A Nobel Laureate’s Lessons From Birds | Giorgio Parisi

Professor George Parisi. He's a renowned theoretical physicist, currently a professor of quantum theory at the University of Rome. In 2021, he won the Nobel Prize for his groundbreaking contributions to the theory of complex systems. What secrets lie in the elegant movement of a flock of starlings? What can complex systems tell us about the nature of life, our universe, and ourselves? Welcome everybody to an exciting episode of the Into the Impossible podcast. We're joined today by an inspiring physicist, a man who's made many contributions to our understanding of nature, and especially the understanding of what are called complex systems. We're going to get into that. But the first thing we love to do on this podcast, Giorgio, is to talk about the title of the book that you have written. It's called In a Flight of Starlings, The Wonders of Complex Systems. Can you explain, Giorgio, what does the title mean? And what does the cover art, what does it illustrate on the cover picture? Giorgio Parisi The point is the following. I've been interested for a long time in the flight of a starling. I mean, starlings are very interesting birds, and they are doing the flight in a very huge group of thousands and thousands, especially in the evening, just as a moment when they have to go to sleep. And the point was that the image that these birds are doing are really amazing, fascinating, but no one knew exactly how they could communicate to do this movement. And the thing that was most fundamental, no one really knew, which was the form of the flock. Because when you see a flock of birds, you see the image that you have on your retina, but you don't see the three-dimensional shape. And usually, in order to see the three-dimensional shape, you use two eyes. But with two eyes, you can see the distance of objects which are nearby. So, which was the solution? The solution was to put two eyes, and we decided to do an experiment about that. It took a few years to do, and people are still working on the problem, and to see how really the starling fly, and the solution was to put two eyes at a distance of 20 meters. Of course, you cannot put really your eyes at a distance of 20 meters, but you can put some camera at a distance of 20 meters, make synchronized pictures, photograms of the starling with these two cameras, and having a three-dimensional reconstruction. This is not so easy, but in the end, we succeeded to do. So, when we decided to write a book on complex systems, one of the chapters was dedicated to the BEVs. After the book was finished, we decided with the editor's order, we discussed the chapters, we discussed to put the chapter on BEVs, on Starling in the first, and also because it was, in some senses, the one that is most fascinating, most easy to be understood, and at the end, we started to discuss the title, and we arrived to Z1. Yeah, it's a brilliant book. It's very short, it's very readable, and it's endorsed by none other than our friend Carlo Rovelli, who is coming back on the podcast for his 20th book, I think it must be, on white holes. I don't know if you know this, but Carlo and I recorded the first ever audio book by Galileo. So, here is Galileo. There's a mini puppet of Galileo. He's holding his telescope, and it reminds me, in your book, when you talk about devising not maybe a new way to see things that were never seen before, but a different perspective, and Galileo said the following when he was inducted into the Lynchian, you say society? Lynchian, yes. Of the lynx, of the lynx, of the animal. That's right. He said, a scientist should measure what is measurable and make measurable what is not yet so. Was this discovery that you made with your colleagues, was this hiding in plain sight? Was this something that could have been discovered earlier, or did it really require the new technology, not maybe of the telescope, but of the camera technology? Could your discoveries have been made 30 years ago, 40 years ago? The things on Stanley, I think that was just the first moment it could be done. The reason is the following. We needed to have a huge number of photographs because it was really a movie, and in order to do this before us, you have to do with the estimate that we needed, and anyhow, and we used tens of thousands of photographs. And now this has to be used in somewhat a digital way because they have to be analyzed by computer. Now, the very idea to have something like an archive with 10,000, maybe 100,000 photographs, and look into them, digitize all of them, is something that is really a big, big mess. So, I think that we started just at the moment we see the camera technology was good for using these things, because we had the sun at that moment, there were four megapixel camera, there was the upper professional one, a Canon, that were able to shot eight photographs per second. So, that was just the one that went out, the price was $5,000, we had to buy six of them, or eight of them. So, but it was not a real problem of the price. The point is that the things really did not exist, digital camera of high precision and high speed. When I look at your history of collaboration, it's impossible for me to not ask you about your advisor, Nicola Cavivo. Can you talk a little bit about him as an advisor? And maybe explain a little bit for my audience, what was he known for? What was his big contribution to physics that probably warranted a Nobel Prize, in my opinion? But what was Nicola like as an advisor? And what did he do for physics? Nicola was a wonderful advisor, was a wonderful advisor, because first of all, he was a very friendly student. And the things that he really did, he was transmitting enthusiasm for the science, was transmitting interest in doing science in a good way, in the right way, and without caring too much of the publicity result. But the real point was to understand that deeply what one has to do. And also the other things that I remember very well of him, that when we're discussing some possible things to study together, the point was that one should try to pick something which is amusing. I think that it's amusing for the scientists, and I think that this is important, because if you start some project which is very boring, at the middle you are going to stop it, you are not going to finish it. So to have some kind of amusement, which is the same kind of amusement that may help people when they solve a puzzle, but it's important to have amusement. Now Nicola had been a really great scientist in the 60s and the 70s. He made a lot of discoveries about the behaviour in which what people call radioactivity, I mean people nowadays call weak interactions, I mean some forces which are not as strong as strong forces. And the thing that he really understood, the way that these particles interact, we'll say at the present moment how quarks don't interact in the weak, and introduces what people called after him the Cabibbo angle, and the Cabibbo angle is at the basis of present theories of weak interaction. He could have had the Nobel Prize in 2008, I believe, but things happened that the Nobel committee decided to not give to him, doing some arguments which I think were factually wrong, but sometimes also the Nobel committee makes some mistakes. When I think of him as an advisor and a contributor, it didn't seem like he was bitter about not winning, I mean it seemed like he was committed to his students and to the science with enthusiasm. So is that a trait that you mimic with your students? Did you learn as an advisor to many students, and formally and informally as well, to many millions of people probably? What lessons in terms of education or being a mentor did you learn from him? Yes, I mean I think that I'm trying to transmit the enthusiasm for science, and enthusiasm for science is quite important to do, and of course you have to do it the right way. I mean you have to sit down near your students to understand what they're doing, have them to do, and also you have to encourage them. I mean if they're able to solve things in some way which is not the best way, I think that you should let them go on and not explain that it could be done in a much simpler way, because otherwise you take out from them the joy of having discovered something. And I think that I have done things well, because there was Nature, the magazine Nature made a prize for mentoring, and this was I think in 2015, there was the prize for mentoring in Italy, and I think I was one of the three guys that won the prize for best mentor in Italy. And this was based also on the reports of my students who wrote the very enthusiastic report. Well certainly, so I think it's Latin, and you'll correct me if I'm wrong, but the word educate in Latin is educare, and it means not to pour into, but to bring out of. And so I think you've brought out a lot in your students and your colleagues, and it seems to me you have quite a good deal of humility as well as sort of the confidence to pursue these incredible questions. And when I was reading the book, I started to wonder about these murmurations. So a murmuration is a collective noun for starlings when they flock together, and it almost as if they become a different entity, like an organism. Can you describe what they're actually doing? Why do they do this? Is it for to scare off predators? Is it to migrate? Is it to attract mates? What is the evolutionary purpose of a murmuration? Well, that was well understood by biologists much before entering the game. The thing is clear. These sparrows do not like cold weather. Therefore, in summertime, they stay in North Europe, and during the winter, they arrive more or less in November to Rome, and they spend the winter up to March. In that period, they have to find a place which is relatively warm, because they do not have enough many things to eat. They have some fat, but the amount of fat they're able to burn is not so high. So the point is to find a place which is good, which is warm, that you must have some trees which have leaves, and there should be not too many cats that go on the trees, because that would be bad for other reasons. So what happens is that when they come, they go in the countryside during the day. So they're commuting. They go in the countryside in the day, and they come in the evening to sleep inside the city. But anyhow, they commute, and when they come back, they have to find out a good place. Some of them will find out a good place, or maybe the same as the previous day. So they start to make some kind of murmuration movement on the top of the place, and the other bird that arrives, they see this kind of murmuration, and after they're becoming bigger and bigger, and when it's the moment to go to sleep, which is usually half an hour after the dawn, they go to sleep, and this murmuration can be seen from a very large distance. I remember that I was able to see murmuration on the sky room, more or less at 10 kilometers of distance. So they are something that you can easily see in the sky, because you don't see usually the sky objects that move, make change, and so on. Yeah, they're quite mesmerizing. Are they describing them with the tools of condensed matter physics? Do they exhibit phase transitions? Do they exhibit first order or free energy? Are there things that we can connect to our introductory thermodynamics classes that a student can understand about their behavior? Or is it really unique to these birds and the fact that they're birds? Are there commonalities, critical points, phase transitions? How do they behave in a physics, from a physicist's perspective? Well, from the point of view of physics perspective, one has to take care that these birds are out of equilibrium, because usually when the student is doing the standard textbook for thermodynamics and so on, one is looking to a system which are at equilibrium, and now at what people call thermal equilibrium, and now these birds are not at thermal equilibrium, but I mean, thermodynamics, the physics of these last years has done a lot of progress to discuss a system which are not at what people call thermal equilibrium. And therefore, one can use in describing these birds by physical law, one can write something like an equation of motion, collective equation of motion, one can speak of a normalization group, phase transition, and the thing that happens is that the way that these birds move is essential that they stay essentially at the critical point. The reason for which they choose the type of parameter which they use in flight to stay near the critical point is that when you are near a critical point, near a phase transition, the speed of information inside the system is going to move very, very fast. Indeed, this is what happens in this case, because in half a second, all the flops decide to turn in one direction, another direction. We know that when they turn, the few birds that start to turn, which is typical in the center of the flop, other birds are following, but the signal that someone is starting to move propagates very, very fast. My thumb is very busy right now holding up good old Albert, but if yours is free, please go ahead and hit that like button, and don't forget to subscribe. It really helps us with the algorithm. When I thought about the murmurations, it crossed my mind that maybe human beings can exhibit these same kinds of behaviors but not know about it. Are there phenomena, maybe not physical phenomena, because except when we go to a football game, we don't really behave as huge flocks, but are there social behaviors, maybe obsessions or so forth, that human beings also can act as murmurations, or am I wrong? The point about the reason of murmuration is that each bird is going to irritate the other birds nearby, because it has to avoid collision and so on. Therefore, there are many, many things in a society where people try to imitate other human beings. For example, you can think of fashion, but also there is one particular case that we have studied, and it is the distribution of baby names in the United States. Now, you see that in certain moments you have a certain fashion. For example, in the 60s, Jennifer was a very common name. Nowadays, I don't know what may be a very common name, maybe Isabella or something like that. Now, if we look at the distribution of names in the United States, you see there are some states which have nearly the same distribution name of other states, and other states that have different things. Now, what we did, we analyzed numerically these distribution names, because we have the recording of the names that were given to babies in the last century and something. For example, the thing that we discovered that, for example, in one century ago, the great division was the North Sun County and the South Sun one, that were quite in a different way, and now what happens essentially after the thing changed in the 70s, and now the East Coast and the West Coast go very well together, and the center part of the United States goes in another direction. Something like, I would say, that the democratic state used different names than the republican one, roughly speaking. And now this is clearly an effect that people hear probably different television channels, read a different newspaper, read different things, have different friends far away in the United States, and also that is something that we published, and also we started to study if one can understand this type of waves, which are the states which they first started, and we found, but we had not finished or started, that there are some states which start two, three years before the other, some kind of fashion, and after the other state is systematically imitated. So, this is something that can be done in many, many different subjects. The only point is to have the data, because if we would have the data sold in each state of the United States by Amazon, one could do this kind of study, but the fear that it would be very hard to have from Amazon this kind of data. Yes, yeah, I agree. That's fascinating. Let's turn towards now the research that you did. Kind of buried the lead, as they say. I didn't mention that you won the Nobel Prize. Normally, I do that in the intro, but I'll clean that up when I actually edit the video, but I want you to now drop in and start talking about your work on spin glasses. They're so fascinating, and the curiosity I think my audience would have is what inspired you to do that and invent this concept and collaborate to make this occur, and then possibly talk about some technological implications of them. So, let's start with what is glass, first of all? What is glass, and how does it have an applicability to spin? I mean, if you have, you know, my glass starts to spin, I've got problems over here. So, tell me, what is glass, first of all, and then what is a spin glass? Because I think the public understanding won't be as clear until you explain it rather than me. Let's say to the following. It's supposed to take water. You cool the water, and it becomes ice. And we know that this happens at a very precise temperature, 32 Fahrenheit. And so there is what happens here, in that case, a well-defined transition from something that you call liquid to something that you call solid. Now, suppose that you look to the wax of a candle. I mean, when you see that it goes down, you see that it's liquid, and after going out from the fire, it becomes more and more solid, but it's not really solid. It's something that you can push your finger in and deform it, and becoming cooler and cooler, become more and more rigid. Now, in this case, you don't have a real fast transition. You have a situation in which you have a liquid that, at a certain moment, becomes so rigid that you cannot really push it. And you have many, many other types of liquid of this type, like, think of honey. Honey is liquid, but you usually don't do it, but if you put it in the fridge, it becomes really solid. So you have a lot of things, and real glasses, window glasses, belong to this category. And in Venice, you can see how people work with glasses, when they are very hot. Now, spring glasses is some kind of material which have some glass properties, they behave with some respect as glasses, but they are done with spins. But if you ask me why I was interested, I became interested at the moment which I did not know anything about spring glass. The only thing that I know, that it was a mathematically difficult problem, in the sense that somebody had tried to give a solution, but the solution was factually wrong, it was inconsistent. And now, so I started to study how to solve the mathematical problem, and at the end of one year, I found the solution of finding, of computing the quantities that were needed to compute it, and after all that period, I was not at all interested to what spring glass were, to which was the possible experimental realization. I mean, if you want, all physics connected to spring glass was not interesting to me. It was just a problem that I wanted to solve, also because maybe I wanted to show that I'm good in solving problems, but not particularly interested to it. And at that moment, I left the problem, and after a few years, three, four years, we started by speaking with people to understand better the meaning of the solution. We started to have a new interest in the problem, we started to look at it better, and realized that the problem was connected to a complex system. But it was discovered that it was done by analyzing the problem a few years after that was done. And that was due also to the fact that other people were looking to the problem, and therefore I also found there were interesting things to be understood, and I started to look again, and after looking again in details, one started that it wasn't connected to a complex system. And spring glass itself is embedding magnetic or metallic particles inside of a glass, as I understand it. Are there any technological applications, resistors, transistors, quantum computers, are there any technological spinoffs from these magical devices? No, as far as I know, spring glass, no one has found a real application of spring glass. Someone was thinking maybe to have an application as a memory, but it was too complex to be done. No, what was, and a lot of technology has been offered, was a theory that was behind spring glasses. Because the theory that was behind the spring glass was not so different from the theory that Hofffield wrote down for the first modern type of neural network. And the theory of spring glasses was fundamental in the way that was done by other people, by the Israeli group led by Amit, to have a deep understanding of the Hofffield model of neural network. And this made a strong push towards understanding neural network. Many people started to study analytically neural network, because using the theory about verification, the theory of that type, for example, people were able to compute using this kind of theory, which was a maximum amount of things that a Hofffield network would be able to memorize. And in this kind of wave of interest for neural network, in the 90s people started to propose what the deep network, which now are the deep networks, the deep neural network, are now at the basis of modern artificial intelligence. Let's summarize that the interest in spring glasses in the 80s had also a deep influence of the beginning of neural network, and this neural network are now artificial intelligence of these days. PAUL So my first book is called Losing the Nobel Prize, and it's about the story of how I came to invent an experiment that was looking for cosmic inflation, trying to understand the origin of the Big Bang via the imprint on the cosmic microwave background radiation, and how if we had been proven correct, then if the experiment had been confirmed, then somebody would have won the Nobel Prize, maybe not me. But everybody agreed that this was the case, and in fact, we got a lot of attention. And then spoiler alert, we did not win the Nobel Prize, and that's the name of the title. But a lot of people criticized me and they said, well, you can't lose the Nobel Prize because you don't really have it until you lose it. And I said, that doesn't make any sense. You can't lose a football game because you didn't win the football game. But it actually occurs to me that you did lose a Nobel Prize in a certain sense back, and you described this in the book, to Kenneth Wilson. Can you talk a little bit about what Kenneth Wilson did, what you almost did as well? Can you talk about your actual losing the Nobel Prize before you actually won it? There were two moments when I was very, very young. I was 25, that I lose in some sense the Nobel Prize. The first one was that I was interested to the same problem that Kenneth Wilson was interested in, to understand the renormalization, to understand not the renormalization group, because the renormalization group was the idea of Wilson to understand the second order first transition. But in this case, there was no match because Ken had so many ideas, and he was working on the problem in the last 10 years. And so, it's clear that I could not really match him starting in one or two years time. And so, when just at the moment where I arrived to start to think about the problem, he came out with a solution. So, this was really no match. The things on which we were quite near was the point of view of asymptotic freedom. Asymptotic freedom, which was a wonderful idea that got us a Nobel Prize by Grosz-Wilczek-Politzer in 2002 or 2004. I never remember. Yeah, 2004. Yeah, Frank Grosz-Wilczek, he's been a guest on the podcast. Grosz-Wilczek-Politzer got the Nobel Prize in 2004 for asymptotic freedom. But at that moment, I was really interested in this type of problems. And I knew that the same computation of Politzer-Grosz-Wilczek was done by Toast that was left unpublished. But Toast had not tried to apply this type of computation to real physics, which was the opposite of Grosz-Wilczek that discussed the quantum chromodynamics. So, the things, I remember that I was in CERN with Toast, and we started to discuss how can one construct a model of physics in order to use this discovery. Now, we have only discussed half an hour because I was interested mainly to other problems connected to first transition. But Toast was interested in quantizing gravity. And just the right solution that was a model that was proposed by the man two years ago that I knew very well. I did not like the model, in reality, but I knew the model very well. It came not to my mind the idea of applying to that model. Now, if I get the idea, or someone would be present in the discussion and would just say, but what about the man model? It's clear that all this, we could write a very similar paper to those people who got the Nobel Prize in two days because all the computations were done and it was easy for me to spell all possible applications. But the idea did not come to our mind. I was an expert on physical applications and Toast was more interested in theory. So, the thought was mine, certainly not Gerard's. But anyhow, we did get something that, in this case, I was quite near, a few centimeters away, and the things escaped. Also, maybe it could be a mess because as far as probably also the other people in the United States would arrive at the same moment, would have five people with the same disability, and which would make a cosmos for the Nobel Prize committee. But I really do not know what would happen. Well, my second book, thankfully, is not as obsessed with the Nobel Prize being lost, but it's about how to win one, potentially. So, this is my second book. It's called Think Like a Nobel Prize Winner, and it's all about how you can collaborate and work with people to make the world more understandable. So, I want to ask you about collaboration and how you view collaboration. Is it possible for scientists to work in isolation and not be involved with, say, experimental results if you're a theoretical physicist or if you're a experimental physicist to not understand the theory? Is it possible to do things by yourself nowadays, or is it only possible with the help of collaborators? Well, I think that it's very, very difficult to do things by, to have one man work. Of course, sometimes we do have, but this is just an isolated spot, I would say, because after, in order to show the importance of this isolated work, you need the work of many other people. So, this type of collaboration is very important. I mean, certainly, I am very fond of collaborating with people. When I was 70 years old, people had just done a poster with all the names of people I collaborated with, and there were 317 people. If two years ago or one year ago, maybe people did an updated version of the poster with 360. So, I am pretty sure that I'm supposed to go more than 400 of different collaborators. Sometimes our collaborators are all in one work. Sometimes our collaborators have written 50 works together. But I think that collaboration is very important in these days, also because, and what is certainly important to change your ideas with people, because sometimes you have some idea, but very often the idea that people had are half-baked ideas. And in order to transform really final things, you have to explain to other people, discuss with them, and so on. At least from my point of view. Of course, there may be other people that work in a different way. I understand, thanks to many discussions, at least in the first paper, Relativity with Besser and other friends and so on. The influence of Grossman was very important because for General Relativity, it was needed mathematics that Einstein did not know. Very few people knew at that time. Grossman, I already explained to him. On the other hand, Einstein won the Nobel Prize for the photoelectric effect was really something that he did by himself, as far as I understand. Yes, I think you're right. And what was so fascinating about this book, or many fascinating aspects of In a Flight of Starlings by today's guest, Nobel Laureate Giorgio Parisi, is that you kind of go through a checklist of what it's like to have an idea. And it's in a chapter called How Ideas Are Born. And I wonder if you could comment on it. You talk about these four steps and we'll put them on the screen. There's a first preparatory step where the problem is studied, existing literature read, and first unsuccessful attempts are made. It's a period that can last between a week and a month because it ends when no progress occurs. Then there's a period of incubation, step two, in which the problem is abandoned, at least consciously. Three, the incubation ends suddenly with a moment of illumination, which often occurs in an unrelated situation. And then four, after the illumination provides the general way to tackle the problem, the solution must be formulated. Can you talk about your process, your work process? Do you follow this rigorously? Or sometimes do you have ideas that can be made to fruition relatively quickly? Or do you really have to wait for these moments of inspiration followed by maybe a fallow period when you're waiting, nothing much is happening, and you abandon it? How does that interplay work, especially when you have collaborators? It's hard enough to have one idea of your own, but you have a collaborator. How do you get him or her to abandon it and work on it, et cetera? So can you talk about your idea generation process? How are ideas born? Well, the point is the following, that it's not that I'm really following this program. I mean, it's not something that I do programmatically. Just thinking on a few cases in which I have some particularly good ideas, and also looking to something that's written in the literature, because other people describe the way that they got the idea. The famous case in which they tell, I mean, usually scientists do not tell people how they got the idea. They only present the final result, but not the way they get it. There are people that discuss it, they discuss it from a career, they have a case of it later, or they have something that is seen in the book of David Well after he wrote my one. So many people describe the way that they get the idea, and this is something that is quite common. Of course, the fact that you need some months is something that, especially for very important and difficult ideas. But in certain cases, also for simple, for much simpler things, is something that you need to work in a similar way. The only thing is that the time scales are much shorter. For example, I remember sometimes that I start in the morning to look to a new program. I realize that it's a bug that does not work, the program code is wrong, and I spend the whole morning trying to understand what is wrong. However, I am not able to find it, but after that I start driving for going to home at lunchtime. During driving, I understand what is wrong. I go home and I check that that was exactly the same thing. So, the fact that sometimes looking back, I mean looking for a little far away, is something that helps. Of course, this way you have a collaborator, the things are somewhat easier if you are at this stage with a collaborator, because you start to tell your collaborator your ideas. At the first time, they do not understand what are the ideas, so you have to formulate in a clear way that is understandable by them. I remember that for my 60 years, one student of mine gave me a present, a cactus, I mean a small cactus, and said this is the way that the idea came out from the mind of Giorgio. Today's episode centers on the math behind complex systems. So many people are passionate about science, but then find themselves intimidated and disengaged at the slightest hint of math, and this might discourage them from their own shot at a Nobel Prize. However, math becomes infinitely more intriguing when intertwined with mathematical notions, animations, and brilliantly planned lesson plans. And that is why I love Brilliant. It is a dynamic and engaging platform for learning mathematics, data science, and computer science interactively. I use it both on the website and on the fabulous Brilliant app, where you'll find a treasure trove of foundational advanced topics like group theory, artificial intelligence, networks, and the course I'm getting involved with, data analysis. It's here to help people fall in love with math and unlock new opportunities regardless of your proficiency. Brilliant tailors content to align with your learning needs, your pace, so you can progress at your own rate. Currently, I'm going through the lessons on the app for their quantitative financial modeling course. It's fantastic and opens up a new set of wrinkles in my brain, a side of mathematical analysis I've never even encountered before. It's a way of gamifying and making the learning process fun. You start the lesson and you're immediately drawn in with Brilliant's fantastic animations and customized pedagogical framework. It's the future of education. To try everything Brilliant has to offer for a full 30 days, visit brilliant.com slash drbriankeating or click the link below. The first 200 of you will get 20% off Brilliant's annual premium subscription. JS Well, I have to ask you about something controversial in your field of condensed matter physics. Although you've done so many things from high energy particle physics to studying starlings, but recently there was a claim of the very first room temperature, ambient pressure, high temperature superconductor. What did you make of the excitement? And what do you think is going to happen with high temperature superconductivity? Do you think we'll have one, you know, in the next few decades? Or do you think it's almost impossible to imagine? Well, first of all, temperature superconductor will be very useful. First of all, for doing toys for children. And also because there will be lots of gadgets which will consume much less electricity. So certainly will be very, very useful. And I feel that, I mean, I do not see any particular reasons for which we should not have high temperature superconductors. Of course, it's clear that this is very difficult. Also, because we really do not fully understand why the actual superconductors that have reason that they are superconductors at the liquid oxygen, liquid air temperature. The reason for which they are superconductors, there are some recent papers that claim they do understand. But I think that the space, the amount of different materials that can be constructed is so huge that especially the moment in which when we have a good theory of high temperature superconductors, I do not see any reason for which we could not have a room temperature superconductivity. Of course, maybe wrong, but I am quite confident that we can arrive to it. I want to just ask about your work that you've been leading to really bring scientific funding in European governments to the high level. One of the topics in the book is how much value that science provides to a thriving society. You talk about in the book, this famous joke by Nobel Prize winner, Richard Feynman, who said that science is like sex. Sometimes it produces useful results, but that's not why we do it. Can you talk about your movement that you've been heading called, and I'm going to butcher this, Salvimano la ricerca italiana. I hope I didn't butcher that. Can you talk about that? What drove you to start this for society? The point was the following. In Italy, the research is not enough funded. I mean, the total amount of money that Italy is spending on research, private and state, all together is a little more than 1% of the total gross income and total gross product. This is something that is opposite to other countries like Germany, which is nearly 2%. France is already half percent more than Italy. Korea is 4%, so one and something is really, really bad for Italy. This is a real problem because with this amount of spending, many brilliant Italians go abroad. They do not remain in Italy because there's not enough money to do reasonable research. They go in other countries, and this is something that makes Italy much worse. So, I've been starting to push in the last 10 years, in the last 15 years, let's say, and more money, maybe 20, more money for research. This is something which many Italian governments did not give more money. The reason is that although research is useful for increasing the national gross product in the long run, it's not in the time interval between one election and the other elections, so they are not really interested in doing that. So, it's something that is really bad for Italy, and we, for example, the movement Salviamo la ricerca italiana, let's save Italian research, was a movement which we started on a petition on change.org, and we got 200,000 signatures asking to get more money to Italian research, and this took a certain amount of time to organize to get this number of signatures, but this, I think, was helpful because it showed to the politicians that the research was important. At that time, I think that this did not have any strong effect on the total amount of money that politicians were going on. The only difference it made, that before people or the politicians were not speaking about research, after the movement, they were saying that we give a research a lot of money, but without increasing the amount of money. So, they understood that it was important to say that they give money to the research. Very good, and then the last thing that I wanted to bring up before I ask my final question, which is kind of a philosophical question, has to do with a quote that you have in the beginning of the book, which was really, it inspired me to write a tweet, which is online. I said that, why do we need to have science communicators, people whose job it is professionally to communicate science? We don't have that with movie stars. We don't have that with football players. So, why is it that science needs someone to make science more popular? And I got a lot of hatred online. People said, oh, that's stupid. Movie stars do get paid to go out and do it. And I said, well, yeah, that's proving my point, but scientists should be communicating more to the public, is my philosophy. And it's not a surprise that we don't get much funding, because a lot of times, we do things to say that we can't really explain it to you as a lay person, because you're not smart enough. Or we say that it's too hard for us as scientists to learn how to communicate properly. And I say that's nonsense. It's hard to learn the renormalization group. So, saying something is hard is not an excuse. So, you said at the end of the preface, you say the following, I wanted to start to emphasize how difficult it is to understand the many phenomena that we observe almost daily and convey that complexity is not about what happens in laboratories. It is what happens all around us. Our job as scientists is to illuminate for everyone the truths we discover. Can you say, if you agree with this, I believe scientists have a moral obligation to communicate what they do in terms that people that fund us can understand. Do you agree with that? Or do you disagree? And if so, how? No, I fully agree with that. And I think that scientists have to understand that if they do not communicate with people what they are doing, the funds will stop eventually. So, I think it is certainly a moral obligation, but also a long period of need to communicate with people. Because science in these days costs a lot of money, and we can think of some kind of maybe not very efficient way in which technologies go on without science. And this is something that may be difficult, but may be possible. Or you may have a situation in which both technology and science escape from small countries like Italy. This is also another possibility. So, I think that it is extremely important. I agree, fully agree. It is a moral obligation and also convenience for them to communicate. It is not easy. I mean, one has to study, because also communication with people should be done also in a fast way, because you have to get the attention of people. And therefore, it is not easy to get the attention of people. And also, because as a scientist, you normally are accustomed to use written words. And also to speak with people that are interested, like scientists. Now, the real problem for scientists to communicate is to get the attention of other people at the moment that they start to communicate. And that is the thing that makes things different, because other people get immediate way just looking to them in the face. You are interested in what they are doing, but not scientists. JSC Georgia, that was beautiful. I really appreciate your time. And there's one last question before I'll let you return to have a Buona Sera. And that's the question I like to ask my guests and ask them to give themselves advice when they were 20 years old, 25 years old. And it's based on the name of this podcast. So, this podcast is based on Sir Arthur C. Clarke's Third Law, which states, the only way of discovering the limits of the possible is to venture a little way past them into the impossible. So, I want to ask you a question, Giorgio, for your former self at age 25. What advice would you give him to have the courage to do as you've done to go into the impossible? What piece of advice, if you have 30 seconds, with 25-year-old Giorgio, what do you say to him? This question was already asked to me. And after some thought, I say that I will not give any advice. Because I've been very lucky in the choice of things to study in my trajectory, and to hear some say, I mean, I think that there's a lot of luck. And I think that any disturbance of the trajectory would be very likely to have a quite negative effect. Well, that's very smart. Because here we have The Simpsons, a very famous cartoon where Homer Simpson goes back in time, and he steps on a bug, and he goes, stupid bug, you go squish now. And then fast forward 60 million years later, and humanity is a servant of all these bugs. So, Giorgio, I want to thank you so much for this wonderful book, for the inspiration to millions of people around the world. You made so many people happy when you won the Nobel Prize, but really for the work that you've done and this fabulous book. And I hope we can meet someday in person and have a cappuccino together. You are welcome. If you come to Rome to have a cappuccino here. Thank you. Mille grazie.