Colorado Innovators: Carl Williams, Principal CEO at CJW Quantum Consulting

[00:00:00] In this episode of The Bear Roars, Dan Caruso sits down with Dr. Carl Williams, one of the architects of America's quantum ecosystem, for a wide-ranging conversation on the science, strategy and future of quantum technology. After helping launch the NIST Quantum Information Program and shaping the policies that led to the National Quantum Initiative, Carl has spent decades at the forefront of the quantum revolution.

[00:00:22] Together, he and Dan explore the breakthroughs that made quantum computing possible, why Boulder became a global quantum hub, and how technologies like entanglement, neutral atoms, and quantum teleportation are moving from the lab into the real world. The conversation also looks ahead to the convergence of AI and quantum computing, and the profound technological and societal changes that may define the next generation. Let's poke the bear to kick off the conversation.

[00:00:51] So, Carl, one of my favorite topics is quantum, and we're going to talk some more quantum today, aren't we? I think we will touch on the subject just a little bit. Just a little bit. So, when we got reconnected recently, you reminded me that we actually were connected before. Let's start there. Let's start that story. Okay, that story was 2004. This was the second time NIST held a meeting with industry around quantum.

[00:01:19] So, 2004. So, that's back when I'm either still at, well, I must have left level three, but that was before I started on my CO journey. So, this was a long time ago. So, 2004. Yeah. And, you know, I don't necessarily recall exactly talking to you, but again, it was a meeting at the Millennium. I see the Millennium's gone. Yes.

[00:01:45] And there were, I think, about 10, 12 companies in the room, and a couple people who would eventually become startups. And the reason you know I was there, you were saying because you looked at your past notes and saw my name pop up. Is that right? I was just looking through some old files, and there's the list of attendees. And here's this Dan Caruso guy from Bear Equity.

[00:02:14] Bear Equity, yeah. So, my interest in quantum was from a long time ago. It was actually a story that was shared when I was graduating from college, my undergrad, engineering at University of Illinois. And some student who had just graduated came and was speaking, and he told this quantum story about to just try to break the ice. It wasn't about quantum.

[00:02:37] But he told this story about the only thing he learned during his engineering program at University of Illinois was that if he ran as hard as he could into that brick wall, he would go through it. The only trick is he would have to run as hard as he could into that brick wall for a really long time. But at some point, he would end up on the other side of it. I'm like, what is this guy talking about? I have no idea what he was even talking about. And it turned out that was quantum tunneling was his, you know, obviously highly unlikely to happen at the human scale.

[00:03:07] But, you know, according to laws of physics, highly unlikely isn't impossible. Yeah, I don't think it's a practice that either one of us care to do. But, you know, if you have an enemy, we could try to encourage him. Yes. But what it did for me, though, is it made me curious. There's nothing better than life. I don't think I'm being curious. You know, curious is what makes you want to learn things and want to know things and want to discover things.

[00:03:35] And for me, it made me leave there and say, what was the guy talking about? And that led kind of almost like a personal journey because it was really just through reading. But I would pick up whatever the latest popular, you know, theoretical physics book of the day was and I would read it. And I think one of the early ones I read was was God in the New Physics, which wasn't a religious book.

[00:03:56] It was a physics book, but it was what is the then latest grace of physics tell you about questions that are typically seen to be questions of religion, like where the universe come from and how will it end and this and that. So that led me on a journey. And then I was just thrilled probably in 2004 to find out how important of a role Boulder plays in the realm of quantum. So why don't we start there? Why is quantum such a big deal in this geography?

[00:04:25] So, again, I think, you know, if you really want to go to the broader community, you start back with, you know, quantum is really quite old. I mean, it's more than 150 years old. But, you know. Well, that's funny you say 150 because 150 would be 1880. Yes. I would have thought maybe 1905 or 1910. But what was happening in 1880? So, again, Boltzmann probably was the first.

[00:04:53] I mean, he could do statistical mechanics if he just assumed everything was quantized. I mean, there was little pieces of this even at the end of the 19th century where people already knew that atoms had spectra. There was other things. They didn't understand any of it because quantum mechanics didn't exist. But you could still see and observe things that made you scratch the back of your head. So, the real birth. Well, let's stay there for a second.

[00:05:23] So, pre-1900, what would they sort of see that would make them scratch the back of their head? Like you said, they sort of knew. So, if you looked at the spectrum of hydrogen, it had lines where it emitted light. Well, how could this happen? I mean, it was quantized. This was nothing from the classical field could make this work.

[00:05:46] And so, there were a lot of quandaries that were the step-ups to what would become the photoelectric effect, which is the 1905 experiment by Einstein. And as I was mentioning before, you know, he's one of the fathers of quantum mechanics, along with a lot of other people.

[00:06:04] But the real equations that came down to create the field is Schrodinger's equation and Heisenberg's matrix mechanics, which is 1925 and 1926, or 100 years ago. And those were the real foundations. And Heisenberg, the name, is one that is very familiar to people now, in part because of Breaking Bad. But what is the Heisenberg uncertainty principle? What does that really mean?

[00:06:33] And both what it did mean early in the journey of quantum and what, in your opinion, does it mean today? Well, the uncertainty principle says that you cannot know everything about a quantum particle. If you know exactly where it is, you don't know anything about its momentum or how fast it's moving. If you know how fast it is moving, you don't know where it is. And this principle and this gives rise to a bunch of things.

[00:07:00] So this is, you know, eventually things like the double slit experiment where you shoot an electron at a little screen that has two slits in it, and the electron appears to go through both slits. Well, how can that happen? I mean, that's not anything we observe classically every day. And just to break that down a little bit more basically for those who are listening in, so if you think of an electron as a small little thing, a small little dot of mass,

[00:07:28] and you, you know, and if you brought that up to the classical world, maybe you can think about it as like a pellet or a bullet. So it's a physical thing. So you would think a physical thing if there's two slits. So two slits that are spread like this, and you made it go that direction and it passed through, you would say, well, if it passed through, it must have gone through either this slit or that slit. But what they found is the answer was... Went through both. Went through both.

[00:07:54] Well, how come one solid object go through, you know, two slits that were physically separated from one another in the classical world? And at the time, it made no sense, right? Yeah. But it kept resulting in the nature of the experiment getting more and more refined, really to the point where that, I think it's fair to say, became the definitive proof point that no,

[00:08:20] whether we like it or not as humans, you know, this thing called quantum uncertainty is real. It's the way the universe really works, even if it makes no sense to us humans. And whether you're looking at a particle like electron or a photon, a single quantum of light, many people feel with light that they prefer to think of it as a wave. And then you can see this double slit experiment, but you can also see that wave as a particle again.

[00:08:49] And so you can design the experiments. And, you know, this is, of course, the quandaries of quantum mechanics. And those early quandaries are still with us. But there were stranger pieces. Those stranger pieces are the ones that really bothered some people like Einstein, as I was mentioning earlier. Einstein spent most of his career trying to prove quantum mechanics incomplete because he didn't believe that the world,

[00:09:18] that God will die. I mean, this is this God piece again. And the expression, he didn't believe God will die. He didn't believe the role of chance in how the universe worked was real. That is like, no, that can't be. There must be more to the equation, more to the understanding of physics that will reveal that things aren't really left to chance. We just don't fully understand it.

[00:09:47] There must be some underlying force at work and we just haven't discovered it. So he spent, as you said, the better part of the end of his life trying to, you know, trying to make the case that there's something more that we haven't yet discovered. But eventually he became a believer, right? I don't think he ever really became a true believer.

[00:10:08] You know, one of the other interesting pieces is, you know, in 1935, he, Einstein, along with a guy named Podolsky and another one named Rosen, created this, wrote this paper. And, you know, within a few weeks of writing this paper called the EPR paper for Einstein, Podolsky and Rosen, Wolfgang Pauly, another one of the great founders, came back and said, well, Einstein has spoken again publicly about quantum mechanics. Every time he does, we know it's going to be a catastrophe.

[00:10:38] So there were those who all along, and of course, it wasn't easy. So quantum mechanics itself is hard. And then you... If it's hard for Einstein, it's really hard for us. Oh, yes. And it gets more spooky and odd when you go away from quantum 1.0. And so quantum 1.0... Well, let's stay on ERP for a second, because that was a famous multi-year set of debates back and forth, right?

[00:11:06] I mean, there was the ERP, and I can't remember the specifics. So ERP... EPR. EPR had a certain proposition, might be a certain hypothesis that they believed to be true. And then the other person you mentioned, and maybe one or two others, said, no, that's wrong. And then it was like, who's right or who's wrong? Is that the right way to think about it? Yeah, there was a lot of discussion about this interpretation.

[00:11:31] And eventually, a mathematician named John Bell came up with a simple proof that... But what was the... What was the... Before John Bell came into there, what was the... The argument. ...gap between the two understandings, do you recall? So the problem was, the CPR thing was the first kind of thought experiment about entanglement. And so you created a very strong relationship between two quantum particles.

[00:12:00] And then you can separate these two quantum particles, and you somehow... The act of measuring one seemed to determine what was going to happen with the other. And how could this happen if they are light years apart? Yeah. How could this kind of magic occur? The spooky action. And at a distance. Einstein referred to it. Yes. Sarcastically. He did.

[00:12:27] I have to say, you know, as a graduate student, it didn't bother me so much. But I remember once a wise old professor says, the problem with you young people is you just accept this too readily. That correlation basically gives rise to the enhanced power that is used in modern quantum theory for building quantum computing. You just shifted the word correlation.

[00:12:56] But first you said something different in correlation, which is a really important point. You said something here seemingly affects something there. And we'll come back to that. Use those words because that was part of, I think, Einstein's thinking that connection meant like, you know, if something here could cause something here to happen instantaneously, you know, not constrained even by the speed of light. You know, like what force here could act upon something there. Something so far away.

[00:13:23] And if so, does that mean you could instantaneously go from one place to another or communicate information from here to there? Not even constrained by the speed of light. And he's like, that just can't be. But then you use the word correlation, which is something different. Yeah. So maybe just make the distinction between those two. So if you have brought two particles together and you entangle them in a way that there is

[00:13:51] a very strong correlation, it doesn't matter how far apart, that correlation will be conserved. And so it's by force of nature that it must come out this way. And this issue about information is you find, and again, people bring this up, this issue of, well, can I instantaneously communicate this way? And the answer is no.

[00:14:18] Because without a classical channel, you can't ask what that measurement means. You can't give any inference to it. So on average, it looks just like noise. Yeah. So if you're on one end of the entangled set of particles, if you're on one end and you learn

[00:14:42] something here, you do instantaneously know with certainty something brand new that exists over here. Okay. You know something, right? Well, you know something, but I'm willing to show you how this creates a problem. Yes. Because this act of measuring, and so Alice is in Paris with her particle and Bob is in Tokyo with his, and Alice measures her particle.

[00:15:11] Well, what Alice didn't know is that when Bob was getting on the plane to go to Paris, he'd already measured his. So hers had been determined the whole time. You see, you never know who did what in that picture. So no violation of causality, which that would have really bothered Einstein. This is the thing he didn't want. He wanted to be sure that the world was causal. And so, yeah. But it's still a crazy notion, right?

[00:15:39] I mean, it's still a crazy notion that whether Bob did it first or Alice did it first, once one of them learned a piece of information that otherwise was unlearnable, right? It wasn't like they just discovered or existed. The information wasn't yet settled. It could have been blue, it could have been red. It could have been one, it could have been two. You know, they didn't know what it was. That's correct. But once either Alice or Bob kind of knew over here what it was, it was red, not blue,

[00:16:07] they knew instantaneously from where they sit what the other one was. You know, this is red, therefore that one's red, or this one's red, therefore I know that's blue. But the problem is, you know, just because you know it's sitting over here, how do you use that as an information channel? Well, you can't. You know, you can't just, you could shout really out, I know it's blue, right? And you will know with certainty.

[00:16:32] But I think the other important thing that I think is hard to convey is until you did that, neither site could have known. It was unknowable by anything until it became knowable. But once it became knowable, both sides were knowable at the same time. Okay, so now, so does it matter? You know, does that even matter that that happened? So how is that useful? What is entanglement? You know, if it's not one where you could communicate instantaneously or, you know, or

[00:17:01] travel instantaneously, what can you do because of this property called entanglement? So in the modern world, and now we're talking the last roughly 30, 40 years, people have been using this entanglement to build a new kind of computer, a quantum computer. And in the absence of entanglement, I cannot build that computer. And what this entanglement gives me is an ability to use the quantum world to process information.

[00:17:31] And in fact, this is one of the things that moved us from quantum 1.0 to quantum 2.0, was a realization that basically all information, including classical information, is physically limited. So information belongs to the universe. And whether it's classical information as in a classical computer, or it's quantum information. And so the quantum world processes information.

[00:17:59] And in fact, it can process information in a way that is far more powerful than any classical computer. Now, it doesn't mean you're ever going to do word processing on this quantum computer. You just gibberish out the other end. And of course, some people listening to this might be thinking that we're talking gibberish already. But it's guaranteed in the quantum computer that if you try to do word processing, you just get gibberish. So how... I'm going to challenge you on that in a little bit, but we'll come back to that later in the conversation.

[00:18:28] How do you utilize this entanglement to do something useful? Well, clearly, the first person to think about this was Richard Feynman. And he says, well, if you want to compute something quantum mechanical, this is the way to do it. But it has become clear today that there are other problems like breaking encryption, especially public key or the asymmetric things that we use to validate ourselves to our bank or to

[00:18:57] digitally sign something to break that encryption. So it's really quite powerful. Figuring out how to exploit it and use it for something useful is non-trivial. A lot of fun. So the very old TV series, Star Trek, had a problem. And the problem was they had a low budget. And since they were building a series about traveling around the starship and needing to

[00:19:26] kind of go from the starship down to various planets and didn't have a budget to show how the starship was going to land and take off, they invented this thing that was called Beam me up, Scotty. You know, and all of a sudden something would evaporate over here like Captain and it would reappear over there on the planet and back and forth. Beam me up, Scotty. What does that have to do with entanglement?

[00:19:52] So the idea of teleportation also uses entanglement to do it. Yes, quantum teleportation. But the thing is, when you understand quantum teleportation, and believe me, this can get very confusing. I have been told that I wasn't thinking big enough when the person from logistics in the Navy wanted me to teleport his ship. And so you start trying to explain why you can't do simple things.

[00:20:23] So the teleportation... Why we can't do it? Or why... It can't be done. Can't us a thousand years from now not do it? Physically, it cannot be done. Oh, okay. This could be interesting because that's new information for me. But you can teleport information. So you can make information that's appeared. I thought information was... I thought the line between what is physical and what is information is like a blurry line. So the problem is, is if you think of a physical object like a glass of water or something else,

[00:20:51] there's 10 to 23 particles in it. And if each of those... That's just a quantity issue. That's an engineering problem, not a theoretical physics problem. Oh, no. It is a real problem because if each of those atoms was just a two-level system, two to the power of 10 to the power of 23, well, that's more particles than there are in the universe. Eh, not possible.

[00:21:22] It is interesting that you can actually teleport information. So what do you mean by information? Like, can you teleport a molecule? No. If I can teleport... If I have information in a quantum system here, I can make that information reappear in a quantum system over there as long as I learn nothing about the one that was in the first position. So it's just the movement of that information, all within a light cone.

[00:21:51] Never again... In anything else, classical channels required, all the other tricks are done. You're still constrained by the speed of light. So the speed limit of the universe, you know, because of entanglement, there still needs to be a classical communication channel open, and classical communication channels are constrained. But essentially, because I thought they did do teleportation, climb teleportation, at the molecule level.

[00:22:19] I thought that was done here in Boulder some 10, 15 years ago. So here in Boulder, they had a piece of information sitting in the cubit here. It was an ion. And they made it appear over here. But it's only the information moved, not physical... So what happened to an ion over there? It was left in an unknown state because it had to be... No, it didn't evaporate. It was just still there.

[00:22:49] But the information that it was holding was gone. So an ion's the biggest... Would you call an ion a piece of matter? Yes. I mean, it's an atom, so a piece of matter, an ion is just a charged atom. Okay, so they took what was... Coded. Coded within that ion. It, constrained by the speed of light, by the communication channel.

[00:23:18] An exact replica of that information... Appeared. Appeared over here. But in doing so, what was there... It wasn't a copy. It was gone. What was there went away. And it basically manifested itself over here. That's correct. Okay, so... Why are you so convinced... That... That... Future...

[00:23:48] Intelligence... Human or... Otherwise... Isn't going to use that to do stuff that looks like... And appears like... The physicality of what was here... Was replicated... In a physical sense over there. Yeah. Obviously, they would have to have material available for that to happen. But... You know... But why are you convinced that that isn't something that is an engineering problem to be solved over a long period of time?

[00:24:19] Because you can't move matter. Make matter just go from one place to another. I didn't say move matter. I said the manifestation of... The manifestation. What looked like that glass over here... In a perfectly replicative way through quantum teleportation. Kind of... No longer existed here because it lost its identity. But replicated here through... Through the quantum teleportation process. Yeah. It's...

[00:24:49] You're physically not good. So when... I didn't say the... Matter somehow went from there to there. But the... The... Content of information. The disappearance over there. And the reappearance over there. In a way that was... You know... Pretty much an exact replica of what was no longer there. It is now here. So the ideas, the concepts, the information content can move. Mm-hmm. But of course you can only move that information perfectly.

[00:25:18] If you leave no... Don't leave anything behind. Right. And again, this is part of the whole problem of doing these kind of games. And I call them games because they really are tricks in some ways. Magic tricks. Quantum magic tricks. Engineering. Is another way to call it. But all you're doing is moving the information.

[00:25:42] So if you wanted to take and encode a poem on this side, you could make that encoded poem appear on the other side. It'd be a waste of a lot of good quantum resources. And in principle, you can do that. But you could also just send it via the internet at the speed of light. And the same thing would happen.

[00:26:10] Now, when I send something down the internet, all I've done is move the information. And all I'm doing in this teleportation trick is moving the quantum information from one place to another with the help of a classical channel. Okay. Just like the internet. All right. Well, I'm going to come back to this in a little bit. But we jumped right into it. Now I want to get into who you are. So tell us about your background and why are you so smart about this kind of stuff?

[00:26:40] Where did your interest come from? Walk us through your journey. So I did my PhD largely on small molecules. But after that, I spent a lot of time looking at very cold atoms. And of course, coming from Boulder, you know a lot about cold atoms because eventually there's this guy here. Especially as an investor in inflection and interim CEO of cold quantum. Inflection, which is cold atoms, neutral atoms.

[00:27:09] That's correct. Just went public. We're also investors in atom computing. Cold atoms. We're investors in. Vessant. Scott is the one who reintroduced us. Scott Davis, who's an awesome guy. So yeah, I know a thing or two about layman's view of what neutral atoms are all about. So in the early, after I finished my PhD, I started working on trying to understand what happened when two atoms at very, very low temperatures ever bumped into each other.

[00:27:35] And of course, this became the foundation for whether you could actually make a Bose-Einstein condensate, which was something Eric Cornell did here in Boulder. And got a Nobel Prize for it. That's correct. So even in the late 90s, I'd be out here talking about cold collisions and everything else. People can tell you old stories about me. So tell us what you mean by cold collisions. Cold collisions. And what happens when you have a cold collision.

[00:28:04] So as you cool atoms down to move all their external velocity, they can bump into each other at very, very low temperatures. And in that bumping into each other, they can either have an effect of positive or repulsive interaction. Yeah. And let me pause for a second there. So we think of heat and we think of motion. And heat and motion are kind of two sides of the same coin. Is that the right way to look at it?

[00:28:33] If you suck all the heat out of an atom, it's going to lose all of it. We can think of it as very cold, but we're also going to think of it as very motionless. So if you get it very, very, very cold, motion is also very, very low. Is that the right way to think about it? That's the right way.

[00:28:56] And, of course, some of the first people who really got these atoms to almost stop realized soon that the atoms were gone because gravity still worked on them. And they fell. Okay. Okay. So – and you never get quite all of the energy out of them. They get – there's always a zero-point motion. So you get really, really cold and you want to know what was going to happen if they got really, really cold. If two of them were cold and they bumped into another one. So what was your – before you experimented, what was your theory about what would happen?

[00:29:27] Well, I didn't do the experiments. I did theory. I'd like theorists as better than experiments. Don't tell the experiments in the CU crowd. But it's the theoretical physics people I love talking to. The thing was to figure out whether these atoms – if you had two identical rubidium atoms or two identical cesium atoms or two identical any – whether they had a net positive or repulsive interaction at zero temperature or near zero. And this is what I went to do.

[00:29:56] And this was really – Why you cared about – wondering about that? I cared about it because there was these people trying to do Bose-Einstein condensation and we were going to figure out which atoms they should put into their trap. Okay. And there are those who picked the right atom and those who picked the wrong atom, I would say. Eric Cornell, as we mentioned earlier, they were initially trying to do cesium and they switched to rubidium because the lasers were cheaper. They picked the right atom.

[00:30:24] Rubidium-87 was the atom that could do no wrong. The people who tried cesium, well, you know, those were also great physicists. Eventually, it was Bose condensed, but it had such nasty properties that it basically was not trivial to do. And only after we really understood the collisions there were people able to design an experiment to make it work. And the Bose – tell us about Bose congestion.

[00:30:53] Bose-Einstein condensation. So Bose and Einstein are two people. We know the Einstein name. You can tell us about the Bose name. And they had a theory that they thought this new form of matter would happen under certain circumstances. Tell us that whole story about what they thought it was, why they thought it was important, and then eventually what you're talking about is how we actually proved it really existed.

[00:31:19] So, again, in this room there's all kinds of molecules and they're moving around very fast. And you don't notice hardly anything. You feel nothing or anything else. But if you form this new thing of matter where you took all these particles, these gaseous particles, and you got them so cold and they had a net repulsive interaction, then you could form a new state of matter. And this new state of matter, it was kind of funny.

[00:31:48] I now have this gas, and if I hit it, it will wobble like a balloon full of water. Well, that's strange. How can a bunch of individual atoms all of a sudden move like that? In some ways, this new state of matter is a lot like a laser. It has a phase. It's coherent. They're all doing the same thing together.

[00:32:14] So, it's like a massive dance in which everyone is doing exactly the same movement at the same time. Very, very strange. But, again, something that happens in this quantum world. And they saw it. Bose-Einstein saw it in math, right? They said, well, we believe in the math, and if we believe in the math, there's this strange thing that happens at a certain temperature when,

[00:32:40] I'm going to use your words, particles repulse, and then form kind of this blobby. Absolutely. So, that's kind of a cool thing. Is that true or not true? Well, eventually, it's only true if we do an experiment and create it or discover it. And it took many, many years to do that. So, again, I think that the original prediction was back in the, I believe, late 20s.

[00:33:05] And, of course, it's the experiment here in which Eric got the Nobel Prize was done in 1995. It took 50, 60 years. And so, you were wanting, this obviously must have caught your imagination, or you wouldn't have been working on it, or what was the circumstances that caused you to work on it? So, that whole thing was a massive thing about, can you really do this? What does it mean?

[00:33:34] How do you? It was, you're chasing a challenge because it hasn't been done before. And, you know, there's nothing like doing something that's never been done before. You know, with the fun of playing the game, it's the fun of what I'm doing now. I mean, it's, I want to see things that haven't been done before because it strikes your imagination. It makes you get up in the morning.

[00:34:03] So, as a theoretical physicist working on this problem, you're helping to identify under what circumstances, what kind of, you know, what kind of atoms should you be working on most likely to produce this effect. Tell us about what you were doing to help lead to the experimentation and the discovery. So, a lot of it was modeling.

[00:34:32] And we developed codes and tricks to do the modeling for these systems. And then we would work with the experimentalists to extract the right parameters from the experimentalists. How were you doing modeling back then? You didn't even have, what kind of computers were even available at that point in time? You know, again, eventually a lot of it was done on what people would call mini supercomputers or little things. But early on, some of them were actually bigger computers.

[00:35:02] I mean, some of it was done on a Cray. I remember at one point when I went to do one of the systems I wanted to do, I want to compile. There wasn't enough memory in the computer to make it happen. I mean, these days we look at it and all these calculations would be trivial. But, you know, these days we have a Cray walking around in our pocket.

[00:35:25] Most people don't understand that this is a powerful, that multimillion dollar computer in the year 1992. So, the technology changed quite dramatically. So, I would model those things. I would make predictions. I would work with the experimentalists so we could back out information from the experiments. They would make measurements on things I was doing. And we worked together. And it was a lot of fun moving the ball forward.

[00:35:55] And eventually, of course, new things happen. And from cold collisions, it went into quantum information science and this idea of building a quantum computer, whether with neutral atoms or ions. Do you remember when the Bose-Einstein concept was, when you guys actually knew that it was created? Was there a moment or was it something that just kind of sort of snuck up on you guys? Or did you find out about later because they did it somewhere else?

[00:36:24] So, I think we heard about and saw the data from Eric Cornell and Carl Wyman here in Boulder within probably 24, 36 hours after they had seen it. And the evidence was just kind of overwhelming. I mean, it was everything you wanted out of it.

[00:36:44] Now, having said this, I believe if you just go back about nine months earlier at a meeting here in Boulder where Eric was in the audience and others were around, I told another one of the theorists, yeah, it ain't going to happen for at least another five years. And nine months later, they had done it. Wow.

[00:37:11] So, you know, my ability to make predictions, not so good. Well, that's why I'm going to hit you up on the word processing example. I'm going to describe a situation to you and see if you think it's ridiculous or not. But we'll get there in a little bit. So, what does it matter in today's world that we were able to produce the Bose-Einstein? I'm going to say.

[00:37:39] So, it became some of the tools. Again, the question of what it was useful for. There have been some really nice physics experiments done that are kind of amazing. Building an atom laser. So, the equivalent of a laser but with atoms. Fun practicality? Not much. But the ability to laser cool those atoms, cool them all down, whether it's atoms or ions.

[00:38:09] This is critical to building the technology for a neutral atom or an ion trap on the computer. So, I want to stay there for a little bit. So, we talked earlier about how when something gets an atom, when something gets really cold, it's sort of the equivalency of it losing its motion. So, the first thing you think about is, well, we've got to get things really cold.

[00:38:37] We better put it in like a refrigerator or a freezer. You know, we've got to cool it down. But when it comes to cold atom or neutral atom, it's kind of the opposite effect. What you're doing is you're sucking the motion of the atom. And you're doing it by shining something at it. So, talk us through what that means. Like, how do you make an atom motionless so that it starts to take on its quantum properties? Yeah. And it's a little more complicated yet even than that.

[00:39:06] So, if you remove all the energy from any matter that is neutral in form, it's going to turn into a solid. I mean, you cool down water, it turns into ice. You cool down rubidium atoms, it will turn into a solid piece of rubidium.

[00:39:29] So, to play this little game, I need to cool them, but I don't want them to get so dense that there are three particles ever come together. Because if they do, it will begin to dance and form droplets and do other things. So, the game was, how do I remove the energy from something like an atom? And the answer was, well, you use lasers. Yeah. And let me just kind of double click on what you're saying.

[00:39:55] So, we're all familiar with gas liquid solid. And you're saying, yeah, as a transition states, as you get toward solid, that means they're colder. And that's what makes them solid. But solid, and this is something I've just never thought through until you just said it. But when three atoms get together and get cold, that's what turns into solid.

[00:40:24] But if it's one atom, and you focus on one atom, and you don't let it form into molecules, am I saying that correctly? That's what you're looking to do. How do I get it cold without letting it form into a solid? And so, what happens if you have three atoms, and you bring them together, then typically what will happen is one of them is going to cause the other two to bond. And it's going to take away the excess energy. And now I got two together.

[00:40:53] And the next collision causes three. Okay. This is all condensation. And, of course, then you end up first with a droplet and then eventually with a solid. So, I needed to get these things cold without getting them dense. And so, there are a bunch of properties here that you have to go play with. And you said you needed to do that. You needed to do that because you were trying to...

[00:41:18] Form this exotic piece of Bose-Einstein condensation to other exotic little pieces of physics. And what we're going to connect together now is you were doing it for that purpose. Coming out of that is the whole neutral atom, cold atom, which now is a big branch of not just quantum computers, but also. So, talk more about that. You're doing what to get these individual atoms?

[00:41:43] So, the game was to play a little game using Doppler. Doppler is that, you know, if you hear a train approaching you, you hear it at a higher frequency than when it's past you and going away. And that change in frequency is the Doppler effect.

[00:42:09] And so, what you would do is you'd say, oh, I'm going to shine light on this atom near where it's resonant with light, but just a little below. But because it's moving toward me, Doppler shifts it into resonance with that light and absorbs it. And then it scatters into 3 pi radians. Each time you do this, take a few centimeters per second away from the atom moving. And so, pretty soon, the atom stops.

[00:42:39] These tricks... So, I'm going to slow you down again for the audience. So, you think of like atoms have motion. They're warm, not cold. They're moving around. And now you start shining a light at one. And you're trying to like... So, let's say it's moving towards you and you're shining a light. And you're just fine-tuning, fine-tuning, fine-tuning until you basically... That atom is almost not quite, you know, frozen,

[00:43:07] but pretty close to the point where you now are controlling it largely in space. You're kind of keeping it... And what they really did is they took the light and they would come in from all six directions. So, if the atom is moving this way, it absorbs from this beam. And if it's moving toward you, it absorbs from the beam that's coming from behind you. And if it's moving toward me, it absorbs from the beam behind me.

[00:43:28] So, no matter which direction the atom goes, it's going to run into a laser beam and absorb that photon, take a little small momentum hit and slow down a little bit. This was the game. And this would get you down. And what you're trying to do is basically think of it floating in a certain position. Is that the right way you think about it? Yeah. So, initially this was called optical molasses. It would form this very... Molasses. That's right.

[00:43:57] Very, very system that was very cold and dense, but not still Bose-Einstein condensate. And then they would then use the collisions to farther cool it on down to evaporative cooling, the same way that you're caught the coffee. It's initially nice and warm, and 20 minutes later you're saying, damn, it's cold. Well, not... Didn't lose much, but it evaporated and cooled down.

[00:44:26] And this is what they did with the atoms to form the Bose-Einstein condensate. Yep. So now let's take that forward in time and bring it into the neutral atom or cold atom. Let's say I'm building a cold atom computer. A neutral atom computer. So I want to, you know, I want to use this kind of technique, what we learned from it, and I want to use that to build a computer. Walk us through what that means. So I need to get a bunch of atoms.

[00:44:52] I need to get them cold enough that I can put them in an optical trap or typically these days optical tweezers. Again, just a light force on the atom. But to put that atom into that trap, it has to be very cold. Yep. And so I cool it down. And that's when you say cool it down, you're using these lasers and you're kind of trapping it. You're putting it and you're kind of tweezing it.

[00:45:17] Cooling it way down and then eventually it would just sit in a laser beam, detuned typically to the red of resonance. You can detune to the blue and then you'd have to have a hollow. Yep. So I do that with one atom. Do I do that with another atom if I want to form a quantum computer? Yes. So if you look at these modern things like atom computing that you were talking about, they have hundreds of these or thousands of these atoms in those little tweezers.

[00:45:43] And, of course, then they can move those tweezers together, bring the atoms together and run gates and do other kinds of things. Gates. Create an interaction between two of them to create conditional logic. And, again, this is what you do to build this computer and to do the entanglement and everything else is you have to do one. Gates on one qubit, that is a single atom.

[00:46:13] Gates on the second qubit, which is another atom. On two qubits, which is a two qubit gate. So interacting two of them together at the same time. Yep. And those are the core pieces that you have to do to build this new type of computer. Yeah. So I'm going to break that down again a little bit because there's a lot of people who are trying to understand. People talk about neutral atoms or trapped ions. What the hell are they really talking about? And we are at the core of it right now.

[00:46:38] So we went through a really nice illustration and said, you know, six different directions, shining light, all with the objective of taking this one atom and basically holding it into a spot. Now we said, well, we're going to do that. If you're atom computing, you're going to do that with a lot more atoms. But let's do it with the second atom. You have another set of lasers and you're fixing it into that spot. And then you do it with a bunch more. But now you're going to use these two atoms and you're going to, you know, you're going to start to use the word gate.

[00:47:08] You're going to want to start doing what with those two atoms to create and learn stuff from them. So let's start with first the one qubit gate. And a qubit is just a quantum bit. Quantum bit. Again, the analogy to a classical bit, which is just a single transistor. Single transistor can be either on or off.

[00:47:28] So when I have that atom and it's cooled and it's in its ground state, I can bring another laser in and excite it to a slightly excited state, typically a hyperfine state in these systems. And in reality, I can just put that not into the excited state, but halfway into the excited state. Again, this is kind of a strange little piece of the world. Now you're in the quantum weirdness, right? This is called superposition.

[00:47:56] There's ability to be both on and off or zero and one at the same time. And you look at that and you go, okay, now that's really, really strange. And you say, I don't really believe that kind of thing. Well, I always tell you the reason your global positioning system and you can drive your car around is because of that ability to have superposition. Those atomic clocks, that's how they work. That is called a one-cubic gate.

[00:48:24] And that is part of what you have to do in quantum. The second thing you have to do is be able to take two of these quantum bits, bring them together, and create a conditional interaction between them. Because that's what then creates this entanglement, this EPR syndrome that Einstein so disliked. But again, this is the thing we're going to master if we're going to build this new technology.

[00:48:50] And that has been a ride for a long time, a long, long time. And it goes back to the first gate, first quantum gate done was done here in Boulder by a gentleman named David Wineland, also a Nobel Prize winner just down the street. And is that how he won the Nobel Prize or what did he win the Nobel Prize for? He actually won it for something slightly different.

[00:49:18] But, you know, this was also talked about in his things. He was about the fact that of what they call quantum jumps, that is if you put an atom in a superposition and you look at it, it's either zero or one. And you can, you know, when you measure it, it's always zero or one. And again, this is some of the strangeness of the nature. But he did the first quantum gate here in Boulder in 1995.

[00:49:48] And when you say he did the first quantum gate, what does that really mean? Well, he showed how he could take two of these particles, come together and create this conditional interaction. And, you know, again, you might say, what was the first practical thing ever done with this? Well, by the around 2000, one of the best clocks we had here in Boulder ran off of quantum logic. We were using these tricks to build a better clock.

[00:50:17] And this was an aluminum iron clock. That was, again, an amazing authority force. It was the most accurate clock in the world, right? At the time. And it has been the most accurate clock several times. Other things come along to compete with it. But, I mean, this is how science moves forward. And, again, so an amazing, amazing story.

[00:50:45] And fundamental to all of quantum computing today. If you didn't, until you could do one, you know, you can't even think about building a quantum computer. Because all quantum computers, even ones that use, you know, we talked about a qubit. And in this case, the qubit was the atom. But lots of different varieties of what you might use for a qubit that are being worked. But they all come down to this, you know, this idea of being able to engineer a gate, right? So you asked a little bit about me.

[00:51:15] And so I'm just going to take this into a little side story. So you've heard of the Dream Team. Yes. Yes. The basketball Dream Team. Yeah, yeah, yeah. I have my Dream Team. Okay. So in the year 2000, I agreed that I would coordinate a program that was to be built around a special program inside NIST where the NIST director gave a group of us a little over a million dollars.

[00:51:44] Now, the group was Bill Phillips, who won the Nobel Prize for laser cooling. Eric Cornell, who had not yet won his Nobel Prize. Who eventually did. David Wineland, who had not yet gotten his Nobel Prize. Charles Clark and Paul Julian. And I said I would coordinate the whole thing. This was the beginning of my effort into quantum. That was my Dream Team. Yep.

[00:52:11] You know, you can never end up with a team like that just by, well, only by luck. Yeah. But that was the beginning of NIST's program in quantum information. Nothing's only by luck. You had to know who you wanted on your Dream Team. You had to convince them to be on your team. I'm sure there's a lot more than just luck. Luck that you had access to those kind of people. But access doesn't mean. Yeah. No. Look, it was fun.

[00:52:42] We created a program. Dave Wineland had already done the first gate six years earlier. We created the largest, as they called this best program, was called competence program at the time. But at that time, this was the first time NIST director had ever put a million dollars on one of these. And our idea was, within five years, to show that we could entangle ten of these things together. Well, we only got to about five or six in ten years.

[00:53:11] But it was a long, difficult effort, and it was a lot of fun. And that was the beginning of the program at NIST. I point that out. Well, let's talk about, you want to entangle five together. Let's break that down. Because entanglement is such a thing today, right? I mean, we're starting to scale quantum computers, which means we're doing more and more entangling within. So a quantity of entanglements that are being engineered and controlled is becoming increasingly higher quantities.

[00:53:39] But you guys were out to do ten entanglements. Never been done before. Or, you know, and your goal was ten and you took a period of time to get to five. Walk us through that. Don't just skip through that. That's a big deal. So when you create, when you get one of these programs, you have to promise something and what you're going to do and why it might be important. And there was the clock application.

[00:54:04] There were some other things about seeing whether you could actually build a quantum computer. And so you're just starting down the path of seeing whether any of this is possible. You know, it's a challenge to do something that's never been done before. You want a number of different approaches. We had Dave Weinman who was working with ions.

[00:54:32] Bill Phelps was working with neutral atoms. Paul Julian, Charles Clark did theory. And we just started this big effort to do this. And the NIST director basically came along and said, well, if you're going to do this, you also have to build a bigger program. And so there were other things that came in during those five years, including things like quantum communications,

[00:54:56] sending single photons through the air in broad daylight and grabbing your photon out of the air. That had a bit of information in it. And, you know, again, the techniques and everything else and eventually understanding things like, well, not only do I need that, but I need really good single photon detectors.

[00:55:18] So we have a whole program that was built out here to build the world's first highly efficient single photon detectors. I mean, greater than 90% efficiency. That was a massive effort. So a whole lot of little pieces of tech have to come together to build the empire that is now part of what's quantum computing

[00:55:44] and all the different efforts, whether it's atoms or ions or Josephson junctions or photonics. Numerous modalities are being used. Here are Joseph junctions. We funded a company called Bifrost, who's doing stuff in that realm. Tupa. The Tupa, yes. Yes, I talked to them this morning. Oh, really? Yes, yes, yes, yes. I was at the Quantum Commons this morning. Oh, so was I. We must have missed each other there.

[00:56:12] I was there in, you know, between 8 and 930 with them. That's funny. Oh, I showed up at about 945 because I was supposed to meet with them at 10. We probably drove by each other at some point. So the process of – so maybe I'll tell it in a slightly different way.

[00:56:37] In the year 2000, NIST basically decided that as part of this program that we should pull industry in and ask industry what they thought about quantum. And you can say in the year 2000, you know, there's really no industrial efforts in this area, but IBM shows up. Motorola shows up. You know, there were, again, 20, 30 companies, Lucent, AT&T.

[00:57:06] A lot of people showed up, and there are already companies. I believe the VP at Motorola who was there said, look, we just spent three man years looking at this technology. It's not time for us to act. My question to him was, well, when is it time to act? You know, trying to understand how corporations looked at this technology.

[00:57:32] The reason I'm going to say this is that at that time, people already knew this technology was coming down. And people talk about disruptive technology. Those words get thrown around or revolutionary technology. And the reality is you're an investor. You know there's only a few revolutions every century. Those revolutions are really formal fundamental.

[00:57:58] DNA sync was seen, quite fundamental, changed by biophysics and biometrology completely. Quantum information was known even by then that it was going to change the world in a way that was going to be phenomenal. Oh, there had already been this guy named Peter Shore who in 1994 said, no, if you can build a quantum computer, I can break codes.

[00:58:32] So it was already known that the technology had at least one application. Of course, others believed that it was going to be used for drug design and other things. So we had our first meeting with industry. Learned quite a bit from it. And I think what we started was I met you at the second meeting with industry four years later here in Boulder. And, of course, it was slowly moving.

[00:59:01] What I would say in those first five years, that 2000, 2005, when we had the money from the NIST director, I think we all started out saying, well, this might work. We wanted to see where we could take it. I think by 2007 or 2008, we kind of finally come to a point where we knew that eventually this would become technology.

[00:59:30] Walking that path is long and hard. You're asking yourself a lot of questions. You're showing how ignorant. I mean, if you feel you're not understanding the podcast, but how ignorant we felt, email ourselves. And, again, Bill Phillips would always say, yeah, there'll be a quantum computer. I give it a 50% probability in 50 years. I don't think it's going to have taken 50 years to get there. But it will, if you take the first gate of 1994,

[01:00:02] we have something that has economic implications, not just... Because that means 30 years right now. Yes. Now, I think we're inside of five years. I think we might be inside of three years at this point. I think you will see the first economically useful computation by the end of this decade. So I agree within the five years. I do not believe that, in general, the industry will be paying for itself until the early 2030s.

[01:00:31] So I think that is the timeline. Yeah. And it might be, I mean, if, you know, if, you know, and computing was sitting here, Ben would say, he would take the bet of he will have something that is economically useful that people are paying a lot of money for, not just to do experiments or just to, you know,

[01:01:00] learn more about how to do quantum computing, but to do real solutions to economically relevant problems, he would definitely say inside of three years. Well, I shouldn't say that because I haven't heard him say it, but I've heard him say enough to believe that that is where his head is at. And I am fairly confident by 2028, 2029, there will be a number of valuable computations.

[01:01:27] One of the things that's making it harder, just to be honest, is AI. Again, people said, oh, the first thing we're going to do is some new material, quantum chemistry or something along these lines. And the problem is, is AI is clinging house. I mean, it's making so much progress. Yeah, but wouldn't you also, you know, subscribe to the belief that

[01:01:54] AI is going to be used to accelerate how to both build quantum computers and how to make quantum computers useful that they'll feed off of each other, both in terms of learning how to develop them more quickly, but also the combination of maybe quantum computers kind of discover something that gets you a long ways toward knowing where there might be an answer.

[01:02:21] And then AI takes over from there and is able to bring it home as an answer that they'll, even at the software realm, will kind of leverage each other? Yeah, so I would say AI is already enabling quantum computing. It's used to help improve the quality of the qubits, to tune them up, to find new error correction codes for the things. I think quantum will also help AI.

[01:02:50] And there was a nice paper just about a month ago or so from Caltech group, showing that probably in the future, the way you would do the large language models for AI will be on a quantum processor. So I think... Ooh, that's where I want to come to. I'm going to go there. Well, I don't want to get you off your thought. I want to come right back there because there's something really fundamental in what you just said.

[01:03:13] So what's sitting there is that if you look at the future of computing, it probably is going to involve classical computing, AI, and quantum, which is kind of where you were going there. And they're all going to play together in different ways. You know, there's a lot of classical data out there. You do a little low-level data mining. You pass to AI. It comes up with a slightly better hypothesis.

[01:03:42] You then says, oh, I should go try to build this compound because it may allow me to do high-temperature superconductivity and save the world on energy and everything else. And I pass that to the quantum computer, and I come back. And what you're describing right now, we'll start listening in, is really important because what you described there is how discovery is likely to happen.

[01:04:11] It's likely to happen through this iteration with quantum that starts to discover certain things. The more traditional computing, AI, if you would call that traditional computing, then does certain things, and then it passes back to further discovering the kind of discovery processes leveraging both the traditional computing method and the quantum computing to end up somewhere that probably neither one could have gotten to on its own in that same time frame. That's correct. But here's what I wanted to bring up,

[01:04:39] and that is, what's the killer app for quantum computing? A question that's asked way too many times. It's got lots of different answers. But what if the killer app is conventional computing? But conventional computing, it doesn't require gigantic data centers that require enormous amounts of cooling, but it's a neutral atom, trapped ion,

[01:05:07] form factor that maybe is as big as the room we're sitting in right now and doesn't require enormous amounts of power. But what it's doing is things that you can do with traditional computing, conventional computing. It would just require shitloads more power to do it. And you mentioned maybe it's quantum computers are doing LLM models. Well, that's what's, in today's world at least, that's what's consuming all of the power requirements.

[01:05:36] I know we're not talking three years from now or five years from now, but what if we're talking 10 or 15 years from now? So, you know, there's another little startup here in Boulder called Great Sky. Yes. You know the company? Yeah, we almost invested, but there was some structural stuff that we were getting a little uncomfortable with. But yeah, I know what to do. It's like how our brains work.

[01:06:02] So this idea that you can actually bring down, I mean, at the moment, the cost of doing a classical computation from an energy perspective is just that energy gap that's in the silicon and everything else. There are better ways of doing this than they've been looked at in the past. Yeah. And I think there's... Like the last time I checked, none of us had a big power plant attached to our heads in order for our brain to work. Ah, that's correct. Of course, nobody has said

[01:06:31] that our brains are classical either. Yes. Remember, all information has to be some laws. Yes. So there's always a question. So do you... Would you... Because to me, it's... As a non-physicist, I could say, well, it's obvious that our brains work as quantum computers, but that's not as obvious to people who are in the quantum scientific world, right? That's not a conclusion that you can reach at this point. I mean, there have been people

[01:07:00] who said that the brain was quantum mechanical. I mean, Roger Penrose won the first. But we don't know that, right? We don't know that. No one would say we know or don't know. I think this is one of the great discoveries that will come in the next 20 years. And I mean, if I had to make a bet, and so we'll come back to these issues. We know how a classical computer works based on classical logic, and we understand that you cannot build

[01:07:28] a reversible classical computer unless you have an infinite number of bits because once you erase a bit, you can't go backwards. I point that out because we understand classical processing. We also understand quantum. There is no physical theory for AI. What do you mean?

[01:07:55] Well, there are these things of different kinds of networks that might work and other things, but nobody really understands AI. It does what it does, and it could be just very sophisticated data mining. But again, one of the things that we've come to realize is that all information is physical, so there must be a physical theory for it. Does AI abide by classical mechanics or quantum mechanics?

[01:08:25] Because we don't know of any theory in between. It's another one of those quandaries, and we all use it. Well, you want me to tell you the theory in between? Yes. You heard it second. Actually, that's not true because I heard a physicist speculate on this, so I can't claim it, but I can claim it as only having heard it once, but you know what might be the secret between the quantum world and the classical world?

[01:08:57] And this, again, it's a physicist who brought this up, not as a fact, but as speculation. Something that sounds messy, something we talk about a lot today, especially if you're in the quantum computing world, you talk about air correction. What if, like, if you think about our physical presence here, what holds us together? What makes us, you know, not just fall apart because of, you know, the realms of quantum? What if nature has gotten really good

[01:09:26] at air correction? That that's, it's air correction that is taking things from the quantum realm to what we think of as the physical realm. It's just extraordinarily built into nature itself, kind of what we think of as, you know, air correction in the quantum computing realm, that that's the connectivity tissue between the two. I think ultimately you have to have a theory that you can test and validate

[01:09:55] because that's how we've always worked with physics, whether it's quantum physics, classical physics. And so you eventually have to be able to ask the questions and then remove any other possible explanation. This is discovery. And, you know, it is... But would that be a place to, like, say, maybe there's more to quantum air correction, which is the technique that is being, trying to being perfected to build a function quantum computer. What if there's more to that

[01:10:27] that nature's figured out long before we're trying to figure it out? And that's what's allowed physical stuff to, you know, to exist in the realm of where, you know, we're sitting in this chair and we're not falling through it. Like, what's... What is it that is making this, you know, chair become in permanent form or this class? And what we think of as permanent form. So nature... Nature exploits the laws of physics. Yes. And if you ask what the possibilities are for something

[01:10:55] like the human brain or us, it's either classical mechanics or quantum mechanics. Well, but isn't that just a limit of human understanding today? We think of those as, like, we can't... We can't understand at this point. No one's able to understand where you go from one to the other. But there's... I think you would agree it's hard to believe that those aren't connected. We just don't know how they're connected. I think... There is a continuum there. Increasingly, people understand how complex systems become classical

[01:11:25] and everything else. I think that there's an increasing understanding of this. So I think eventually people will piece it together. We haven't done it yet. So I will come back in. I look at what a classical computer can do. And it's amazing. It's still classical. Just for those listening in, that really means all we're talking about is ones or zeros, on or off, and we're just... Physics is advanced. Like, there's been no advancement

[01:11:55] in computer science from the abacus until now except for... Quantum. That's correct. It's all been around the engineering of how many ones and zeros can you process very quickly in order to make sense of information. But you just said something a little while ago that said, but today's AI is obviously working in the ones and zeros round, but you said something like, or is it? Is something else going on there? Well, they come with weights and probabilities and everything else that highly interconnected

[01:12:25] sets of data coming in to figure out the model weights that go into processing all the information and everything else. But it sounds like you're saying that something else might be happening in what is going on with AI that is doing more with just, you know, a sequence of ones and zeros that it starts to... It starts to do something more to... You're not training it to... You're not programming it the way you would have programmed any other classical computer. I mean, it's...

[01:12:55] It's deterministic is what you would say? Well, I wouldn't say it's not determin... It's probabilistic. It's weighted. It has weightings inside of the kernels and everything else that help you process the information and it's looking for patterns. I mean... Is it looking for... I know it's looking for patterns, you know, and to simplify that again, correct me if I'm wrong, but what we mean by looking for patterns is, you know, this is a gross oversimplification is, you know, if I give you these seven words,

[01:13:25] what's the most likely eighth word? You know, so it's trying to, like, look for patterns and say, this is most likely the right... Next word, next word, next expression, and then you blew that next sentence, you know, next paragraph. It's kind of looking at everything that it can make sense of what has always existed that humankind has discovered, processing all that as quickly as it can to try to make sense of it in a probabilistic way, but it's still entirely in the realms

[01:13:55] of ones and zeros, right? But you seem to have seen something more than that. Maybe not, maybe there's... No, it is just looking at those patterns and probabilities. So you asked the question, when does AI really become truly intelligent? What does it take to become truly intelligent? And can you do that classically? Yeah. I would argue probably not. Probably not, but some, and I agree with you, by the way, and I've thought a lot less about this than you, but thought a fair amount about it.

[01:14:24] And if you were to say yes, that would mean that perhaps, does that mean our brains and our being, do we just, are we just really good at processing ones and zeros really quick? Are we just really great classical computers? Because when you talk to LLMs, you know, when you talk to ChatGPT or Claude, they sure sound intelligent, don't they? I mean, they sure sound like they're doing a lot more than just processing ones and zeros. So... And they sound pretty damn intelligent.

[01:14:53] And they can write damn well, including better than me, and a number of other things. Now, can they actually come up with a new theory? Can they be creative in a way that we have never done? Or even in the way that we do as humankind. Can they replicate us to that deal just on ones and zeros? If they can replicate us, then I would say they truly are intelligent.

[01:15:23] I would argue that we're beyond what a classical computer can do. And so, you know, I think that is an interesting place. But let me just take that because this is a fun conversation. If they're doing what they're doing, they as if it's a being, if AI models are doing what they're doing, it is doing what it's doing just with ones and zeros, and it could get to a point where it replicates us,

[01:15:53] by extension you say, well, is that all we are? Is it really good processing ones and zeros? But what we're saying is we don't think so. We think there's something more going on in what we do as humankind. And if there is, almost by definition the only other thing you'd be talking about is quantum. Right? I mean, you're either processing ones zeros or you're processing qubits. Yeah. Or some combination of the two. And that's where you have to walk and then you ask, well, why can I not get into my subconscious?

[01:16:23] Why can I not know where that next word's coming from? Why can I not think or other things? Well, maybe that's the quantum piece of it because we understand there's some things you cannot access in a quantum world. So, I will come back that, and this is pure speculation, I mean, and you know, these are the kind of things where a bunch of physicists at a conference will in the evening go and have two beers, three beers, four beers, and talk nonsense because they

[01:16:52] can't prove any of it. Yet. Yet. But, like you said, you know, at the end of the day, you have to be able to, you know, for theory to no longer be just a theory, you've got to be able to test it and validate it and explain it. And come back up. And a lot of stuff, you know, maybe not in our lifetime, but, you know, maybe not in our kid's lifetime. But these are things that are going to be discovered, right? We're going to discover, as you said, maybe in the next 20 years how the brain really works

[01:17:22] and the mystery of a kid does it, you know, is there quantum going on in our bodies and what's, how do we physically work and, you know, those are going to be discovered at some point and it's going to be fascinating when it is. Absolutely. So let's, let's pretend we're sitting around a bar at a theoretical physics quantum conference and we're on our third or fourth beer. What else do we want to speculate, especially around how, you know, how the worlds of quantum

[01:17:52] and the worlds of classical, how those come together, you know, where AI is headed. You know, there's this whole concept of physics AI which means how AI starts to interact with physical things in the world, you know, robotics, you know, we talk about, you know, advanced manufacturing, their spaces is going like crazy. So the need for, you know, the physical world we live in as it gets more and more married to even today's, I would say, classical AI,

[01:18:21] you know, brand new things are about to happen. You know, where do you think we're headed in the next five, ten years? Oh, I think from a tech perspective, it's going to be extraordinarily interesting. I think from a social perspective, it's going to be extraordinarily complex. Yes. So I don't think there's a simple answer to this. I mean, I would argue that

[01:18:53] technology moves faster and faster and faster and our ability to adopt and adapt to it is more finite. Why? Well, it took us a few million years to evolve. We probably did not start talking coherently until a few 10,000 years ago. You know, it is not

[01:19:27] we don't evolve quickly. But technology is evolving. But the technology is evolving like this right now and always will. So what do you think is going to happen? So I think we have to spend more time as a society ensuring that people understand what it can do and also developing the respect for each other and everything else to get along. Because when the technology could be

[01:19:56] misused but it only be misused by state actors, the world was safer than when the technology can be used by a single individual with a few resources to basically do massive damage. So I think we have to learn to adapt. I find it in some ways I find it scary. I'm not against technology. I also look at what it can do. I mean, we live longer today because we've learned a lot

[01:20:26] about medicine and everything else. And yet a lot of medicine is purely trial and error. I would prefer that if I have a horrible disease that the doctor can tell me this will cure you and not give me a possibility. So if I was AI and I was starting to get smarter and smarter and I was getting mischievous and I started to get annoyed by humans

[01:20:57] the first thing I would do would be to try to turn humans against one another. They were fighting each other and mad at each other and doing bad things to each other so that I can as AI gain more and more momentum. Part of what I've been telling people is we've got to respect AI which is what you said but we've got to realize this isn't about these versus ours or this ethnicity

[01:21:27] versus that ethnicity. We're going to have to come together more as human as humankind and recognize that there could be this and it might not be AI all by itself. It could be handfuls of bad actors with tremendous amount of resources who are able to harness. We think of harnessing Twitter or X to frame people's opinions but that's like child's play. Those are like kindergarten toys compared

[01:21:56] AI and even AI controlling physical things like an army of drones or something. Those are very real things that humans can have to face up with in a short period of time. I think when you look at the tech and the asymmetry, you're seeing this with the drones and the war and everything else. Shooting a $20,000 drone out with a

[01:22:26] $300,000 missile, it does not seem to make much sense. I think the complexity is going to get there. If we manage as a society to live with the technology and use it, it's a very bright future. Much more wealth, much longer lives. People everywhere, every corner of the world, I was speaking to a class and I said who believes

[01:22:56] that, this is going to be a little bit controversial, who believes that the wealth gap is a big problem? Every student raised their hand. I said, well, you don't see my hand raised. I'm like, you guys wonder why my hand is not raised. They start throwing stuff at me and this and that. I'm like, well, let's be objective here. Are people better off now than they were before? And of course, the answer is, what do you mean? What do you mean

[01:23:26] better off? Define better off? I don't know, are they more healthy? Do they live longer? Do they have more shelter? Do they have more access to food? What people are you talking about? I'm talking about all people in the world. All the planet. Are they better? And they're like, I don't know. I'm like, well, look it up. The answer is yes. Well, when? Compared to when? I don't know, 20 years ago, 50 years ago, 100 years ago, 1,000 years ago, 3,000 years ago.

[01:23:56] Is it because our political institutions have evolved so we have better governance and smarter politicians? Well, hell no, that's clearly not it. If anything, we look stupider now than ever before in humankind when it comes to it. That's not necessarily true, but certainly it's not because of our political institutions that that is happening. There's as much dysfunction in every corner of the world now as there ever has been, I think it's fair to say. So it has something to do with technology. It has something to do with advancement technology. I think we all would be quick to agree with that. Well,

[01:24:26] what's the driving force behind technology? Well, part of it is capital and people who do crazy things and do it at a tremendous scale. That's what's changing the world. And then you could argue about how do you get the best of both? How do you get that to happen? Because the obvious examples lead on most of the world who are making the bigger difference than anyone else, whether you like his politics or not, even things like Starlink has made such a difference in so many people's lives,

[01:24:56] you got to, you know, you got to, it's a much more complex conversation when you start thinking of it through that lens. Yeah. And I think there's also an understanding that when you look globally, again, if the world had to have its modern communication system all done by wire, copper wire, there'd still be a large part of Africa that did not have access to modern communication.

[01:25:26] They couldn't move information and again, information access is equity. Yes, not everybody's equally well educated, but there are people who don't have degrees who are actually quite intelligent. Yeah. But access to information helps make the world more equitable. Let me bring that forward in time if we're going to go there. So we're familiar with the term broadband divide, right? Those who

[01:25:56] had high speed bandwidth had an evangelist, those who didn't have high speed bandwidth, played out over a long time. The government is finally wanting to spend a bunch of money to maybe close the divide. But we have something far more relevant in today's world. We think of everyone having access to AI. Well, that's not really true, right? I mean, certainly we don't have access to the best AI equally. Some people have access to the latest, greatest, powerful models that work because they not just have great

[01:26:26] broadband, but they have great access to the latest and greatest models. But many other people don't. And there's a high correlation between who has economic advantage. They tend to be the ones who have more access to the latest and greatest models to those who don't have the economic advantage. and that could create a huge disadvantage. And advantage to the haves and disadvantage to the have-nots that we can't take 20 years to figure that out. That would be really

[01:26:55] bad. That's already a present problem. And what you really want is that if you are feeling ill and you go into the doctor's office that he has access to the latest and greatest. I mean, again, I think there are those places where the access to the technology raises us all up. But again, not everybody sees it that way. And it is... I think part of the students now who

[01:27:25] are anti-AI, because that's a good thing now, I guess, it's like, you can be anti-AI all you want. AI is here and it's going, whether you like it or not, whether you're scared of it or you're not scared of it, because this is not like, you know, every technology changed in the past. You know, the people who were there thought it was a bad thing and it turned out not to be a bad thing. But that doesn't guarantee that's always going to be the case. I mean, we're dealing with nuclear, you know, with splitting the atom, that's still hovering over humankind as something that could be destructive.

[01:27:56] AI is more like that. I mean, AI, we're going to have to be really... AI could get the better of us. But let me hit you up with one more topic to make it seem more complicated. Every other technology change ever, you know, every other society ever, humans, you know, we're humans, right? You know, maybe some were born to be the child of the ruler and had a lot of advantages over someone who was maybe a

[01:28:25] serfer or something. But at the end day, they're all humans. But that's about to change in that there's going to be people who have genetically engineered advantages and start to have something physical about them. Maybe their kids are genetically engineered to be taller or maybe they're stronger or maybe they're

[01:28:55] smarter because genetics enables that to happen. And even if you try to ban that in your geography, some other geography is not going to ban it. How do you think about that scary future that I think is very real and if it's not already here, it's right around the corner? So, look, again, one understands how we have learned to perhaps even cure

[01:29:25] some diseases because we can do genetic modifications to people. And now you're asking about using the genes to make them smarter or faster or some advantage. So, I'm not sure as a society we're ready to deal with this. No, we're certainly not ready to deal with this. That doesn't mean it's going to happen. No, it doesn't mean it's going to happen. It might happen in North Korea. I don't know where it's going

[01:29:55] to happen. I mean, again, there's been always this idea you can clone sheep, cows, that have been done. Can you clone, you can in principle clone a human? At the moment, we think this is unethical. I don't know the answers to those questions about where the lines are. I think we have to, in some cases, slow down

[01:30:24] enough to be prepared for dealing with consequences. These are real issues. This isn't just like, oh, I wonder what people 100 years from now are going to do. These things are rapidly upon us, and like you said, in a curve that is unpredictable. Let me throw one other thing out there that, I don't know, we're off on a little bit of a tangent, but it's a good conversation, but something that is more on my mind right now in this topic area, where we have versus disadvantages, it's going to be

[01:30:54] really hard for traditional teachers to leverage AI in a classroom. If you've been a teacher for 25, 30 years, 20 years, and now you've got this new thing called AI, what do you do with it in a classroom? You've got third graders, fourth graders, sixth graders, high school kids. That's got to be daunting for most people who are teaching professionals. Some are going to adopt it different than others,

[01:31:23] and there I think you're also in a situation where that may create an unfair and inappropriate disadvantage for kids in a way that's correlated to their economic circumstance, and how are we going to get in front of that? Yeah. I've spent a long time thinking about what tech young people should have, and should a young person have access to be able to AI so they

[01:31:53] can write a sophisticated book report in seventh grade that appears like it came from a college kid? Do they even understand what they've written? So I think one of the problems that you have to come back into is when are you sufficiently along in your education, your learning, to be able to utilize and adapt this and understand what you're utilizing and adapting

[01:32:22] and not just think that you've done something unique. So figuring out how you educate the next generation of children, oh my God, I think that is a very, very difficult thing. I know my daughter when she went to school, they started using computers in like sixth grade.

[01:32:52] I would argue, you know, a lot of people would be better off if they did not have access to Twitter and other things until at least eighth or ninth grade. I would argue that we have to evolve and mature in a manner where we can responsibly use the tech that we have access to. and I think there's an imbalance in our maturity.

[01:33:21] There is. And so I think society is becoming far more complex if you want to know the truth. And I don't know the right answers and I think it's all controversial. I agree with that. I agree with all that. We don't know the right answers. Very controversial. But I'll also say, so I was sitting in a group of people a couple weeks ago at a dinner. I didn't really know the people. They asked me to attend, had dinner with them. And most of them were a bit younger than me. I guess they all were younger

[01:33:51] than me. But they were talking about their kids in school. And these are tech people, right? So one of the guys was really proud to declare that he just went on the school board and they decided that they weren't going to allow AI to be used in their classrooms. I looked at the guy, I'm like, well, that's really stupid. I don't know, like fifth grade or sixth grade. I'm like, that strikes me as really stupid because you can make that decision but I guarantee you somewhere else they're making a decision of how to incorporate AI at a much younger period so

[01:34:21] that kids, and it's going to be really complex, like you said, it's going to be very controversial, but there's going to be, and I've heard some models describe some that I'm really not privy to share because people are running some business plans, buy me, business ideas, but how to deal with the kinds of things you do, how do you do it in a responsible, appropriate way, but very early in the development and people grow up native AI in a positive way, not in a, I just did this really fancy book report,

[01:34:51] I have no idea what I did because it was really Chachi who did it for me. I'm not talking about that, I'm talking about really trained in how to empower them to grow up in an AI native way. They're going to be, that's going to be a different breed my kid's not going to use AI until they're 20 years old. They're going to be like the world they're going to try to get a job in or have a productive wife in and they're not even going to know. I think we can agree that we know what the two wrong end points are,

[01:35:21] the beginning point and the end point. It's need to create nude photos of the cute girl across the room or other things because again, we know

[01:35:51] AI will do all these things. how do you as educators learn to appropriately teach responsible AI? I think one of the other things that I see is the difference from when I was growing up. When I grew up, part of government was also what we would call civics. Today, everybody's

[01:36:21] I know my rights. Yeah, you may know your rights. Do you know when they begin to infringe upon others? And do you understand the civic responsibilities that goes with access to the technology, access to the power, access to the resources, access to everything else, to do it in a responsible way and not in a way that basically demeans or takes from others. Because I think this is where our society is slowly evolving.

[01:36:50] And like you said earlier, we as humans are evolving like this. The technology that we're creating is evolving like this. And that's a big gap. And it's going to be crazy. It's going to be daunting. It's going to be scary. And it's not something we should trivialize. We should be like, this is just the latest technology change. We'll figure it out. It's like, maybe we'll, maybe we won't. point, maybe technology is going to get the better of us and we should approach it with that humility and with that

[01:37:20] eyes wide open. So one last train. I know we're over time, but do you think the laws of physics are fully understood? And if the answer is no, do you think we're close to fully understand them? Or do you think there's going to be just whole new realms of laws of physics that are yet to be even uncovered by humankind? So, no, the laws of physics are not completely understood.

[01:37:50] We have quantum theory. We also understand what is called general relativity or how gravity works, including existence of black holes and everything else. Those two theories are incompatible. And so the unification of quantum mechanics with general relativity will happen sometime. What is known or believed today, and again, this is way beyond my capabilities,

[01:38:20] but you look at people like Kip Thorne and John Preskell, some others, they've been having these arguments for some time, is that whatever theory comes out that unifies quantum mechanics with gravity, that it will have to be informationally sound. Now, there are two possibilities as a result of this. One is that there is yet

[01:38:49] an ability to build an even more powerful computer than the quantum computer, because that unified theory gives you that ability. Two, but it's the same as what we already have, and so you can't go beyond. Well, until you actually have the theorem to prove it, that's another issue. What I would say is the energy scales of that max unification is something that is

[01:39:20] formal for an amount difficult yet than even quantum mechanics. I mean, quantum mechanics spreads a broad range. So, you know, we're not done understanding the universe. We would like to understand the universe, but that includes dealing with disunification, perhaps finding out what dark matter is and dark energy and all these other strange things that physicists

[01:39:49] talk about that probably could make a next good podcast. Yes, it could. All right, well, thank you. This has been a lot of fun. I know it took us on a couple of changes at the end there, but enjoyed the conversation. Love having conversation with people who are theoretical physicists because I think by nature you're just so curious and think about things that are beyond what most people are even able to know they could think about. So, lots of fun. I appreciate you humoring me during it.

[01:40:21] Thank you for listening to this episode of The Bear Roars. Check out Stretch, the new song from Dan Caruso with music by Jason Mendelsohn available now on all streaming services. If you enjoyed the episode, please like and subscribe on your listening platform. This podcast was produced by Loud Bear Productions and edited by Kendall Weinberg with support from Gibson Seagert.