one. That's it. So that's how different is consciousness. And consciousness, of course, is the capacity to feel to know within ourselves. Not within, meaning in the heart or the brain, not in the physical. The within is another dimension, is the dimension which is the the Hilbert's corresponds to the Hilbert space of quantum physics. The Hilbert space is an n dimensional space where each core, each coordinates is complex number, not a real number. So because of that, you can create situations in which the sum of the parts is more than the sum of the parts, which, you know, is twisted, but is twisted like quantum mechanics is twisted. A particle, an electron is both a particle and a wave. Go figure, right? What does it mean? It means that an electron is a system. It cannot be an atom like, you know, the atoms of democracies, you know, bounded, little hard with certain properties and so on. No. The electrons are systems that behave when we measure them here, behave like a particle, like it was an atom. Okay. But when they interact, they share states, that's entanglement. They share something and these states that are shared are independent from the distance. Therefore, when I change, when I measure something here, immediately something here happens. That's magic. Not not not time to move from information from here to there. Instantaneously. So this is the property that is inherent in our consciousness and also in our free will. Right. In a theory which I have developed with a famous physicist, Italian physicist, is a specialist in quantum information. The actual collapse of the wave function, which is how a quantum state becomes a physical state in space time. So you go from many to one, many states possible in superposition to one, that of course by virtue of the free will, the free will makes that conversion. So that's a revolutionary view. This will become a chapter in the book that will come out in a month or two. And it is a paper available in an archive already, but it is a, you know, a preprint. So this theory is really the first theory of consciousness and free will, which goes against the grain of how people are thinking, typically scientists are thinking about quantum classical and free will in particular. But you're marrying philosophy and physics together. But you talk about free will. Free will is not free will. You call it a physics? Absolutely. Absolutely. It is free will. It is physics in this model, in this theory. So how does that consciousness interface? Basically, but it is already, in a way, is already known, but nobody wants, nobody accepts it because somehow people do not like free will. Because if reality has free will, it means that if you know, you are not better than anybody else. Right? And this is why the artificial intelligence, which lacks free will, can never, can never be over. The artistic, the artistic will. The sum of the parts is the whole. In a computer, the sum of the parts, which are the parts are the algorithms that interact, the interaction is the sum of the parts which are the algorithms. The sum of the algorithms is all there is. There is no whole as an independent entity that can affect the parts. But in quantum physics you can. In quantum physics when you have this superposition in entanglement, new entanglement creates new holes that are more than the sum of the parts. And that's what nobody had before understood. That's part of this paper, part of this theory. So that human-to-machine interface, if we go back to synaptics and one of the big inventions was the touch controller, where you have a human-to-machine interface. What you're talking about now is something much, much, is taking this to the extreme. But is it the same kind of process of human-to-machine interaction that synaptics? No, no, no, no. This is way beyond that. This is what makes us human. I mean, this is big, right? Because science today is telling us that we are machines. We are biological complex machines. That's it. There is no consciousness other than the functioning of the machine. And I'm saying no. The functioning of the machine is the correlate of something that involves consciousness driving this machine. We are controlled by this entity that we really are. We are a quantum entity. We think that we are the body. But we are this quantum entity that controls the body. Big difference. I mean, this theory returns power to human beings that the people that tell you that you are a machine are taking away from you. If you are a machine, what the hell are you going to do? I mean, especially if the machines are smarter in the mechanical sense, controlled by smarter people than you, they know that they are not machines perhaps, but in any event they want to control you through the machines that they make. Come on. I mean, we have to wake up. This is what's going on today. So how do we manage these machines in the future? Do you regulate? There has to be some form of regulation, obviously, because you can imagine how much mischief you can do if you control those machines. But these smart people behind, they control them, but they pretend that they are not. They are innocent. I'm innocent, but they, you know, they, yeah. Interesting. I see you very animated. This is the exciting part of the book. I don't know, Sergio, if you want to take some question as we, as we move through this, because I think this portion of the discussion of the book I find really extremely interesting. Do you want to come to the, to the... We haven't had the question specifically for that. So I don't know if we want to go back a little bit. That's fine. Or maybe come, Sergio, in the camera. So one of the question was, in your opinion, what will be the biggest innovation to come in the next 10 years? And maybe this one you can... Sorry. Practice. I can hear you better. In your opinion, what will be the biggest innovation to come in the next 10 years? And actually, what do you will see your theory of consciousness going in 10 years from now? You are talking about the next book. Yeah. Yeah. You know, my hope would be that in 10 years, a sufficient number of people understand what I'm talking about, because returning meaning and purpose to human life is the most important innovation that we need. Okay. Technological innovation, great. They are, they are, continue to occur, they will take their course, but if we do not evolve our consciousness and the sense of who we are, we are doomed because this technology otherwise would be used against us. Okay. That's, that's it. As simple as that. Okay. So reading another question here. Who do you think will be the most influential person or agency into this new innovation process? Well, I mean, the, I mean, basically the people that are awakening that understand that we are now machines and they want to understand who are we really and beginning to move in a direction of personal discovery. This, this job has to be done by each one of us. It cannot be done by reading a book and repeating what you read. You got to do it within yourself. Each, each of us need to understand who we are within ourselves. That's the only way that is going to work because only within yourself you know if what you perceive is right or wrong. And you know it. Absolutely. If you're really serious about it and you want to know, you will know the same way that happened to me 30 years ago. I was unhappy about my life after having achieved everything. They should, the world says that if you do this, you should be very happy, you know, and I wasn't. It was the time of, I was studying consciousness, study neural networks, neuroscience, biology and so on. I wanted to understand this stuff. And I had an image, you know, an opening where basically, you know, is in the book, you know, I cannot, there's no time to tell. But basically, I experienced myself as the world that observes itself. Now, that's a mind bender. How can you be the world that observes itself? You have to experience that. It's not something that is logical. Exactly like quantum physics is non-logical. How can an electron be a particle in a wave? Exactly the same problem. And I experienced me as a particle, the observer and the wave, the world. It's very interesting because the next question that we receive, it's unusual for the environment of engineering. But what is your view on soul versus consciousness? Is consciousness in your words the same as soul in many philosophers? The consciousness is the capacity to experience through feelings and sensations. What philosophers call qualia, the fact that I know not because I have signals in the brain, a computer has signals in the brain and it does whatever it does, it goes from signals to action, nobody home there. No feelings, no sense of self, no sense of the world, no understanding of what it's doing. But we have between the signals and the experience of the signals, which is qualia, something happens. That capacity is not in this physical world. It is in another physical world, which is the quantum world that was mentioned before. So it's like, look, suppose that you are controlling the character in a computer, like a video game, but not with joysticks. You have a costume that every movement that you make is automatically taken so that you actually, the character simply does what you do without you having to think about it. Then you have your goggles, you see in 3D the virtual world and you hear the voices of people there and your voice is heard. So, suppose that you are in this environment. Now, you have a sense, you basically think that you are in a real world. I mean, you see space, you see space. But where is the space? The space in the virtual world is not this space, it's the space created by the computer, but you perceive space. You move, you do stuff, you can even get so in control or so, you know, so, you know, captivated by the game that you forget that you are actually in this world, especially if you are a kid, right? And so, all of a sudden your consciousness is focused on only that reality, okay? But where is the experience? Where is the reality? Is it in the computer? Is it in the character of the computer? No, it's in you, all right? Now, let's make it another step now. My consciousness of this physical world is not in me. It is in that entity, quantum entity, where the experience resides. So, my body is like the avatar in the computer. But have you seen the Marvel movie Ant-Man, where the guy goes back into the quantum realm? It sounds like we're in this space. If you haven't seen it, you can... But the point is, they cannot go back to the quantum realm. You see, that's the old point. The old point is that there is, you know, irreversible transformation. I mean, the quantum world is many dimensions and dimensions. That's where we have the experience. So, I mean, people don't understand quantum. That's the problem. But everybody says quantum. But, you know, saying quantum and understanding quantum, two different things. Yeah. Maybe, Serge, if I go back to your first question, the answer to that from what I heard is, it's like the innovation. It's not going to come from a government agency. It's not going to come from a market leader. It's going to come from just like everything else, an innovation from an entrepreneur who understands these types of things. Yeah. Because the entrepreneur translates something. Okay. You know, translates something that is in his mind into a product, an idea that is, you know, there are worlds or pictures or images of what I view. So, an entrepreneur, you know, is essentially a translator from a higher mind, a higher mind where there is intention, purpose and ideas Competence. Into symbolic form, which can be a product. You know, this is a symbol. In my model, this is a symbol. Right. My body is a symbol. But my consciousness is not in the body. Okay. So, but really, just the analogy or the metaphor of the, you know, the virtual reality that I made before can get you pretty close to understanding what I'm talking about. Because when you control a character, the experience of that world created by the computer, the experience and of the character that you're embodying is not in the computer, nor in the character. You see? So that tells you immediately that we are playing the same game in this physical world. This physical world is our construction. We are constructing this. And we think that we are living in it. But we are constructing it. The body is living in it. But the experience is not in this physical reality, is not in 3 plus 1D. So that's how powerful this is. I think you, Paul, and you, Federico, have just answered the other question. Of course, someone just started a career of engineering. Where should they focus? I think this is exactly the focus that we... But they should focus on what they really feel like that they want to do. The passion. What they're passionate about it. Absolutely. The passion and the desire. That's really what drives everything, is the desire to do something. And then you take the rest of it goes with it. But if you don't have the desire... Having started and founded a few companies, it's such a cliche, but I have to ask, how do market leaders or established companies allow for this type of entrepreneurial spirit? How do they break down the natural bureaucracies that force people to leave the company and start their own ideas, their own company? Frankly, they shouldn't even try to do that because it is inherent in a structure when it reaches a certain level that the number of entrepreneurial spirit, on average, decreases. Because you need more doing than inventing new things. You need inventing too, of course, but percentage-wise, that naturally decreases. And so by people going out, they provide new innovation to serve the company that let those people go out too. In fact, you can acquire the company and later if they are successful and let go of the ones that were not successful. So the best way is to spin it out, maximum freedom, and don't try to manage in your corporate process. Well, no, you shouldn't manage the innovation necessary to go to the adjacency of the marketing which you are operating. Of course, you don't want to let that go. So you need to maintain that ability to innovate, but you cannot do everything and many people can have ideas that are not necessarily what the company should be doing. So let them go, I mean, let them go do their stuff. And then maybe five years later, this company has done something that you didn't see and then you can buy that company back. Exactly, exactly. Many small companies, start-up companies end up being bought by larger companies. Elon Musk just did this with SolarCity, right? They spun it out, they created some things and then Tesla just bought it back. They bought it back. Because it takes a different environment. A larger company becomes more bureaucratic. An entrepreneur hates bureaucracy. He wants to get things done like me. Yes, knock it down. Any other question from you? No, just to thank Federico for the time. I mean, this is the book Silicon. Yes, and it is available on Amazon. But also in Italian. Also in Italian. It's published also in Italian. And you have also a website, right? SiliconTheBook.com. So if you want to buy the book and read the other interesting story inside the book, please do so at Amazon. And I just want to thank you, Sergio, for putting this together. This was really great and Federico again. Thank you, Sergio. Thank you for your time. Well, it's been my pleasure. I always, always, always be happy to hear Federico. It's a very interesting person as we have seen here. And I was reading the sentence here. Our technology starts with you. I think that's the most appropriate that we can ever choose having here, Federico, today. And we, I mean, I extend the invitation for your next book to present the book again here. You are always welcome here in Santa Clara. You are our neighbor. And please visit us anytime you want. Thank you, Federico. Thank you, Sergio. Thank you.