The Technology Bigger than AI w/ Jack Hidary | EP #68

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Quantum computer.

Quantum mechanics. Quantum physics.

Yeah, that's a quantum processor.

And inside are these actual physical qubits. These. There's many quantum technologies that are actually here and now.

These ideas didn't even exist not too long ago.

This is what's possible now. Peter. Okay, we have quantum computers and quantum sensors and quantum security. What is going on here? Underlying all this is quantum information. Science is qis. Our world at a fundamental level is not the Newtonian world that we're used to. It's not the billion volt world that we used to. At a fundamental level, it is a quantum world. We're the first human generation who can finally harness not just the world of bits and not just shaping furniture and stuff in the macro world, but harnessing the ability to manipulate the atomic and quantum world. We are that first generation. Great to see everyone. Wow. This is not a conference. This is a happening. This is.

Yes. This is a community and a conversation about how the world's changing. And then importantly, Jack, something that you care deeply about. How do we use these extraordinary technologies to make the world a better place?

But most importantly, first, Peter.

Yes.

Before we actually speak about quantum, one very important thing, please, for a gathering like this. Does everyone have a drink? Okay. Is the bar still open? By the way, we find that Quantum is more easily digested with a little alcohol.

So you just closed $500 million as, like, your seed round. That's awesome. That's epic. And, yeah, let's give it up for that.

Thank you.

God. We go back a long way, and I'm so. I have no right to be this proud of you, but I'm tremendously proud of you.

We go back, Peter, to the very early days of X Prize.

Yes, the early days.

There's some early X prizes here. Let's hear for X Prize. X Prize. The look on Peter's face many, many years ago when Anousha Ansari and her family. Where's Anousha? The amazing Anousha. There it is. And her family stepped up and gave us enough money not for the prize, but for the insurance. For the prize.

Hole in one insurance policy.

Hole in one insurance. And it happened just weeks before the expiration. Burt Rutan and his team got up there to space and opened up the private space industry. The vision of Peter. Incredible. So thank you, Peter, for opening up. Peter, to honor your commitment in opening up space, we prepared a number of very technical drawings based on you going to space. So I want to show this now. This is Peter Diamantis playing golf on Mars. Now, one of the sides is terraform. Mars is already terraformed, so that's why you have no spacesuit in the other one. I love how stable diffusion created a golf caddy bag that is itself also a spacesuit. I think that is just fantastic. And look at Peter's form here on the right. I mean, just flawless, impeccable.

Well, it's one third gravity. It's 0.38 gravity.

So it's kind of tough. Go ahead.

Yeah. So we had Eric Schmidt on stage with us last year.

Yeah.

And this was just around the time.

We were just about to spin out. Just before spinning out, just about to.

Spin out from Alphabet. And Eric's brilliant, and he's an amazing Persona. What's it like to have Eric Schmidt as your chairman?

Well, we were very lucky. We started this inside Alphabet. And Alphabet was an incredible partner and platform to build this out. First and foremost, you have a lot of free sushi, which fuels the team. And in all seriousness, Sergey and the entire team. Astro, incredible support for more than five years in stealth. Inside Alphabet. Building this out five, six years ago.

Peter, you were inside of Alphabet.

Yeah. And specifically housed inside X, the moonshot factory.

And we've had Astro.

Yeah.

Like three or four times over the years. And I remember I'd meet you there, right. Astro was always on his rollerblades and be there. I was like, huh? Why is Jack here? Now I know.

And I'd be able to say some kind of very general things about. Yes, we're working on some interesting things. That's about what we can say for five years. And around 2020, Eric was wrapping up. First he was CEO, of course, of Google and then chairman of Google and Alphabet for another eight, nine years. And in 2020, he was ready to wrap that up and he came to Sergey myself and he said, of all the things here at Alphabet, 150,000 people, incredible projects, there's one I want to work on for the next decade of my life, and that is sandbox. That is this fusion, this convergence of AI and quantum, two twin engines that will change the world. And we're going to talk about that tonight. He said, if you'll have me, I'll join you guys. And I thought about it for a few months. No, for a few seconds. And Eric became part of the team. And so when it was time to spin out, we all discussed it and we realized this is the moment we needed to drive this growth faster and adoption faster and needed to bring this out to the world. And Eric then took on the role of chairman and myself as CEO. So one of our first things, Peter, one of the first orders of business of any chairman and CEO was to go find an office space. Right? That's a typical thing that we do, right, San Francisco. Yeah. I mean, you look at Palo Alto, you can look at a lot of great. I just came from Austin, another great tech center. So we went scouting Austin. Any Austins here? Yes, yes. Just as with Jay, the president of UT Austin, incredible tech center brewing there. And so any guesses where this location is? And any guesses? Any guesses? So I'll just give you a hint. It's. The sun is setting and rising at the same moment. Alaska is one good guess. Iceland, another good guess, little farther south. Antarctica. Yes. And so of course, Eric and I had to go down there recently and check it out to scout for the various things. But in all seriousness, Eric and I went down there with. We brought actually 15 scientists that we curated from around the world, Peter, glaciologists, whale scientists, penguin scientists, scientists who cover the gamut of the. Not only the climate sciences, but all the biodiversity also. And we'll talk more about that in a little bit. And we have a lot of workers down there, a whole staff of people who are buttoned up and dressed very Very nicely down there. And here we brought a submarine down there, a research sub, and this is one of the first expeditions to actually go underwater and be able to classify. And we actually believe we had with us one of the foremost scientists who studies the southern notion marine life. We believe we may have actually discovered two new species on this expedition. And the whole aim of the expedition.

With personalities and whatnot.

Yeah, the whole aim of the expedition was to bring AI and quantum science to climate change, to the climate science, to the ice science, to the biodiversity science.

You sent me a WhatsApp from Antarctica.

Yeah.

And I'm like, I had no idea where you're down. It's like, why are you going to search for cold for quantum computers or something?

We actually realized that we can actually accelerate the science of understanding what's happening to our planet with both AI and quantum. And hopefully we'll have time today to go more into that. But we did come to a really big epiphany down there that indeed we can make this happen. And the beauty of our planet is very evident down there. This is a snow petrel flying by us and just an incredible place. If you want to take a time machine back to 10, 20 million years ago, I asked one of the scientists with us, I said, if we were here 10 million years ago, if we were here standing on this rock, the rock that we were standing on right there, we don't believe humans have stood on, unfortunately, ever before. This was covered in ice just a number of years ago. And according to the records, we're the first expedition to have an icebreaker big enough to get in to this place and take recordings and data. And so, unfortunately, this is a newly uncovered piece of land. And what I asked a number of the scientists on the trip, I said, because one of them said, hey, penguins. I said, what's the origin of this penguins? They said, they split off and speciated 38 million years ago. I said, all right, 38 million years ago, these penguins, the Adelies, the chin straps, the Gentoos, the three species that we were with right there near that land. And I said, if we were here 10 million years ago on this land right here, near the penguins, if we were here 20 million years ago, what would we see? If we took our sub down 10 million years ago and saw the marine life there, what would we see? And each one of them said, you'd see exactly what you're seeing right now, except for the fact that obviously the ice looked quite different. And so it's amazing to kind of Go back in time into a land beyond, into a place of stillness, Peter. A place that captures what our planet was like for millions and millions of years. And then to start to quantify using these new tools that we have now to understand the dynamics of how we are impacting this planet. So that was really an incredible journey, both in place, but also in spirit. And I encourage folks to go down there to experience this, but also to contribute to the science. We'll talk later about how people can get involved.

Those photos of Eric Schmidt there with his camera and so forth remind me. I took Eric and Larry and Sergey on a trip to Russia, to Kazakhstan, to see a Soyuz launch and it was extraordinary. And he's just with his cameras. I just love his photography.

Yeah. So he's been great. To answer your question, he's been incredible support. And the philosophy that we had both when we were inside Alphabet and now outside is the moonshot thinking that we have so developed at XPRIZE and AT X and the moonshot thinkers in this audience. Everyone here is a moonshot thinker, otherwise you wouldn't be here right now. Everyone is here and have self selected yourself to come here to say, how can I take this kind of thinking but turn it into action? Right. The folks, I see a lot of friends in the audience here. The people here are doers and that's really what we need to make this impact.

Yeah, amazing. Let's talk about the basic concepts right now that we're going to be talking about. Everybody's heard about quantum computers. We've been talking about quantum computers for years. The idea of quantum supremacy was a term that was used along the way. And last year you started saying, no, it's about quantum technologies. That's really what is hot and is going to drive revenue and immediate value. Can you take a second and walk us through the difference between quantum computers and quantum technologies?

Yeah, sure. So I think most people here have heard about quantum computers. You hear about it in the press. There's a lot of buzz around that and there should be some buzz around that, but that's going to be a longer term impact. Build these computers. We have to have error correction. Every one of your phones right now that you're holding, every laptop that you have has error correction in it. Believe it or not, these errors can come from a lot of different sources. Including muons from the cosmos can actually cause some errors in your computers. In most computers we can get away with having three bits for every one bit that we want to signify. And so we kind of Take a vote. Two out of three bits say it's a one. Let's go with a one in case there was an error in one of the bits. But in the case of quantum computers, Our ratio is 1000 to 1. A thousand physical qubits to one logical or fault tolerant qubit. And what is a qubit? A qubit is the logical computing unit of a quantum computer, a quantum bit or qubit. And there's seven different ways to build these kind of quantum computers. And they each have a completely different physics. Some are cryogenic, some are super cold, minus 200 or even colder. And in one case, you have to bring it down to 6 to 7 millikelvin above absolute zero. Okay, so it's really, really cold. Others are room temperature. Right. And so there's lots of different ways to build it. You can use photons, you can use ions, you can use neutral atoms. Lots of different ways to build it. But in general, we're on a quest as an industry to build these things. We decided at Sandbox, Peter, not to build one of these computers because we saw that there was a great ecosystem already building it. We wanted to encourage this ecosystem. Instead, we focus more on the application layer, both on GPUs, the chips of today, and QPUs, these quantum processing units. But beyond quantum computing, Peter, the big picture, one of the big takeaways that I'd love to share with you all today is that there's many quantum technologies that are actually here and now. They do not require error correction. They do not require the fault tolerance that we're talking about with quantum computing. One of those examples is quantum sensing sensors that can detect magnetic fields around us. This blew me away, and we're going to talk about that today, tonight, and talk about how magnetic fields are all around us, including those that emanate from our bodies. Every time you have electricity, electrons on the move, electricity, you have a magnetic field. Faraday taught us that in the 1800s. And so there's magnetic fields coming from our body. Any ideas from the audience about an example of a magnetic field coming from an electric shock in your body? That happens pretty often. Any ideas of an organ in your body that is producing an electric shock? Pretty often about, say, 70 times a minute or 80 times a minute. Any ideas? The heart. Right. And so those pacemaker cells are causing a contraction of that big muscle called the heart, just another muscle, and it contracts and squeezes and blood goes everywhere, hopefully in the right places. And as that's happening, as that's happening, a magnetic field is also being produced. Orthogonal to the electric field is the magnetic field. And that magnetic field is something that we can finally now sense using quantum sensors. And so we'll talk about what the implications are. And then there's another application that really is global in nature and something that we did down in Antarctica with our quantum sensor right down there on that trip just a number of weeks ago. So quantum sensing, Peter, is something that's here today. We're using it right now, and that has not gotten the press. So it's good everyone came to a360 because you get the information right here, right now. In terms of the quantum sensors, there's also quantum simulation. And quantum simulation is the kind of breakthrough technology we need for digital twins of drugs. We'll talk about that as well. So all these technologies, quantum simulation, quantum sensing, these are the kind of technologies that we do not need quantum computers for. We do not need error correction for. And so these are the technologies that we are focused on right now to drive your business. Well, not only to drive business, but to drive impact. Right. Because you know our philosophy. Your philosophy, Peter? Same one. Is that when you drive impact for billions of people, you will have a business. Right. You will have a very robust global business. And our ambition is nothing short, to be one of the most, if not the most impactful company on this planet. Not the biggest company. You don't have to be the biggest company anymore. In fact, what we're showing is that with smaller and smaller teams, you can have bigger and bigger impact, given the forcing factors that you have with both AI and quantum.

So let's rattle them off as quantum computation. We've talked about a little bit. I want to hit one more thing there, and then we'll come back. Quantum sensing, Quantum communications.

Yes. Quantum security encryption. Yep.

Do you put quantum chemistry into this?

So quantum chemistry is that quantum simulation. It's that digital twinning of a molecule of. If we want to do battery chemistry.

For clean energy, it's a group, quantum medicine in that.

It's all in there. All in there, yeah. And so all that is happening right now, now quantum computers as they rise up, and we're encouraging them and working with these teams around the world to make it happen.

Quantum companies are there, you think, out there.

There's about four dozen really strong quantum.

That's about 50, by the way.

Yeah, about four dozen quantum computing companies out there. They've gotten some good funding, and most of them have spun out of really good labs at universities. We're encouraging them. I mentioned there's seven different ways to build a quantum computer. And here's what's great news. The great news is that we see a diversity of ideas out there. We do not see groupthink. What we know for example from the history of technology the last 50, 60 years. Look at the AI winter. Look what happened in 1969 in the first AI winter when a book was published Perceptron that said, ah, this neural network idea, not sure it has any legs. Right. Anyone know the author of that, of that book perceptron 1969 that killed off. Yep, you got it. And so that, and the Lighthouse report in the UK basically said hey, neural networks, cute idea, brain inspired, not going to scale, let's use reasoning and conditionals and if then statements, that's how we're going to get artificial intelligence. And of course that was not correct. And there was a few handful of people who believed still in the idea of distributed networked ideas of neural networks. And those people went to the only country that was funding them, Canada, cifar, Canadian Institute for Advanced Research. And that's why it's not a coincidence that the folks who just got the Turing Award for being the deans of neural networks, Jeff Hinton, Yeshua Bengio, Yann Lecun, where they do all their work, which country? Canada. Because that was the place where you can have a diversity of opinions and say there's another way of doing machine learning. And now we see, and I think you've discussed it here yesterday about GPT and all the incredible things that we now see from that. So it's very important, we're watching very carefully in the quantum phase, Peter, that we stay on course in terms of having avoiding groupthink and having a large number of opinions across the board. That's critical to making sure that we don't too early get into a rut that can lead to the kind of AI winters we saw in such a key. Imagine if we had 25 years of extra research on AI, where we'd be today. We lost 25 years of work. So we want to make sure we don't repeat that again.

Amazing. So why don't we jump into some of these. I want people to appreciate what becomes possible because what you've described to me seems magical. Do you want to start with quantum sensing?

Sure, let's start with quantum sensing. And I think one of the big themes Peter, that I'd love to share with you all tonight is the move from bits to bits and atoms and the tech sector. I'd give us A pretty good grade for manipulating bits, moving bits, creating bits, pattern recognition with bits. Right now, with all the AI and now generating new kinds of bits from other bits. So in the bits column, I'd say pretty good tech sector. But in the area of atoms, the area that actually impacts our lives in a very deep way. Molecule to medicine, battery chemistry for electric vehicles, for stationary storage of solar and wind material science for new kinds of solar panels, we're hitting a limit. New catalysts, new catalysts that do not depend on rare earth, and so on and so forth. This area, the actual world we physically live in, this era, I would give ourselves the tech sector a failing grade because we haven't done much. If you look at the way that we develop and design drugs today compared to 10, 20 years ago, basically roughly the same, same time, same amount of money, same kind of failure rate. We'll talk about in a minute, but let's talk about sensing now, when we look at medical imaging. I started my career at NIH combining physics and neuroscience and AI, bringing those disciplines together to help move forward a field of functional neuroimaging and imaging that was not just static, but looking at a moving image of the brain. Because we went in and with the help of Siemens and Gee and Phillips, we opened up those machines and we tweaked them so we can take images much faster with the physics inside. And those are actually quantum devices. And so we haven't seen a lot more diagnostic revolutions until now. And so let me see if I can move on. And so, yeah, so that's the bits to bits and atoms, something that we need to get to. And I want to now get to sensing here. Let's just jump right here. Okay, here we go. So a number of really, really smart academics about 22 years ago, Peter said, hey, we want to build these quantum computers. We just talked about different ways of building them. But the thing with quantum computers is that to keep them coherent, to keep them in those states of superposition and entanglement, these very, very delicate states of the quantum world is very difficult. If there's a magnetic field around, it'll knock it off its pedestal. And you have to restart that qubit. If there's stray photons around, you'll have to restart that qubit. So some enterprising academics said, wait a second, let's turn that bug into a feature. Let's say, hey, if it's so sensitive to the outside world, let's stop calling it a qubit. Let's call it a sensor. Fantastic. Okay, so they Said, all right, we're going to call it a sensor. And what are some of the sensors they have? I'll give an example right here. It's a quantum diamond. We make these diamonds with our partners. There's no mining of diamonds here. We synthesize these. And this is not the synthesis you'd imagine of taking some carbon and crushing it at high pressures. This is layer by layer, the kind of way we do with techniques that we take from semiconductors and we create layers of carbon. Of course, carbon is one of the primary constituents, right? And in the case of normal diamonds, the only constituent. But here we dope in some nitrogen. We actually keep a spacer. So we have a vacancy and this nitrogen vacancy center in diamond, in nv diamond is a quantum system. The electrons hanging out in that little center right there, we can manipulate those electrons. We can move them from a ground state to a higher state, a quantum state. And again, the thing to remember about quantum what is this world of quantum. The idea of quantize is that it's discretized. These electrons cannot exist anywhere between. It's like rungs of a ladder versus a ramp. A ramp. You can exist anywhere along that ramp. But rungs of a ladder, you're either on this rung or the next rung. And that's what we have over here. We have a quantum system that says if we pop in some green light to give energy to those electrons, we'll move them from a ground state, Peter. We'll move them to an excited state. And when we stop our green light and we let those electrons come back down, of course, conservation of energy, they're going to have to give out energy, they're going to have to release photons. And those are the red photons you see over here. And we can measure with great exquisite precision those red photons. And what does that tell us? Well, what it tells us is the magnetic field, the strength of the magnetic field that that diamond is in or near. And now we have a magnetometer, a magnetic sensor such as we've never had.

On Earth before, with a level of precision. How much?

So specifically, if we have someone's heart, and let's now go to heart, we know that heart is the leading cause of death.

Yes.

Continues to be talking about that globally, particularly in Europe. Us, we have tons of statins, tons of procedures, tons of stents. We still cannot seem to budget this. And one of the things that's holding us back, when we interviewed cardiologist after cardiologist and the folks at Cleveland Clinic and the folks at the leading universities and medical centers, we need better diagnostic tools. How many times have we heard about somebody getting clean bill of health at their great concierge medicine? Three, four months later, heart attack. Why didn't we detect it? What happened there? EKG is not sufficient. The tools we have today are not sufficient. Think about ekg. There's leads on your chest picking up electricity. Now, where did that come from? That came from the pacemaker cells in the heart, which is not attached to the chest, it's not at the chest wall. So it's a very indirect measure. What we realize is we can actually build a box. Here is our lovely subject, Stephan B. Our scientist. Notice that his shirt is on. And there's no leads and there's no wires because we're picking up the magnetic field coming through his bone and tissue. The magnetic field is not dissipated by that bone and tissue. We're getting the real activity directly from the heart. And it turns out that back in the 80s and 90s, an early quantum sensor known as a SQUID, a superconducting quantum interference device. A SQUID, a cryogenic device. Something has to be liquid cooled. You need a Faraday cage, you need a room the size of the stage, and you need to protect it and shield it from the Earth's magnetic field. And then you have people come in, and in Cleveland Clinic in Ohio, they have one of these. And it turns out that you can tell a lot about the heart. And that's why Cleveland Clinic still uses it today. A device that was made 20, 30 years ago. But that form factor does not allow us to democratize it, to scale it, to take it out to the world. One of the reasons why we're so committed to XPRIZE and all the xprizes that take technologies and blow it out to the world is the same reason why we want to take this modality, magnetocardiography, mkg. Not just ekg, but mkg, and take it out in a form factor that's room temperature, that's small, that we can take to clinics in rural areas, take to people all around the world, and of course, take to hospitals all across the us, Europe and other countries. And this allows us to do that. In fact, this is much bigger than we had to make it. We took our initial designs to the hospital. We showed them. They said, don't make it that small. We were going to make it the size of a Rubik's Cube. They said, our doctors will not take it seriously. The size of the Rubik's Cube. So can you put some air around it. So 80% of that box near Stefan is air. Then they said, put it on wheels. Because anything that's wheeled around is taken very seriously. If you wheel it around and it's white, it will be taken extremely seriously. Oh. This device right now is at UCSF Hospital. Anyone wants to be a test subject, clinical trial is open. Join us. We're building up the data now. And here's the beautiful thing, Peter. We don't have to prove its medical efficacy. That's already done by Cleveland Clinic, by others using the previous generation of mcg. But now all we have to show is that this form factor also adheres to that kind of thing. In fact, already today, the standard of care for fetal cardiac diagnostics is magnetocardiography. You can't get an EKG lead into a womb and say, how's your heart doing, Mr. Ms. Fetus? Right. And so what you can do, though, is again, passively listen. Just listen to the heart magnetic field coming out. There's nothing emanating from our box. Already presented to the fda, and the FDA said, we love this first principle, do no harm of medicine. You can do no harm because nothing's coming out of your box. This is a device that is just listening and waiting for the heart to give it information.

Is this a spin out from Sandbox, a partner of Sandbox?

This is. No, this is one of our devices. This is one of our products. Yeah.

Amazing.

And so let me now talk about how the AI and Peter, you and I have talked about this. Where does the AI come in to Quantum? Well, this device is so sensitive.

Again, the name Sandbox. The A is for AI, the Q is for Quantum. The convergence of these two technologies, we.

Had to have both. And one of the reasons why this beautiful technology did not come to light until we got involved is that in the hands of the physics departments. Again, brilliant that they turned this bug into a feature making sensors. But look at. Let me see. I don't think I have a. No. Okay. If you just look in the upper left, that's the signal coming out of the quantum diamond. It's too much information. If, Peter, you're standing just a few meters from the device with your iPhone, you're going to set that thing off. You're going to add to the noise of the device. In fact, our first version did not work. Our first version worked great in our lab. We brought it over to the hospital, failed completely. What happened? We were about 7 meters from the elevators of the hospital, and the elevators go up and down and have electromagnetic portion, which was throwing off our design. Now we could kind of ML it out. We said, you know what, let's go back to the lab and actually redesign it. We did. We're back in there now, and we don't have that interference. But we have to build for noisy environments. We don't want to build for a room that has to be caged in with a Faraday cage. Right. We want to democratize it, bring it out. So when you look at the upper left, you're like, where is the heart signal? And so it took us more than two years of additional ML work to bring it from the upper left to the right. What you see there, ML, is machine learning just to make sure where we can find the actual heart signal. And so this is a combination of hardware and physics and quantum making these diamonds more pure, more homogeneous. When I showed you that one area of the nitrogen and the vacancy, we don't. There's not just one of those in there. There's a billion plus in one cubic millimeter. A billion plus of those dopings that we put in. In one cubic millimeter.

Amazing.

And so this is exquisite technology that I'm really proud of the team having created. But also the ML needed to go from complete noise to finding that heart signal. And so this is what's possible now, Peter, to bring this out and to have this impact.

Are you able to speak about the navigation application?

So just to give a little secret, okay, just to give a little peek, the heart, you asked, how sensitive is this? This is 10 to the -12 Tesla. If you've been in an MRI machine, everyone, I'm sure here has, you've been in something that's either 1.5 Tesla, 3 Tesla, 7 Tesla, maybe even if you felt you had any kind of metal and was pulling like this to the machine, that's like a 7 to 9 Tesla machine. In research, I used to use these Mach, and one time I had small little pieces of metal on my shoes and I almost lost my leg like this to the machine when it was turned on. But that's 1 to 9 Tesla. This is 10 to the minus 12 Tesla point and then 11 zeros and a little one. That's how weak the magnetic field. Yeah. Of the heart is. And if we want to do the brain, then we have to even go even more sensitive. And hopefully that's coming soon. So let's now talk about navigation. Well, what's happening right now in Ukraine, Russia is jamming the signal over Ukraine, and it's not Just there. The signal of gps. Right? Gps. If you want to go on ebay or other websites, you can buy for $700 something that looks like a walkie talkie, but like a big walkie talkie like this. We can jam GPS for the entire area of Terranea with one little device like this. Because again, we know the spectrum of the GPS satellites. And we can have destructive interference where we're sending out a wave that exactly destroys that particular signal. And you'll have no gps. In fact, Qantas Airlines just issued a warning just two days ago, and they said we're getting jammy when we're near the prc, when we're near China. GPS jamming. Our flights with passengers on them have lost GPS due to jamming. Now, why would China be jamming the GPS signal near the Straits of Taiwan? Any guesses? Okay, I'll leave it at that. But the point is that Maersk, the large shipping company, reported the same thing, that when their ships are coming into the port of Shanghai, going various places, they lose signal for portions of their voyage. This is a major issue because it's so easy to jam. So what are the alternatives? Well, you can do dead reckoning, and that's been used for hundreds of years. But we know the drift involved in dead reckoning, right? You can get your astrolabe out. Right. If you can see some stars. But what we realize is that we can be like the bird I just showed you before. There's a tern, an Arctic tern, a bird that travels 24,000km a year in its migratory pattern from the North Pole to the South Pole. Other birds, of course, we know very well, migrating during different seasons. Whales using the magnetic field of the Earth as well. Even turtles. When those turtles are born and they're running to the sea, they're actually using magnetic gradient as well. Nature has figured out that you can use. You can leverage the Earth's magnetic field for direction, for navigation. For birds have figured that out. And maybe some evidence that some humans have a little magnetite left in our brains. Maybe some people can do it, but most of us cannot. And so we rely upon gps. But now we have given humans that ability by having a diamond sensor, the kind of diamond I just showed you before for the heart, the same diamond. And matching that now not with machine learning that looks for the heartbeat, but machine learning that looks for the unique fingerprint of the Earth's magnetic field in every square meter of this Earth. And this was a revelation to us as well.

This blew me away.

Yeah. When we spoke, Peter, to the geophysicists, and we brought them in to our team, and we realized that, actually, I know there's a lot of geeks here. Everyone here is a geek, otherwise you wouldn't be here. So I'll just geek out for a second on geophysics. And it turns out that, yes, we all learned in school about the liquid core. There's an inner core ball of iron, and around that is liquid molten iron, a little bit of nickel in there, and that's sloshing around, creating what's called a geodynamo. And that geodynamo is creating the core field of our Earth. But in fact, there's another modification of that magnetic field. As lava comes up and has come up for millions and hundreds of millions of years and then cools down, the magnetite, the hematite, the ferromagnetic materials in the mantle, as it cools down, modifies locally that core field. And you now have a fingerprint, a unique signature on that spot on Earth.

So every square meter of the planet has a unique. Has a unique magnetic signature that you could map and then use for navigation from then on.

Correct, Correct. And so right here, this square meter, that square meter, every square meter on Earth.

And you could navigate a thousand meters underwater.

That's correct. So when you're underwater, you can't navigate. One of the reasons why the scientists were asking for help down in Antarctica is because when they have their underwater drones, the British Antarctic Survey Bass, as it's called, had two underwater drones at the cost of 2 million British pounds each. Both of them now are broken. Why are they broken now? Because they did dead reckoning and they couldn't see where they're going. And they bumped into various walls and underwater seawalls, and they're both broken right now. Giving the opportunity to have true absolute navigation. Not dead reckoning, not inertial, but absolute navigation. Underwater, you can't get GPS signal more than a meter underwater. And so when you want to go deep more than a meter, you've got to have some way of navigating. And this now allows us to do that. Remember what we said about magnetic field, we said about bone and tissue. It's also true of the water. We can detect that underwater. So this becomes Peter. And right now I'm happy to say that this device that we created is flying as we speak now on a test plane of one of the largest airplane manufacturers on the planet right now. And there's actually a button that was a very emotional moment for us, was when they sent us a picture from this company and they added a button on the dashboard of the plane, on the avionics, there's a button called sandboxaq. When they flip that button up, up comes a magnetic navigation. We're not saying don't use gps, of course, have gps, but if it's getting jammed, if you lose that signal, you can lose it for other reasons, not just jamming. You better have some kind of global backup and it better be absolute navigation. Finally, we can empower scientists as well with underwater navigation and allowing them to do the exploration and data collection that we all need to find out.

Amazing. Everybody, I want to take a short break from our episode to talk about a company that's very important to me and could actually save your life or the life of someone that you love. Company is called Fountain Life, and it's a company I started years ago with Tony Robbins and a group of very talented physicians. You know, most of us don't actually know what's going on inside our body. We're all optimists until that day when you have a pain in your side. You go to the physician in the emergency room and they say, listen, I'm sorry to tell you this, but you have this stage three or four going on and you know, it didn't start that morning. It probably was a problem that's been going on for some time. But because we never look, we don't find out. So what we built at Fountain Life was the world's most advanced diagnostic centers. We have four across the US today, and we're building 20 around the world. World these centers give you a full body mri, a brain, a brain vasculature, an AI enabled coronary CT looking for soft plaque, DEXA scan, a grail blood cancer test, a full executive blood workup. It's the most advanced workup you'll ever receive. 150 gigabytes of data that then go to our AIs and our physicians to find any disease at the very beginning when it's solvable. You're going to find out eventually. Might as well find out when you can take action. Fountain Life also has an entire site of therapeutics. We look around the world for the most advanced therapeutics that can add 10, 20 healthy years to your life. And we provide them to you at our centers. So if this is of interest to you, please go and check it out. Go to fountainlife.com Peter When Tony and I wrote our New York Times bestseller LifeForce, we had 30,000 people reached out to us for Fountain Life memberships. If you go to fountainlife.com Peter will put you to the top of the list. Really, it's something that is, for me, one of the most important things I offer my Entire family, the CEOs of my companies, my friends. It's a chance to really add decades onto our healthy lifespans. Go to fountainlife.com Peter. It's one of the most important things I can offer to you as one of my listeners. All right, let's go back to our episode. And this is probably just, you know, a fraction of the potential applications you haven't thought about yet.

Yeah, there's so many other applications. But I think just sharing hopefully tonight the promise of where this is going and the fact that we're doing this right now, this is something that we invite folks who have ideas. If you have an idea for what we can do with quantum senses, we're open to, you know, brainstorming ideas. That's always been the philosophy at xprize and always been our philosophy as well, to partner with folks and think about new ways of helping the planet in this way. So that's in a nutshell, quantum sensing.

Where do you want to go next? Yeah, give it up to quantum sensing. But I just appreciate again, how these ideas didn't even exist not too long ago. Right. And what this is going to unlock. I remember when Scott Madre at International Space University, one of the early geolocation pioneers, was showing me the idea of geoposition systems and little did I could imagine of Uber or Google Maps. All the applications will be born on top of these things that we can't even imagine yet. And this is magic. And ultimate cost of this is.

Oh, that's the idea. To democratize this, we have to make sure that it's very accessible. If it's once again a multi, multimillion dollar device like you see in hospitals, we have failed. Yeah, cool technology, but not impact. The standard we hold ourselves to is the impact that we have. And by making these devices room temperature and really small and portable. Low power, by the way. To power one of these devices is a couple of D batteries, probably even maybe just four or five AAA batteries. But it's really low power. We don't even have to use lasers. I showed an example there with lasers because it was easier to visualize. But now actually we've converted to LEDs. You know how cheap LEDs are. So a green LED and then it comes out as red and we detect that. So that's really, really easy. But maybe, Peter, we should now Turn for a few moments to quantum security, to cybersecurity, because I know that's on the minds of a lot of people protecting our data. And then just a few moments on that, and maybe then we talk about medicine and how we can really revolutionize drugs. Does that make sense?

Yeah. So, I mean, we have had this buzz in this conversation year on year about is quantum computing, quantum encryption, or decryption going to unlock all of our wallets? Should we be worried about that? And the answer will eventually be yes. But before then, you have some solutions.

Yeah, this is a serious topic that a lot of really good brains are working on it right now around the world. And we're very privileged, Peter, to be collaborating with incredible centers. I just came from Delft in Amsterdam, near Amsterdam, where there's a tremendous center for quantum information. And one underlying theme, Peter, I hope to share with everyone here tonight is that underlying all this stuff, it sounds like, okay, we have quantum computers and quantum sensors and quantum security and quantum. What is going on here? Underlying all this is quantum information. Science is qis. And if we had a moment, just like the Graduate, the movie, and we want to say one word to the next generation, let's say QIS to the next generation. I know it doesn't roll off the tongue like plastics, but it's something that is fundamental to our world. Our world at a fundamental level is not the Newtonian world that we're used to. It's not the billiard ball world that we're used to at a fundamental level. It is a quantum world. And quantum ultimately, now that we're the first human generation, the first generation of people who can finally harness not just the world of bits and not just shaping furniture and stuff in the macro world, but harnessing the ability to manipulate the atomic and quantum world. We are that first generation.

Amazing.

And it's no less than landing on the moon. It's no less than any one of those big breakthroughs that were both conceptual mental breakthroughs as well as the kind of technology breakthroughs. So let's talk about security for a minute. So, Peter, as you said correctly, quantum computers can do many, many positive things in the world. But one thing they also do, we know from a 1994 paper from Peter Shor, a brilliant mathematician who's now at mit, then was at Bell Labs in New Jersey, and a young researcher there, he's in his cubicle and he's checking out various papers that are brewing in this new field of quantum information. And he realizes in epiphany that this computer, once built, will break the encryption that we all use. And already by that time in 1994, this encryption. An example of that is RSA Extra Credit. What does RSA stand for? Extra credit. Anyone here revest Shamir? Someone help him. A, A, A A Edelman. Yes. Good, excellent. So raves Shamir and Adelman. Three brilliant folks from the 70s and 80s came up with this incredible public key encryption. The ability for us to share information over this wild west of the Internet without having to meet in secret. Before public key encryption, what did we have to do? We had to meet in a bunker and we had to say, here's our one time pads. We are spies in East Berlin and we're going to share. Peter, our one time pads. On Monday we will use this key and you will use the same key Monday and then Tuesday we move to the next key and we call it a pad. We take off. Do we tear off the pages of the pad and we use those?

I've seen this movie.

Yes, Bridge of Spies. And what we found is obviously that that's not scalable if you want to build a global economy such as we just did. Since the 70s and 80s, that global economy was fueled by a number of things, but one of the key drivers was public key encryption. Can you imagine if Jeff Bezos set up an incredible company, Amazon, in the Seattle area, and we had to all go take flights to Seattle. Every time we wanted to give him a credit card, we had to go there, drive there, take planes there, ride bikes there, and say, Jeff, here's my credit card. We're in secret. I'm now giving you my credit card. I will now go back home and wait for my package. No, that would not be scalable. But instead, because of rsa, because of this encryption, this asymmetric encryption. Why asymmetric, Peter? Because my public key, which I published over the Internet and Amazon uses, and now in this case, I want to send them a credit card. So I find their public key. I encrypt my credit card with their, with the Amazon public key. Of course, I don't have to consciously do this anymore. The browser does this for us. When you see that little lock, that's what it's doing. And it's sending Amazon and with their private key, a different key than the public key. It is decrypting that. So the whole basis of RSA is what we call a one way trapdoor function. A function that's easy to go one way but very difficult to go back unless you have the trapdoor the private key. And that's been the basis of global commerce. Without that, we wouldn't have the incredible economy that we have right now. And so that Standard started in 1978 and even right before that with Diffie Hellman and some precursors to that. But basically late 70s, early 80s, we had that. And here comes Peter Shor, a Researcher, Bell Labs, 1994, writes a paper, puts it out, and first a few mathematicians read it, and then some cryptographers read it, and then some security people read it, then the government reads it, and then others read it. And everyone realizes, oh, my God, this whole edifice we have just built one day will come crashing down. And nobody knew at that time in 94 would it be possible to build these computers. And so for many years it went by not really gathering much attention until in the last number of years, it became very clear that these seven ways of building a quantum computer that we just talked about were gaining traction. People were announcing new engineering, barriers being hurdled again and again, here, there, everywhere, all around the world. And so it became clear, we will build these computers and encryption will fall. And that means that all of us in this room, everyone on the planet, will have to migrate over. And here's the good news. It's not often, Peter, we can point to a government program and say that worked. But in this case, we can, because six years ago, a number of governments around the world came together and said, whoa, boy, we better have a solution for this, because this train is coming at us hard. And so they got together, made an open call, transparent process, and said, come all ye who have an idea for a better protocol that would not be killed by quantum computers. That was more or less the statement. And sure enough, people came in and was 82 different ideas of how to have a protocol for securely transmitting information just the way we do right now. But to do so that is not breakable by a quantum computer. We call it quantum safe cryptography, or post quantum cryptography. PQC different words, different jargon, but means the same thing. And in fact, after three rounds of culling on July 5 this past year, about eight, nine months ago, the global governments came together with us in the industry and the academics. Everyone said, kumbaya, we have found it. And so the process actually worked. We now have a standard that we'll all be using that is a different kind of encryption. Instead of the hardness of factoring large numbers, that's what RSA is based on, having very large numbers as the public key. And it's very hard to go back the other way, to find the two factors that we use to multiply them together to make this big number that would take billions of years on today's computers, but only a millisecond on a quantum computer. Instead of that regime, we're moving to something called lattice based cryptography, a format that is not subject to this kind of quantum attack. And so we now have the pathway forward, but now the real work begins. This cannot happen overnight. It's not going to happen overnight. In fact, it's going to take a number of years to happen. But now we have a roadway, a roadmap to make it happen. I just put this slide up, Peter, just to show that when you look at banks, banks have been in the news recently. And among the other things, not just the balance sheets and the number of bonds and the interest rate of the bonds and where the interest rate swaps and many other things, but also the IT infrastructure because of the amalgamation of M and A that led to all these large banks. And we could say the same thing about pharma and the M and A and pharma and we can say the same thing about other industries. Telco, as an example. Does anyone remember some of the early telco players? Bell Atlantic, anywhere? Nextelantic, Nextel 9X. Okay. Anyone? Okay, so all these, when they're merged, it looks good on paper. Lawyers get paid fantastic for them. But who actually harmonizes the IT backends. It often never happens. And so what we find when we go in there with forensic tools, we find old protocols, protocols that are not just subject to quantum attack, protocols that have been broken. And we can break it by an iPhone. MD5 SHA1 these are hashing protocols, protocols used to store your passwords, passwords that we don't want out there. And so we find this in banks around the world. We find this in governments around the world, we find this in hospitals around the world. These are protocols that have been broken already. And we need to go in there and identify these vulnerabilities and then migrate them over to better standards. So quantum is a, is a great catalyst. This is the positive news. It's a wonderful catalyst for us to finally fulfill this obligation to secure our data. Every time you hear about a breach, you say, oh, how did that breach happen? How did 100 million records and credit cards and Social Security numbers get out there? It was probably the case that not only was there a firewall issue, but once they got in there that should have been encrypted, it was not properly encrypted so there's been a lot of focus on viruses and malware and ransomware and of course, firewalls. But we now need to pay attention to the nature of how we encrypt the information. Not just how we transmit information back and forth, that's one encryption called data in Motion, but also how we store information, data at rest. This is an opportunity, that's how we see it, of engaging with our world, engaging with our key data that we own, that is our data, our healthcare data, our banking information, our personal data. And so this is the moment now to relook at all that in the next three, four years. And we now need to reestablish the foundation so that we can continue to grow this economy. Otherwise the whole thing comes crashing down. Or we can all take trips to Seattle every time we want to buy something from Amazon. So that, in a nutshell is quantum security.

Amazing. That, in a nutshell is quantum security explained by a brilliant genius.

Thanks.

How far are we from quantum computers breaking today's standard rsa?

Yep, it's a great question and that's why I want to put up this slide here. So there's a lot of efforts around the world to build quantum computers. And it's not exactly as if the business plans of these companies is, hey, venture capitalist Peter, I have a quantum computing idea. We're going to build a quantum computer and the reason we're going to build it is to break the world's cryptography. That's not necessarily the business plans that you see being pitched, but the fact is that no matter why you're building your quantum computer, once it gets to a certain scale, we will start seeing encryption fall. And they're also state sponsored efforts, maybe adversarial, that are building quantum computers and they're open about it and they have thousands and thousands of engineers and scientists on this. And this is open information now on the Internet. And we look at that information and realize that there is no way to control it anymore. The genie is out of the bottle. This will be built because the prize, the brass ring, is simply too big, too valuable. The ability to have a computer that cracks everyone's encryption is simply too valuable. It will happen. There is no regulation, there is no way to stop it at this point. And one of the reasons why we're urgent around this now is this slide here. SNDL store now. Decrypt later. Because if I know, Peter, that one day I will have such a computer and I want to know the secrets of that company of that government of that individual. I don't wait until then. What I do is I siphon off. I don't even have to break into your network. I just say, I know Peter lives in the LA area and I know that he's probably on this isp. And so I'll just go to a hop over here, I'll tap in and I'll just start siphoning information. And somewhere in there is Peter's communications. And I'll just make a copy, just make a copy, make a copy. I can't read it today because you're using RSA or a similar encryption. But I'll just store it now. I'll store it now and then in a number of years I'll have such a computer and I'll decrypt it later. And then when I decrypt it, I say, oh, Peter, FYI, you owe me $5 million in ransomware because I have your data. Otherwise I'm going to release it. Oh, you're a pharma company. Ah, yes. I have all your molecular formulas that you've been transmitting to your factories. I have everything. I know you transmitted them securely at that time, but retroactively now. And there's probably a Hollywood script in here somewhere that retroactively, none of it was secure at all. So this is the concern we have now. This is the concern that governments have. This is why you hear various governments, including our own in the United States, issue directive after directive. In fact, Congress passed a law on December 9 this past year, and amazingly, the Senate passed it unanimously. Does that happen very often? No, doesn't. Unanimously, 100 Eyes said, We approve this law that requires our federal government to move to the new standards. Because of the concern about sndl, that law is now signed. It's now the law of the land. And now the federal government is on the move to make this happen. So the good news is that we have a response, we have a roadmap, but this is the concern. The concern, Peter, is that over the next number of years, these quantum computers will get bigger and better and more powerful. And it's not just little companies making them. There are state sponsored adversaries who have intense moonshot Manhattan projects that are making these quantum computers. And did we announce that we had broken Enigma back in World War II? Did we announce that to the world? I don't think we did. So we may not know when somebody has this computer, but it's too late.

The companies have sent this all and they are. But we now have quantum encryption.

Yeah, that's quantum safe encryption. That's right. And here's the good news, Peter, that we don't need a quantum computer in our hands to be safe against quantum computers. We can do this encryption using your current cell phones, using the current servers. Don't throw out your machines.

But what's the date before which, all of that?

We know that adversaries probably started siphoning data in great levels probably around three years ago, probably around three, four years ago, they started to siphon data. But every day that goes by is another day. And of course, you know that the world's. And you've talked about this, that the growth of how much data we produce in medicine and other key areas, you know, and so this is the moment to start, to start changing now because of sndl. Yeah.

And have the major telecom companies started doing that?

They're starting. Right. So if you have a vpn, if anyone here uses vpn, that P in vpn, the private, virtual private network, that P is currently secured by RSA or similar protocol. So we have to upgrade the VPNs, we have to upgrade Telco. All this ecosystem has to be upgraded. It's a huge amount of work, and this is the work that has to be done collectively. There's no one company or individual who can make this happen. This is a ecosystem that has got to come together. And the good news, I think, Peter, is that this is a moment to relook at all this encryption and say, let's batten down the hatches and let's make sure we have deep security and privacy. Privacy is absolutely critical. And to have privacy, you need encryption. So this is a moment, I think, for us to strengthen the entire infrastructure and take care of years of stuff we should have done. Because of all this M and A.

That went on tomorrow morning is our dive into longevity. We have eight phenomenal longevity conversations. And one of the things that we've been talking about is this decade is different than past decades in terms of our ability to begin to understand at a molecular cellular level why we age and how to manipulate that. Super pumped about this. We heard a presentation earlier from Alex Zavoronkov, the CEO of In Silica Medicine and the work that he's doing in global drug discovery using generative adversarial networks. Talk about this because this is something that you're super passionate about, and I am too.

So I think everyone here is familiar with the stats on this slide. And one stat that people may not be familiar with is not only is there a 2/3 rate of failure in clinical trial. I think most people know that. What people may not know is that 40% fail in phase three. Now, phase three, Peter, we did phase one and that was our safety phase, right? We did phase two, we showed some efficacy. Otherwise we wouldn't get permission to go to a pivotal or to go to phase three. And now we're in phase three. It's a cherry on top. It's confirmatory. We're just here to say, yes, it works now in more than just 50 or 100 people. We're now at a few thousand people or more. We just want to make sure. Yeah, but we have a lot of good news coming into phase three. Otherwise, are we going to spend the four or $500 million on a phase three? No, we would not. And yet we do. And so if somehow I said to you, hey, Peter and I have a new company. Peter makes a company every week and I make a company once in a while. But let's say we had a new company. We had a new company that's a construction company. And the audience comes to us, Peter, and says, build us a new hotel. Build us a new building. We have a construction company, but we say, hey, audience, sorry. When Peter and I build this hotel for you, there's a two thirds chance it will fall down in the first 30 days. That would not be a very promising startup that we have. But in fact, this is what we accept in the biopharma industry. This is what we live with. And I started my life helping to run clinical trials at nih, and this is what we lived with then and, and this is what we have now. We have not materially improved the situation in decade after decade after decade. We have a lot of new tools. We've talked about this, talked about that tool, this tool, but in point of fact, net net. Any guesses, on average per year, how many new drugs are approved by the FDA? Any guesses? I'll start the bidding at 10 new drugs. 38. 50 hundred 10,000. No, 10. So this is a very savvy audience. Yes. About 48, 49. About 50 drugs. And of those, more than half are. Me too. Drugs. More than half are. Hey, Peter, we're on the board of a great drug company. I think we need a new statin on the market. Yeah, there's only 17 of them. And so I think you and I should make a new stand. We should modify one of the current stands, patent it. We should make a new stand, shouldn't we? A billion dollars a year revenue. Why not? And so why don't we see the breakthroughs? Why don't we see it, what's happening? Why don't we see more effort going to pancreatic cancer into very difficult cancers? It's very risky. It's very, very risky. How do we change the game here in silicone medicine is one of the companies changing the game. We need a set of tools that completely the way we think about going from molecule to medicine, this is not working right now. Be it for small molecule or for biologic, for proteins or small molecules, it is not working. And so how do we change this game? And people have heard about digital twins. And so what we realized is we needed to put together a team, Peter, that had the expertise, had the knowledge of how things are done now, but also had the knowledge of AI and quantum, had the knowledge to say we now need to take an AI and quantum approach, a physics based approach that is driven by AI initially, but the last mile must be quantum. Why? Because when one molecule meets another molecule. Here's an example I have right here. Here in this case, Keytruda is a synthetic antibody that you see right in the middle of the diagram here. It's an antibody not made by the body, but antibody made synthetically to plug up that receptor, that PD1 receptor that you see right there. We want to plug that hole. We do not want the tumor to insert the ligand into that receptor. Because if that tumor inserts that ligand into that receptor like a lock and key, what does it do to that T cell? What does it do? What can tumors do to T cells? T cells are there for the fight. They've come to the fight. They're here to do what our immune systems want to do, to destroy pathogens. In this case, it's a different kind of pathogen. It's not a bacterium, it's not a virus. This is something that was a human cell. It has a locking key to turn off the T cell, to put it into sleep mode for enough time for the tumor to grow out of control. That helps us understand why the conundrum of why our immune system has not been more powerful in helping us take care of cancer. We know it's doing a pretty good job. We know the stats that when people are taking immune suppressive drugs, Peter, as you all know, as a physician, for having, say, a transplant of an organ in the two years following that period, in that period where they need to take immunosuppressive drugs, their rate of cancer goes way up. So we know that when the immune system is there, it is pretty active, it is helpful. But in all too many cases, the cancer is able to run away and to evade. And this is one of the methods it uses. That blue and that red spike allow it to go into that receptor and turn off the T cells that came to the fight. And so Keytruda from Merck and other drugs like this do a great job of plugging up that hole and saying, no, we won't let that happen. But unfortunately, this drug does not work for everyone and not for every cancer. So we need to experiment and make new drugs that work for more people, more cohorts of folks. For melanoma, where this was first approved, it works for about 32% of the melanoma patients. It helps them. But in about 2/3 of cases, the cancer, after a while of remission, progresses. When molecules meet molecules, what language do they speak? They speak quantum. While AI based AI driven drug discovery has been very helpful to us in terms of taking a landscape, Peter, of 600 million, say, potential compounds and narrowing it down to say, a few thousand. Now that we have a few thousand, we must ask the next question. When that not just molecule, but now let's drill down further. When we have the atom on the edge of the molecule and on the edge of that atom we have an electron, and that electron meets another electron, does it bind together? Do they meet? Do they bind and with what binding affinity and with what characteristics and what's the conformation and what's the shape and so on and so forth. All these are quantum characteristics. And now we're the first again generation right here in this room and around the planet that can now understand this quantum language. Now you might say, how about the quantum computers? I thought we needed a quantum computer to make this happen. And what we realized and others realized around both academic and industry circles, is that the GPUs were getting so good. The same GPUs that have led to ChatGPT 3 and then 4 and soon to come 6 and 7. Those same GPUs that initially started as what, what's the G in GPU graphical graphics. They started for better video games. So every time a teenager is playing video games, thank that teenager because that teenager is saving our butts. That teenager is responsible for the rise of the gpu, which initially was not made for AI, was not made for quantum simulation. But once we in the AI community realized that the matrix algebra, matrices times matrices, matrix times a vector, this matrix algebra that was inherent in how we can have better video game rendering, we can hijack that for representing neural networks. Neural networks can be represented as an image coming in as a vector and we can multiply it by the matrix of weights in our neural network and our multi layer network. That is the same mathematics in the firmware of an Nvidia chip, of an intel chip, of a Tesla D1 chip, a great GPU that Tesla uses, Amazon has one, Alphabet has one. Many companies. And what we saw five, six years ago is that the GPU wars were growing so rapidly that we would get a GPU that not only was great for graphics, for video games, and not only was great for AI, leading to the GPT revolution we see now, but what we surmised five years ago within our team was that by 2021, 2022, we would have GPUs capable of doing a quantum simulation amazing of simulating this interaction. And sure enough, we published various papers just two years ago and the first time in the world's record for doing that quantum chemical simulation showing hundreds of thousands of electrons meeting hundreds of thousands other electrons in like a speed dating and allowing us to understand what that interaction would be. So this, Peter, is what is now possible. And this is already impacting the folks, the biopharmas we're working with in terms of neurodegen diseases. That's the first one we're tackling right now. Alzheimer's and Parkinson's. We've had 35 years of failure in neurodegen. 35 years. And we need these kind of breakthroughs. We all know in this room how much we need these breakthroughs. But we're not going to get it unless we bring all the tools to the table. And now the combination of both AI and quantum finally coming together to say let's down select from the large numbers that we have out there and use generative AI as well to offer up new ideas. But then test them through the funnel of quantum interaction to say, let's de risk this molecule. Peter, before we go to animal, before we go to human, let's walk into the clinical trial with a much better chance than 2/3 failure.

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Thank you.

All right, let's get back to our episode. So what do you think in terms of price reduction and speed increase?

Well, great question. I think if we. Let me go back here. If we look at these super depressing numbers, the average right now is $2 billion to get molecule to medicine. The average is 13 years to get molecule to medicine. And so we need to bring this down to under a billion dollars. Certainly we're hoping for 4 or $500 million instead of $2 billion. So a 70 plus percent cut in cost. We're hoping for a dramatic decrease in the number of years. The majority of those 13 years are not the clinical trials. The FDA and other regulatory bodies have actually done a pretty good job in the last number of years recognizing the cries of the families, the cries of the patients, the cries of the clinicians. They've said we're going to accelerate. If you have a breakthrough that we can accelerate, let's do that. If we can go with a pivotal phase two and not even go to a phase three, let's do that. And look what happened also in terms of even during the vaccine era, a fast acceleration of approval as well. So what we see is that we've actually compressed the time of clinical trial from seven, eight years. We can now get that done in about three to four years in some cases, if it has an orphan disease or various other kinds of breakthrough status. So that's not the issue anymore. We still need those human trials. It's the 8, 9, 10 years of pre trial work, preclinical work that we need to really compress down. That's what we need to impact right now. That's where we need partners. That's where we need collaboration to make this happen.

Take me a decade forward here. Of the potential in terms of understanding, I mean, the complexity of the immune system, the complexity of even the intracellular mechanisms and intracellular mechanisms, communications is massive. We understand a fraction. Is this going to give us. I mean, we are quantum systems on a. On a fundamental level.

Yes.

Is how much will we unlock as we begin to dive through with these tools? Is this where you expect to see the majority of the breakthroughs of a decade out from now?

I think it's. The human body continues to surprise us. The cellular pathways continue to surprise us. If you've ever seen a complex subway chart of the metro in Paris or New York City, imagine that times 10. If you want to look at cellular pathways times 100. Right? Yeah. So all these different cellular pathways. So we keep getting surprised every time we think, oh, yeah, we've got that down nailed down. Something else pops up. In neuroscience in particular, we're still at a very early phase of understanding. We know so little in terms of neuroscience. We keep getting shocked by new discoveries. Basically, the rule I have is that if I go back to my neuroscience textbooks, I had the privilege of being taught by Eric Kandel, who later won the Nobel Prize because of the work I did. No, I'm joking. Nothing to do with me at all. Eric Kandel was an incredible mentor for me. And also his bow ties are incredible, too. And I go back to that book of all neurologists.

Yes.

Yeah, I go back to that textbook, and it gets thicker and thicker as the additions go. But every time you go back to a textbook and read a word, read a phrase, Peter, that says this never happens. This always happens. That's when you know a breakthrough will happen. Because when we learned in our early textbooks that the brain never creates new neurons after a certain age, well, guess what? That fell down as a never. And so we keep getting shocked and surprised. So what I would say is let's take a humility approach, a humble approach to the body and to the biology. And let's say that let's go step by step in understanding the systems. And the body is an incredible system. We know the tremendous healing power that the body has when you let it use its systems. And that's why immunotherapy, what I was showing before with Keytruda, that is not chemotherapy. It's not there to, in a toxic matter break down. And Kill off so many cells, but it's there to help your T cell keep fighting. Right? In a natural way. That is the kind of therapies I hope we can bring out. But we need a deeper understanding. When we get to the quantum level of understanding this interaction of molecule to molecule, we're just again, at the precipice, as Newton said. I'm just at the tip of the ocean as the waves just come in. I've had the opportunity to play with a few pebbles and rocks on this wonderful beach. And this is how we feel right now.

Amazing.

We're just at the beginning of this ball game.

I'd love to go to some of your questions, please. Head on up. Okay, Steve. You are fast, my friend. Steve Brown, what do you got for Jack here?

So you talked a lot about the physical layer of quantum technologies, and that's where it feels like all the action is right now. And I'm curious, in what ways should we be starting to reimagine the software models based on quantum information theory? For example, an undecided voter is like in a superposition of two states, probably entangled with other people, probably in a contextual field nudging one way or another. It sounds a lot like the same kind of mathematics that you're using for quantum information science. I'm curious when we start to reimagine the software side of this based on quantum information theory, and you marry that with the quantum technologies, like, what do you see in that combination, and what should we be reimagining on the other side of this? Thank you, Steve. Great, profound question. So Claude Shannon, famous for information theory, also at Bell Labs, years before Peter Shore, of course, and his papers, founded the field of information theory, the field that we needed to establish computer science, information science. And then a number of years later, others came after him and quantized that information theory. Claude Shannon, as you remember, was working for Atelco, working for Bell Labs, and his task given to him by his manager was help us understand the communication of information over a noisy channel. And so he did that, and he did that brilliantly. But now we understand that information is much more fundamental. One of the best processes of information is not on this earth right now. It's not a gpu, it's not a tpu, it's not an ipu, it's not a quantum processor. Well, it is a quantum processor, but not the ones we're making here. It's a black hole. A black hole. When we understand a black hole in physics now, we see it as the most efficient processor of information that we have in our universe. And so we've now reimagined black hole physics in this informational sense. So I just want to relate that because that's how profound Steve's question is. This is a deep, deep question that goes to the heart of our new understanding of our physical universe. That at the fundamental layer we have an informational driven layer that drives and helps us understand the context of everything from a black hole to. To a quantum computer on this planet, to our own biology. And so coming back now to your question, yes, a lot of companies are focused on the physics of building these quantum computers. I alluded to the fact that we chose not to do that. And one of the reasons is because of your question, that while those folks are doing God's work to build these quantum computers and we're encouraging them to do that, others of us, including ourselves, need to start focusing on the information layer, the software layer. And one of the things I love about the GPT revolution is that finally we can start getting really good code in a more scalable way without artisanal coding. I call today's coding artisanal. Because, Peter, in five or six years, when I say to you, hey, next Saturday I'll be doing some coding, what you'll know is that I'm doing that in the same way. If I told you today I'm riding a horse, I'm not riding a horse because I need to get somewhere. I'm riding a horse in a nostalgic, artisanal way. And so coding will become that way as well. And this is the opportunity now where we need to create meshed code, hybrid code, code that is a series of lines of information. And part of that code runs on a gpu, part of it runs on a cpu, and part of it runs on a QPU on a quantum processing unit. And this code should be smart code. I don't want to have to put in brackets. Hello, computer, Please run this next code on the quantum computer. It needs to know that so we can think of a quantum computer now in a new way as a subroutine to our main code. Because quantum computers are not good at everything. Please don't run an Excel spreadsheet on a quantum computer. Please don't. You'll not have a speed up, you'll have a slowdown. And so. But there's certain things that quantum computers do extremely well, and they leverage the physics of these quantum systems to do that. These are not transistors. They're not just representing ones and zeros, they're doing something physically. And one of the exciting things now about quantum computers is we're starting to use them in education. And we haven't talked about education yet, which I'd like to get to at some point after some questions. But now in our physics courses when we teach students, we don't just say oh, something could be in a superposition. One of the concepts, Steve, that you mentioned, it could be in some combination of state 0 and 1. We ask the students to take this code that we give them or they write themselves and run it and make a real superposition on this planet right now in a say 5 or 10 qubit machine. That's real, that's not modeling it. That is a real physical system in a state of real superposition. Before us, students can never do that. We never had the ability before this generation to actually have students do that. So back to now, your fundamental question, even as we build the physical devices, we are giving more and more thought to how do we program these devices? How do we mesh these devices into the larger context? Because a quantum computer has no hard drive, it has no screen, it has no keyboard, it has no compiler, it has no memory, it has nothing except the ability to do these incredible things and then return back in information, a piece of classical information back to you gpu. And so that kind of architecture needs new kind of software architects. And so I'm sure it was said here in the AI panel yesterday that it's not so much that AI might replace all of us, it's that we need to now adapt and use these AI tools so that we are not replaced by others who know how to use these AI tools. And the same thing now could be said in quantum. We need to make sure that students today, that we ourselves up leveling, upskilling ourselves. And none of us in this room have to know how to code. We need to know what the computer is capable of and how to architect a quantum system into the system that we are designing. Thank you Steve for that question.

Amazing. Kurt, let's go. New next.

Thank you. My name's Kurt Max mind hailing from Australia.

I've got a question about your sensor.

And I don't know if many people know, but to get to net zero.

2040, 2050, we need four times more metals than than we mine and recycle today and six times more by 2050. Like you know, 16 times more metals.

To build an offshore wind farm than.

Gas fired power plant for the same scale.

And one of the challenges, metals for Batteries, things like that. You're talking about batteries, steel. Like it's something that even if you.

Build a new material, you need millions.

Of tons of this material to build those things.

And to find these resources is very hard.

So about 20 years ago, Falcon magnetometer flood, very hard to find it.

So is your sensor capable?

Because given the sensitivity to detect more.

And find more of these resources, so we pick better places to mine, is the question.

Yeah, well, great question. And I'll even broaden that question beyond just sensing for mining, but also sensing in general for on a geophysical scale. So imagine you wanted to know underneath the Earth what the densities of the materials are underneath the place on Earth that you're hovering over. Maybe you have something called a balloon that you're hovering over a piece of land. And you want to know is there a different density that might house a certain thing called a missile underneath that thing, if you wanted to do that. Or you might be looking for mining for metals in your case. And so if you wanted to do these things, you can then use this kind of quantum sensor. And it would be advantageous to use that quantum sensor at different altitudes. And so that's one reason why we think about these different platforms of passing sensors over different parts of the Earth. And also, of course, underwater, you'd want to know what the composition was of the mantle underneath. Right. The crust underneath that sea, that ocean, to understand what's there as well. And so these sensors do give you, not just through the magnetometry and then through adaptations bringing it to gravimetry, you can actually detect what the density of the materials are in different spots. Just like we talked about how every spot on Earth has a different magnetic fingerprint, every spot on Earth has a different density fingerprint as well. And so this is absolutely possible. More work needs to be engineered in terms of the harness or the capabilities that you might want to put around it. But certainly what you'd want to do is adapt the same sensors we talked about here, adapt the GPU chip that goes on board, and then just train the machine learning models. Instead of looking for the heartbeat like we talked about, instead of looking for navigation signals, you're now looking for a different signal. And that's the beauty of machine learning, that we can adapt to that new context. And so absolutely, already there's been a number of papers going around in terms of detection of what's going on underneath the Earth, again, for various reasons, not just mining, though. Thank you.

Amazing. Jared, let's go to you.

Hi.

Thank you so Much for all you do, both of you. So I have five year old twins with spinal muscular atrophy, which, which is.

Kind of like ALS in children. And.

Though there have been some amazing breakthrough drugs just recently in the last few years, anyone like my children who did not get that treatment really early.

On, like in the first few weeks.

Of life, a lot of neuron damage has occurred and there's a huge need there and in all neurodegenerative diseases for neuron regeneration and drugs or methods that would do that.

I have a healthcare doctorate, but I'm.

Not a research scientist.

I don't have a lab or I'm.

Not an AI expert and I've made some really exciting connections here and have some ideas about how I'll move forward. But I wanted to ask you, what would you do if you were in my shoes? How would you move forward to help your children and others like them for neuron regeneration?

You want to start?

We're going to have a few presentations tomorrow morning. It's really. We have two presentations tomorrow, one on a company that's basically in the regenerative medicine side of the equation from a stem cell exudate basis of how do you actually get these going? Another one which is based on technology out of Tufts that is regenerating limbs. And I think the question becomes, does the body have the ability to regenerate complex systems? Because you're not just regenerating the muscle, but it's the nerves and the connections there. Is the information for that early embryogenesis still there and can it be reactivated? So there's a company called Pharmaceutical Amorphousuticals and Michael Hufford, the CEO, acting CEO, will be here to speak to that. I don't know if Michael's in the room tonight by any chance. I would start with him and we'll have those conversations more tomorrow. Do you have anything you want to add there?

I just want to add that again, I would have a lot of hope. This is a difficult pathway in the foundation we set up. We help a lot of different families with very difficult chronic illnesses. And so we've seen a lot over the years. I would say where we are in neuroscience, to Peter's point, is that when we think about the ability for neurogenesis, the ability to go back to the state that we were when we were creating lots of neurons and neurons were following a gradient and finding their place within the wiring, both in the brain and then the rest of the nervous system, there's a delicate balance because obviously we don't Want to revert everything back and then go into an expl. Explosive fetal growth phase. But we're getting better at understanding this balance. We're not there yet. Those tools are not there today. Our hope is that by modeling this with better tools, we can create this digital twin that allows us to understand those processes. So what I would say is that it's about collaboration. Where I've seen this work, it's collaboration, it's patient advocacy, it's associations, it's getting the dollars, but not just the dollars. Lots of dollars have gone to lots of things that have not borne fruit. It's connecting with a community like this. And I've always been very positively encouraged. Every time that Peter holds a visioneering. Every time he holds a gathering like this, I come away super pumped up because this is a crowd, this is a group that says yes when everyone says no.

Yeah, I do.

I think, thank you for that.

I think having that point is really important. Having the entrepreneur's mindset of saying, I refuse to just let it be and to take it on. Right. We've had Martine Rothblatt speak here before, who her daughter was dying from a lethal disease, and she started with a high school textbook and found a medicine to treat her daughter, Genesis, and then said, well, this medicine is going to keep her alive. Now I have to go and actually learn how to regrow lungs because the only cure is a lung transplant. And she's been building her company and building basically an abundant supply of organs. Hans, are you in the room? Hans. Christine. Here's Kirsted. Hans is the CEO of Immunis, and he'll be speaking tomorrow morning as well. What's that? We've connected. You have connected. Okay. Fantastic. Yeah. The tools to understand and begin to take our lives and our health in our own hands are finally coming of age at an atomic, a molecular genomic level. And so the only time it becomes impossible is when you give up. Thank you. Thank you for your question. Hey, everybody, this is Peter. A quick break from the episode. I'm a firm believer that science and technology and how entrepreneurs can change the world is the only real news out there worth consuming. I don't watch the Crisis News Network. I call CNN or Fox and here hear every devastating piece of news on the planet. I spend my time training my neural net the way I see the world by looking at the incredible breakthroughs in science and technology, how entrepreneurs are solving the world's grand challenges, what the breakthroughs are in longevity, how exponential technologies are transforming our world. So twice A week I put out a blog. One blog is looking at the future of the longevity, age reversal, biotech, increasing your health span. The other blog looks at Exponential Technologies, AI 3D Printing, Synthetic Biology, AR.VR Blockchain. These technologies are transforming what you as an entrepreneur can do. If this is the kind of news you want to learn about and shape your neural nets with, go to dmandis.com blog and learn more. Now back to the episode. All right, Francois.

Yeah. Thank you so much for a beautiful evening and the energy is amazing. So thank you for that. I just wanted to come back to what you were presenting with Immuno oncology and the checkpoint inhibitors. You were talking about reducing the time to develop those things which I think are important, no question about it. But to my knowledge also a number of them have been developed and each time the cancer cells found a way around it. It's not just a question of blocking PD L2, PD L1 with Keytruda. It's iterative. Even if you reduce the time for development, it's going to take decades before we outsmart the tumor. My question to you, and I think you know, Peter hinted to, that is, can we use the tools of you have developed today, the superpower tools to perhaps not understand fully the biology of the tumor itself. The cellular tumor gets so complex, but at least get a hint of what's going to be the next thing to hit the immune system, in this case with another type of checkpoint inhibitors or what have you, or. Or maybe even start thinking about different mechanism of action rather than trying to counter this molecule. I know that there's some technologies that are being developed around that, but uncovering more and more of the mechanisms where you can attack the production of PD L2 and PD L1 inside the tumor itself through new mechanism. And so using this amazing power of computing to really understand better the tumor at the molecular level. So not to understand everything, but the key element that allowed it to escape and allowed it to survive. Synthetic killing, synthetic lethal. As you know, oftentimes if you hit two different pathways, the tumor cannot handle that. Can we use those tools to really uncover that faster? That will allow us to develop tools that are a bit more. Thank you, Francois. So just to hit one key point on that right away, because you're absolutely correct, part of what we know about cancer as we delve more and more into it as a society, is that we also have to look at the context of the cancer. Correct. So an example is not only the micro tumor environment, but also, for example, the microbiome Naveen is here with Viome and other people here are involved in the microbiome. Microbiome. Now there's several papers that have come out over the last five years indicating that that's why of the modulators of the response of a human to checkpoint inhibitor immunotherapy, that the reason why we have a third of people doing really well in melanoma on checkpoint inhibitors and then 2/3 not doing so well in terms of dural response after a year is partly one reason. Again, it's never one silver bullet, but one reason could be the microbiome. And so it's very important for us to delve into that. Microbiome has not traditionally been part of standard of care. And so as it becomes more mainstream, more and more places now will incorporate that into an integrative way of understanding cancer. That becomes another tool in the tool chest. So what we find with cancer and the reason why it's so elusive is we love to say that it's just one mechanism and just looking at this one narrow thing and that's the way to get your PhD and your postdoc and so on and so forth. But unfortunately, unfortunately that's not what cancer cares about. They don't care about your PhD. What cancer wants to do is it wants to survive. It's its own organism. It now wants to move and survive and so it will do anything to do that. And so looking at that larger context, that's where we've had now some more luck in looking at that larger context. So I agree with your premise and that's why these tools that can model much more high dimensional kind of systems are so critical. I want to make sure we get to more people though. So thank you, thank you, thank you very much.

I would like to. We have five questions standing. I like to do them quickly so we can wrap and let people.

I want to end on education. I want to make sure we get.

Okay, we'll do that. Mike?

Yes. Does your diamond sensor sense the direction.

As well as the magnitude the magnetic fields?

Great question. Yeah. So it is a vectorized sensor. It's a great question and we didn't have time to go into it today. But in the heart for example, why would you want to know direction and not just the picture? Well, blood flow, for example, obviously you'd want to see the direction of that blood flow to start looking at the health of not just the overall heart picture but the valves. And looking at is the blood pumping in this way and the different chambers of the Heart. All that is because it's a vectorized sensor, not just the magnitude. So you're absolutely hitting on a key point again with equality, EKG and other kinds of sensors. We don't have that kind of vectorization so we can't see it. That's part of why Cleveland Clinic and all these places are excited about and have been using this technology a long time. But now it's time to take vectorized cardiac diagnostics out to the masses. Great point.

Thank you, Annie.

Thanks so much. I wish that I had a teacher like you when I was taking material science engineering. Quick question. There are so many challenges that you.

Can choose to just dive into at this point.

How are you choosing the use cases and the challenges? Because I can't even imagine how you're doing that.

And then number two, I used to work at Genentech.

Do you see quantum solutions supplanting animal testing? Eventually, yeah. So great questions on the first question. How do we choose? You're right, it's a tough thing because quantum sensors alone just one part of what we do. There's so many applications and one of the Kirk before asked the question about using it a totally different way, which again is very, very exciting. We've chosen to focus on cardiac care and navigation to start with. We've chosen to say if people want to partner with us, we're happy to partner with them to look at other applications. We can't do everything, there's just no way we can do that. But we can offer some fundamental stacks that other people can then use. I'm a fundamental believer and Peter and I have talked about this over the years of making sure that we can get the core stack technology out on a licensing basis to lots of academics and lots of startups out there and.

Let evolution take its course.

Yes, exactly. And so one thing we're doing, we're actually now investing in young startups, right? So if folks have ideas or if there's venture capital folks in the room, we like to co invest we with startups alongside them and say hey, let's invest in this startup and maybe they can use this technology in a totally new way. I think that the old B school of the 1980s thinking is this company must do this and must focus on this and then keep your all IP in the big moat and things like that. I think we've now seen that there's a different way of doing things. Elon famously gave away the pants, opened the up the patents to the Tesla because he wanted to see more people out There, I think that is the way to go. The way to go is to publish out. We publish as many papers as we can to show people what we're doing. We are offering up the stack out there so people can license it and run with it, and we'll even give them money to invest in them and run with them. So that's, in a sense, of what the best way to go with that. To go with that is. Yeah.

Thank you, Annie. All right. Nora. Hi.

In the image where you showed the noise for what is the reason why you couldn't just take, like a baseline read without a human in the room of what the noise was like with the elevators, and then take a second one and delete it or triangulate with three. Yeah, no, great question. So one of the reasons is certainly you'd want to take a baseline reading and you want to get a sense of the noise in the room. And we do try to do that. But even the human body offers a lot of noise. That's part of the issue. One of the things that's producing magnetic fields is also our brain. It's a very weak magnetic field, but it is a magnetic field as well. And the other humans in the room also could also be offering up new noise as well. So there's a lot of noise factors there. So we have to have better and better machine learning tools to really understand. Here's the good news, though. Because the heart has this pattern to it, right, where it's beating X number of times a minute. We have a way to anchor ourselves into ground truth. Right. It would be much more difficult if the heart were this chaotic kind of ball game that we couldn't understand at all. But in fact, we can understand, understand the regular heartbeat. And that actually allows us to go into chaotic fibrillation as well and understand that. Because once we lock onto the signal, then the ML algo is like, that's my signal. I'm going for that. And thank God, again, these GPUs, when you have a device like this, you cannot be going to the cloud and sending processing to the cloud, both for privacy reasons and latency reasons. You need to do everything on board. And again, five, six years ago, these GPUs were not powerful enough to do that, but today we can do that. Thank you, Anusha.

Jack, as you mentioned, this is one of the most powerful technologies that will transform our world. And how can we make sure that this is not locked up in certain countries or certain large corporation, and it's truly democratized and every Person in every.

Part of part of this world can get access to it and innovate with.

It and take advantage of it.

Well, this is what Peter and I, we didn't get to this topic, but Peter and I wanted to talk about the growing quantum divide. I think all of us in this room were at the Point 20 years ago, we remember the launch of efforts to attack the digital divide, right where digital divide is if you don't have a cell phone. Starting 20 years ago and then starting 10 years ago with the rise of the smartphones and all the services you can get, you were blocked off from health education, you're blocked off from financial services, you're blocked off from E commerce and selling your wares onto Etsy and lots of places around the world. You're blocked off from taking loans. I served on boards of microfinance banks for 10 years and the rise of the smartphone was a critical tool for us to get to people and to engage with them with their loans and give them financial education so they could actually build their businesses with the loans that, that we were giving them. But all that was cut off from you if you were in the billions of humans who did not have access to that. And now, 20 years later, finally, at the rate of about 250 million people a quarter, right now, people are joining the Internet for the first time right now. And so we're now squeezing that digital divide down. But as that is happening, we've opened up, unfortunately, a quantum divide. A divide where there's about 20 countries in the world that have national blueprints. Australia is one of them, with incredible quantum science in Australia, UNSW and many universities there, US, UK, Canada, so on and so forth. But 170 countries do not have quantum programs. And we are very, very concerned because those have nots will then have to pay rent to the haves in terms of the medicines, the battery chemistry, the material science, the quantum sensors for medical diagnostics, the quantum sensors for navigation, all this the have nots will have to then find from the haves that is a problem. And so what fundamentally it comes to is the topic that Peter and I wanted to focus on, which is the educational topic. The good news is we don't need 100,000 people per country to know quantum. You need literally just a few thousand people in each country to know this. And the question is, how can we do this? We have a new initiative with the World Economic Forum, many others as well, not just us. It's a global issue and we want to nip this one in the bud way before we did the digital divide. I would say I failed in the digital divide just to take personal responsibility that I tried, I worked on it, and I did not make much of a difference at all in the digital divide. I went to many, many countries where we were doing micro finance, banking, and we tried to get programs going and we worked with Grameen bank and others, and great efforts. But ultimately we didn't have much of a difference. We didn't make much of a difference. And one of the things that animates me now about this is my failure in digital divide. And I hope we can do a better job here.

Amazing. All right, guys, last one standing here.

All right, thank you very much.

Maximilian. Yes, please.

You mentioned early on that the climate change issue is. I mean, you had the epiphany, and.

It seems to me that that's a.

Very important use case for your tools. And I would like to ask you whether you could elaborate a little bit on that. What is it we're talking about? Are we talking simulations to decarbonize the economy or. Yeah, let me just briefly touch on. I also want to thank Shivka, who might be here tonight, who came with us on the Antarctica trip and had great contributions on that trip as well. But what we realize is that using these tools, number one, we need to get beyond just lithium ion in terms of battery chemistry. If we want to scale battery chemistry, not just for electric vehicles, which is critical, but also for stationary, the larger impact is stationary batteries to store not just solar and wind, but even whatever electrons you have by getting them at night and off peak and storing them in a building like this and then using them by day. That arbitrage allows us to shave the peak and to have better, more efficient use of whatever electrons we're making. This battery chemistry. There's many proposals out there in the academic literature. Zinc, air, aluminum, different ideas of material science for the anode, the cathode, the electrolyte, the membrane, all this kind of stuff. But this needs quantum simulation. We need to do the billions and billions of combinatorial runaway in terms of making that new chemistry happen. Again, just like clinical trials, if we physically build each one of these batteries, we'll never get there. And that's why we're still stuck with the current. There's no Moore's Law when it comes to battery chemistry. There's Eroom's Law. Anyone know what Eroom's Law is? Erom's Law is Moore's Law backwards. And so, okay, it's slowly getting out there. Okay. And so we haven't seen Moore's Law in terms of battery chemistry, in terms of the density, power density, energy density, any way you want to cut it. We now need to use these tools and look at and model billions of combinations of chemistry so that we can have the breakthroughs. Not instead of lithium ion, we'll use lithium ion, but alongside that, we need specific chemistries for other use cases. So that's an issue for climate change. Perovskites. Does anyone know perovskites? Any ideas? Perovskites, I use for.

We've talked about perovskite here.

Good. So perovskites for solar. We're still stymied by critical issues of stability. After just six or 12 months, sometimes these things are breaking down. We need to do the combinatorial billions of simulations to get perovskites more stable as an example, and get the lead out and get academy amounts on and so forth, and that's what we need to do. So for climate change, that's one thing. And then, of course, for the data of actually what's happening to our planet, we down in Antarctica just dropped a quantum sensor off the side of the boat, towed it with us, and did magnetic readings underneath the Southern Ocean in the Southern Ocean so that we can do better rov, better underwater drones, so we can take better measurements of how the sea is changing. And so this is all part of a more advanced climate science that we can get to, you know. Thank you. Thank you, Jack.

You're amazing.

Thanks.

Let's give it up for this matter. You know, I write books for popular consumption. He writes this Quantum computing and applied approach. I'm flipping.

This is a beach read, Peter.

And this is giving. This is giving to give me for.

These people in this room. It's a beach read. I think this is, like, this is.

Bringing me back to.

We have a sophisticated audience here, bringing.

Me back to my quantum physics and complex calculus classes that were not a cakewalk for me as they were for you, buddy. Thank you. Are you able to stick around for folks to spend a few more minutes with you?

Yeah, we do have to fly out tonight. But, Peter, I just want to thank you for bringing this incredible group together, all of you in this room. I just. I think it's very clear. I'm sure you've now been spending two and a half days with Peter and the ideas. Every time that Peter and I collaborate, I come away inspired, energized, and I'm sure I can speak to everyone here that you have that same guys. Let's give it up for Jack. Hillary, it.