Using Quantum Computers to Build Alien Technology - Deep Prasad [NASJAQ NASCAST Episode #3]

Let me just like warm up the audience. Can you hear me? I'll just warm up, I'll just like talk to people, 'cause congrats. What's up, yo? Yeah, okay, so I am putting this into one tab. Let me just see like if other people on YouTube can see this. Can you hear me? Is the audio good? Okay, cool. Started streaming less than a minute ago. Let's get some likes on this. Oh, I don't know why the description is testing. Let's check this. Yo, hey Jack, what's up? Epic Blade Runner, ye, what's up boys? How's it going? Setup, um, using quantum computing to find new materials. And then I will update description for the anchor.fm/nasdaq. So full episode will be here. And then I'm just updating the description, everybody. What's up? Yo, everybody on TikTok, I'm going live on YouTube, so just jump on over there and, uh, we'll get into it. So Full episode will be out here, and then what's the other thing? Oh, all links. Linktree. I'm just gonna add our Twitters to the description. And then my Twitter. Updating. Cool. So, what's the chat saying? Yo, I'm here. Raul Does Nothing, what's up? Move straight from TikTok. What's up, Raul Does Nothing? Hi, Future Aspect, how's it going, man? I've been here for a long time, love your content. Thank you, Epic Blade Runner. Dude, I'm a big fan of the news you bring out in tech. Raul Does Nothing, I really appreciate that. It really makes me happy to see all the stuff that we are accomplishing. Dude, your sign on TikTok is still backwards. On TikTok? Oh man, how is it backwards? Is it actually? How does it— how do I make it backwards? On TY. Let's see, do I have a— yeah, okay. No, then why can't I figure this out? What is the name of the podcast for Spotify? It should be in the description. So I think just Nat Shack Podcast. Yeah, so it's on Spotify. Hey man, I got a research opportunity in quantum encryption next year. I'm pumped about it, dude. That's dope. Okay, look, let's get Deep on here. Let's get this show on the road. Everybody, let's welcome Deep.

Hey, thanks so much for having me, Jack. I'm really excited for this.

Deep, what's up, man? I'm super excited for this. This is just something new that I'm testing out. We'll see, it's gonna be just like a chill conversation and it should be super fun.

Yeah, absolutely.

Awesome, so—

And you know, I love that somebody in your audience is working on quantum encryption next year. Amazing.

Well, yeah, I mean, dude, I think it's a growing field, right?

Absolutely. Yeah, it's the future. I mean, you know, anytime humanity has developed a new way of communicating, a new way of processing information, we've evolved. We've unlocked so many wonderful things, and that's what's happening with quantum technologies.

I completely agree, and that's why I was super excited that I met you. I want to just start with that. So like, how do we know each other?

So you ended up being the first angel check. Your first angel check was in our company, and I think that's an amazing way to know each other.

Podcast exclusive. I haven't announced that anywhere else. This was— look, this is the first angel check because you are one of the companies that I think is just going to be insane. So I'm super excited about everything that you're building. It only makes sense to start off the podcast with obviously the first person. So there we go. So look, tell everybody what you're building and let's just get to it. How the hell are you gonna build a superconductor?

Let's start with that. Yeah, sure. So first of all, let's define a couple things, right? So, so before we get into superconductors, I want to talk about Richard Feynman. So Richard Feynman is the father of quantum computing. In the early 1980s, he realized that nature is quantum mechanical. So whenever we're interested in understanding the physics of, let's say, the brain, biochemistry, new materials, like let's say plastics, semiconductors, all of these things share one thing in common. And it's the fact that to describe them properly and to simulate them, you need to be able to simulate quantum mechanical systems since that's what all these materials emerge from. And so in the '80s, he came up with this ingenious idea that in order to simulate nature in these quantum mechanical systems, you need a computer that's also using quantum mechanical systems in order to simulate other quantum mechanical systems. And so that was the birth of the quantum computer. And so these quantum computers are inherently, they were made to simulate nature. That was their initial purpose. Now people are finding other very clever applications for them. But so what ReactiveQ is doing is taking Richard Feynman's dream literally and trying to manifest it into the way that he envisioned it. So what we want to do is to be able to simulate materials before you spend millions of dollars or billions of dollars researching them and, you know, several years and decades in making those materials. We would like to be able to simulate them instead so that we know ahead of time whether this material is worth making or not. Imagine how much that would accelerate, let's say, the next generation of battery development or semiconductors or superconductors, when you can suddenly discover these things within moments rather than years.

That's amazing.

Thank you.

You're using quantum computers to be able to discover these in moments instead of years.

Exactly, you got it. That, that is the end goal here. And so our target materials, so our platform, the thing that we're building based on quantum computers and quantum computing platforms, we want to be able to discover any new material or any sort of, let's say, unique combination of atoms that have never been seen before. So that could apply to drugs as well, right? And so what we want though is the target material, the dream material that we want to discover is a room temperature superconductor. That would be sort of the Hail Mary of material science.

Okay, so before we get into the superconductors, let's just start off by saying, like, why are quantum computers— why does quantum computing make more sense than any other computers to simulate nature and find the correct, like, composition of atoms to make these superconductors or any materials? Why is quantum the, the best way for new material design?

Great question. So There's 2 main reasons why quantum computers are best made for simulating nature. The first one is what I call the exponential scaling problem. So let's take, for example, a group of atoms, they're all entangled. So let's say, like, let's say 155 electrons, and these 155 electrons are entangled. Most materials, most very, like, let's say any material you're interested in, let's say a titanium alloy, will have trillions of electrons that you want to describe, right? But let's just start with 155, and you'll know why I picked that number for a reason. So if I wanted to keep track of the quantum state of 155 electrons, I would need 2 to the 155 classical bits to store that state. And the reason why is because for every body you have and every entangled body you have, or entangled particle, we need 2 to the n classical bits to represent that. So if I have, let's say, 10 electrons or 10 quantum particles and they're all entangled, to keep track of their overall quantum state, I would need 2 to the 10 and so on classical bits. So if I have 155 electrons, I need to store them in 2 to the 155 classical bits. But here's the problem. According to the Department of Energy, If you were to count every atom on planet Earth, including our atmosphere, the oceans, and all that stuff, you combine it together, that would make 2 to the 155 atoms. So even if I turned the entire planet into a supercomputer, I wouldn't be able to store the quantum state of just 155 electrons. And so quantum computers don't have that problem. Quantum computers would just need 155 qubits instead of classical bits to represent 155 electrons. It's linear rather than exponential. So now you can suddenly do things that are literally impossible by today's computers, which is, you know, storing this quantum state. Then—

So what was one possible thing? Oh, sorry, go ahead.

Yeah, sure. And so, so yeah, I'll touch on that for sure because that's where Google's quantum supremacy announcement comes in. But so the second thing that quantum computers can do that classical computers can't, and quantum computing platforms in general, is they can model quantum effects like quantum tunneling, right? So for example, quantum tunneling is one of— it was one of the things that drew me to this field actually, was that you could have these weird scenarios. In the classical world, so the world that you and I are used to, right, where these macroscopic bodies and We're subject to just the laws of classical physics. You know, that's what we observe and what we interact with. It's all based on Newtonian physics and, you know, Einsteinian physics. All of that is based on, again, the classical world. And in the classical world, let's take a ball. If I threw a ball right behind me, it would bounce off the window, right? It would. That's what we would expect it to do. However, with quantum tunneling, it's a very strange phenomenon. When you have a particle, let's just say one electron or any group of particles, what they can do is do something called quantum tunneling. So instead, if I were to shrink this ball down to the size of an electron and I just threw it behind me, there's a small probability that that ball will tunnel through the wall and end up on the other side as if that wall was never there. It's a lot like Harry Potter where you have this ghostly train coming through the through the wall. And so what quantum computers can do is they actually leverage these physics and principles, and so they can simulate other systems that are also using that.

So, so what was one of the first things that quantum computers did that was impossible by normal computers?

So the first thing that they did was something called quantum random number generation. Now this was an announcement made by Google in 2018, when they achieve something called quantum supremacy. So there's 2 milestones that I think are worth defining. And I'll give you an example, by the way, at how fast this field is developing. I joined the space about a year before that, before this milestone was hit. And when I had joined it, there was this idea of achieving quantum supremacy, which the field was interested in. Quantum supremacy was a point at which a quantum computer could perform an algorithm or a task more efficiently and faster than any classical supercomputer on the planet could do. And so it was believed that that milestone would be achieved in several years after 2018. We were expecting to hit it mid-2020s conservatively. But it ended up happening less than a year after I joined the field. And so that milestone was hit by Google. What Google was able to do was they took 53 qubits and they applied these single gate and single unitary single qubit gate and 2-qubit gate rotations. So if you were to visualize your quantum state as a vector, it's really a ray in what's called the Hilbert space, but you can think of it as an arrow in a very complex high-dimensional space. So if you were to start with that starting quantum state, what Google did was they were able to rotate that state randomly using these quantum circuits that they had created to the point where the random distribution that we measured at the end, if we were to replicate that probability distribution, it would require a supercomputer several years, up to 10,000 years to replicate that distribution. And they did this in So that was like the first big milestone that the community hit. Now the field is going towards— we're aiming for the second milestone, which is something called quantum advantage. That's the point at which quantum computers perform or give an actual industrial advantage or commercial advantage.

That's what I was gonna say, because, you know, generating random numbers isn't commercially super helpful, right? Yep, now we're getting into the commercial applications of quantum.

Exactly.

So first off, before we get into the commercial applications, let's just say like what enabled Google or any of these quantum computers? How did we, instead of waiting until 2025 in the middle of the decade, what actually advanced them much faster than everybody was thinking? Was there like a hardware development or what, what was that?

So that's a great question. Really what it came down to was immense engineering expertise paired with the best physicists in the world. who were trying to create this. So for example, you have one of the leading scientists, Hartmut Nevin, who was actually— people had seen him as naively optimistic about reaching quantum supremacy before 2020. But he said, nope, we're going to do it. And, you know, he actually pulled it off, right? And so—

Made it happen. Yeah, he made it happen. Dude, we need those visionaries. That's great.

We do. We really do. The guys who are almost like speaking to ghosts, and then you realize, oh, actually there's something there. And so the reason, the real reason though, like I said, was the engineering. It was this incredible way of controlling quantum systems. That's really what allowed them to achieve this sort of breakthrough is that— here's the interesting thing about quantum mechanical systems. When you interact with a quantum mechanical system, you have any physical interaction with it, it decoheres, which means that it no longer behaves quantum mechanically. So if you have a computer that's trying to simulate or do quantum computations, it needs to be able to perform these quantum computations without physically disturbing the state. It's sort of a catch-22, right? A paradox. So it's very difficult. It's a very hard engineering problem to be able to manipulate quantum states in a way that allows us to process information without decohering the state and collapsing it.

But did they figure out how to do that?

That's exactly what they figured out. And so far, you know, they've been quite unstoppable in their—

Can you kind of explain how you observe it without changing the state, or is that just like— what's the high-level explanation there? How did they figure that out?

Right, so the high-level explanation is, it's essentially imagine the double-slit experiment on steroids. So Just as a reminder for your audience, the double-slit experiment was one of the most fascinating things about quantum mechanics. It perfectly encapsulates the weird aspects of quantum mechanics. So essentially, imagine if I have 2 slits in front of me, right? They're parallel to my face or orthogonal, however you like to visualize it. Typically, if I were to fire just a ball, The ball would either go through slit 1 or slit 2. Now, if— the weird thing about quantum mechanics is that if you change that ball and you shrunk it down to the size of an electron, it would behave as if a wave when you're not measuring it. So the wave would go through both slits at the same time and interact with itself, and you would have this thing called an interference pattern. So what quantum computers are essentially doing is that if you want to perform a computation, It's creating a bunch of slits that are sort of phased sequentially behind each other so that when the wave or when the particle enters this wave state, if you want to visualize it like that, the wave will move through these different slits. And the way that your end interference pattern behaves, that's your computation. So that's how you perform computation without measuring it.

The way— can you say that last part again? Sorry.

Sure, so yeah, of course. So the way that the wave moves through the slits, through all the individual slits, and interferes with each other, that unique pattern, that end pattern is your computation. Think of it as the answer to your quantum computation, and that's how we're able to perform these computations without directly measuring them. We let the system perform the quantum computations, then we measure the end result.

Okay, so I want to go back and How did you get started in quantum computing?

Yeah, fair enough. It's a— yeah, so interesting enough, it kind of starts— so I'll tell you a funny story. When I was 12, I was obsessed with just like joining all these physics forums. I would mostly, you know, lurk in the forums. Sometimes I would interact, and I had this extremely, let's say, naive understanding of the, the double-slit experiment and Schrödinger's cat. I used to think, and I'll clear this up because I know that a lot of people still have this misconception, I used to think that when Schrödinger was talking about the dead cat and the alive cat, that it's both dead and alive. It turns out that that's actually not true, that when it's in a superposition of dead and alive, it's a very different physical meaning than what we actually think. it is when people talk about it. So I had this really passive interest, you know, in quantum physics for almost a decade. And then around the time that I had started my first job out of university as the head of artificial intelligence for wealth management at the Royal Bank of Canada, by this point I was deeply obsessed with quantum mechanics. And I had also had lots of experience now actually building machine learning systems and and working in artificial intelligence. So what I was asking myself was, where is the intersection between quantum mechanics and artificial intelligence? What does that intersection look like? So one day I quite literally randomly Googled quantum machine learning to see if that was a thing, and turns out it's an entire subfield of quantum computing that there's tons of activity happening.

Like a pretty— was it a new Was it a new field or was it like pretty well established or how was the progress there? It was probably pretty easy to meet the experts.

It was, exactly, yeah, it was very new, right? Yeah, we're always learning, even the experts. And it's still very new. It's still like the baby field within quantum computing and quantum computing itself is quite new. And so, you know, interestingly enough, so I was taking this course during my undergrad, it was in my last semester. Called Science Communications. And it's cool because we're, I guess, doing that right now, right? And so we had this option to make whatever podcast we wanted on any topic we wanted, as long as it was rooted in science. And the only condition of that podcast was that you had to interview an expert in the field of the subject that you wanted to talk about. So what I did was, by then, you know, I was obsessed with quantum machine learning. I had watched interviews by Seth Lloyd and some other experts. And so what I did was cold call the Institute for Quantum Computing at Waterloo.

I love that.

Thanks. And I, you know, I literally called their front desk and I said, hey, you know, I'm doing this podcast on quantum machine learning. I really love the field. Do you have any experts who are working in this field by chance? And the lady was, you know, very nice. She said, let me get back to you. We have a few people. I'll ask them if they're interested. And so, you know, a few days goes by and she emails me and she says, one of our experts in quantum machine learning is going to be in Toronto in the next week. We're going to put you in touch with him. This person ended up being currently the leading expert in quantum machine learning and quantum computing.

Oh my God.

His name is Guillaume Verdon, and he is a lead research scientist at X, at Google X. And so he's architected TensorFlow Quantum. Many people are familiar with TensorFlow. He's the co-architect of TensorFlow Quantum. So yeah, he's a true genius. And, you know, we met to do this podcast and it was amazing. We had so much fun doing it. So he kind of, you know, in a way took me under his wing. He really encouraged me to join the world's first quantum computing incubator. at Creative Destruction Labs. He showed me the kinds of textbooks I should be reading, that's sort of the holy Bible of quantum computing, and just really put me off to a good start.

Nice. So, so just to clarify, like, you weren't doing anything quantum in university or anything, and then you completely— you took this, you did this interview because you were interested, and then you started doing a course in quantum, and then everything kind of swept up, and now you're like starting a startup in quantum.

Exactly, that's right. That's exactly what happened.

I love that. That's like, that's proof that you can, you can teach yourself any field as long as you're interested, I think. So what is quantum machine learning and how is it different than normal machine learning?

Sure, yeah, that's a great question. So quantum machine learning is really 2 things. You can divide it into 2 categories. The first category is using classical machine learning on quantum systems, and the second one is using quantum computing in machine learning systems. So let's take the first example. Remember how I said it's very hard to control and manipulate these quantum mechanical systems?

Mm-hmm.

Imagine you have a really, you're a great engineer, but maybe not the best, or you're dealing with a really hard quantum computing problem. Something that the entire field is using, including Google and all these other quantum hardware companies is they're using classical machine learning to correct the quantum computing programs and the systems that control the quantum systems. So these quantum control systems become a subject of machine learning as we know it today. So that's one part of quantum machine learning.

Okay, and that's not the quantum machine learning that you're using?

Correct.

You're using the second type?

Exactly. So we're using the second kind. So One thing that classical machine learning does, and we take it for granted, but think about the machine learning that Geoffrey Hinton is doing or any of the machine learning that today's systems use. When I speak to Siri, Siri is using classical neural networks, right? It's all using classical machine learning algorithms, and even our computer vision algorithm, it's all classical algorithms. Now what is the one thing in common between all of these classical machine learning algorithms? It's that they are learning classical data. So these data have no quantum correlations, no quantum statistics to them, and therefore—

So what is a quantum correlation or quantum statistics? Just like that pieces of data are related to each other and you have more like data points than an XY or something?

Bingo, exactly. So quantum systems have quantum correlations, and so classical neural networks and classical machine learning algorithms aren't built to be able to learn those quantum correlations. That's where— and it comes out of the physical phenomenon known as quantum entanglement.

Mm-hmm. And it's not just like an extra data point that you can add to a classical machine learning algorithm?

No, exactly. It fundamentally changes the mathematics of the data, the data structure, and therefore the machine learning algorithms that need to learn from that data structure. And that's where quantum machine learning, the second half, the one that we're using, comes in.

But it still uses like a kind of a matrix, right? Because the hard— or the hardware that was really helpful for quantum computing was the TPUs, right?

Yep, exactly. Yeah, so, so you have quantum computing simulators and then you have quantum— actual quantum hardware. Now the interesting thing of using classical quantum software or quantum quantum simulators is that some of them are based on representing tensors. And so all of quantum mechanics, every single quantum mechanical equation we've ever seen, every quantum algorithm we've ever seen, can be represented as a tensor or a tensor network.

Mm-hmm.

And so, you know, that was established well over decades ago. So what you could do is actually build simulation systems that simulate quantum mechanical systems on these, you know, tensor network units or TPUs.

Okay, and the TPU just makes it like super efficient, much faster, things like that.

Exactly.

So that's a huge step up from— were they using CPUs and GPUs before?

That's it, yeah, that's what people have been using for quantum platforms in the past.

Okay, so when you do quantum machine learning, I believe on our first conversation when I asked you this, I said that, you know, when you have local minimums and local maximums, I essentially said, can you just like tunnel and go find the actual maximum or a new local maximum? Like, is that kind of how it works? Like just tunneling in a— I don't really have the language for this.

I think it was, first of all, it was amazing intuition on your part. So yeah, it depends on the problem. Some problems have, if you're doing an optimization problem and you're using natural quantum computer on it, some problems will have an optimization landscape. Let's say it's called an energy landscape, where if the hills— so you can imagine literal, almost like physical hills, right? They're made of energy. If the hills are skinny enough, what you can do is actually tunnel through them to get through other local minima or potentially even find the global minima.

Okay. Okay, cool. So now let's get to how does this help you, all this quantum computing, how does this help you find new materials? Yeah, so go ahead.

Yeah, sure. So, so let's look at, I'd love to use the superconductor as an example. Just for, just for, you know, definition's sake, a superconductor is a conductor that conducts electricity with zero resistance. Now, before 1911, we thought based on Maxwell's equations, that this would be impossible. Before 1911, you know, we believe that you would never have a perfect conductor, that every conductor that you'll ever encounter will always have some resistance for the electrons. It'll always offer some pushback. It's a lot like— imagine visualizing a hosepipe. You'll never have, based on classical physics, a hosepipe that's perfectly clean. So if you have water that's flowing without any resistance, That's theoretically impossible because let's say you'll always have dust particles in the hose pipe, so it'll never be perfectly clean or perfect.

The water at the wall has to be zero, right? That's what, that's what I learned in chemical engineering.

Yeah, that's right.

Yeah, exactly. It can't just all be going at the same speed. It's, it's gotta have the, the slope into the middle.

Exactly.

Yeah, for sure. But, but then with this superconductor Exactly.

So with the superconductor, what we found was 1911, a guy named Dr. Onnes, he discovered that mercury, when you cool it down to near just above absolute zero, so a few thousand millikelvins above absolute zero, you have perfect, perfectly no resistance or perfect conduction.

And is it actually no resistance or can we just not detect it?

That is a great question. So physicists were trying to probe that. for, I would say, years and decades after discovering them, just to make sure if it's— is it just our instruments not being accurate enough to detect that little resistance? And the answer is it's truly zero resistance.

That's amazing.

Isn't that insane? Yeah, it's amazing that nature allows for these kinds of materials to exist. It's really— I call them Easter eggs of nature.

So what happened after he discovered that?

Well, yeah, so, so first, Ons, you know, was like, is this, is this real? Like, there's no way this is possible based on known physics. So, so the physics community scrambled for finding a new physics theory or physics model that could describe the superconductivity and explain it. Now, now imagine the historical context here. This is 5 years after Einstein had his first sort of miracle year, right, of publishing those 5 papers, one of which he won the Nobel Prize for, the photoelectric effect. So this was pre-quantum mechanics in its full form. And so fast forward to 1957, you had these 3 scientists, Bardeen, Cooper, and Schrödinger. They created something called BCS theory, and, you know, they won a Nobel Prize for this. What they realized was that superconductors What does BCS stand for? BCS stands for Bardeen-Cooper-Schrieffer. They just named it after themselves.

Classic.

Yeah, exactly, exactly. So, so what they realized was that these superconductors can be described by BCS theory. At least low-temperature Type I and Type II superconductors can be described as by BCS theory. And so essentially the sort of thesis that they had was that the reason why you have perfect conduction in these superconductors is because the underlying electrons are able to use quantum entanglement to entangle with each other. So if you want to visualize it, think of having one electron and it finds the path of least resistance in the material, and the other electrons follow it like a train, and you have this train of cars and And so you just have this essentially infinite loop of electrons moving with zero resistance because the one ahead found the path of least resistance. That's one way of getting intuition for it.

Okay.

And so that was only possible because we had the machinery to describe quantum entanglement and quantum mechanics. So it turns out that superconductors are the first materials we identified that are macroscopic quantum phenomena. We used to think that quantum effects only happen at microscopic scales. Turns out that you can have superconductors that are made of trillions and trillions of atoms all behaving quantum mechanically.

And so when you say the first material that we discovered, do you think that there's more materials that are, you know, macroscopic quantum phenomena?

I do, I really do. So the amazing thing is that this birth of the superconductor caused 2 Cambrian explosions. We found multiple superconductors after this at higher and higher temperatures, increasingly as it went, until about the 1970s to 1980s era. Then we jumped to high-temperature superconductors. We also found something that was extremely counterintuitive. So when we think of conductors, we visualize metals, right? Metals conduct electrons, makes sense. So a superconductor should always be a metal. Turns out that even ceramics can become superconductors at certain temperatures, which is really weird, right? Because ceramics actually aren't conductors when they're not in their superconducting state.

That's super— was the temperature or pressure or conditions anything surprising, or was it just like, like compared to the metals? Was it surprising compared to the metals?

Yeah, solid question. So what was really surprising was that some of these ceramics were superconducting at even higher temperatures than regular metals. That's super weird.

That's super counterintuitive. It is.

It truly is. Graphene is a great example. If I take 2 layers of graphene, a bilayer of graphene, right? So that's just an allotrope of carbon you have, and I twist the graphene layer by 1.1 degrees, it will become superconducting, which is weird because if I just twist it back, it's no longer superconducting.

At what temp— like, you have to have special temperature and pressure conditions for that, correct?

Yeah, it's lower than -178 degrees Celsius, so it's really, really cold.

That is so strange. What makes it— it like just initiates quantum phenomena, or what happens when you, when you change that?

Exactly. So, so what initiates that is something— it's an active field of research called topological materials. So you're essentially changing the topology of the graphene when you twist it. And that topology, I'll give you an example. So topology is a field of pure mathematics, and we found out that it actually has deep use cases in physics, in theoretical physics and applied physics. So if you take, it's so funny, I find it hilarious. So a topological mathematician, somebody, or somebody who studies topology will tell you that a donut and a coffee cup are the same thing. Yes, and that's because—

a good internet meme.

It's amazing. Yeah, I can't tell the difference. We're really not kidding. As far as they're concerned, they have a whole number of 1. So topologically, uh, if you— you can have 10 different materials that look completely physically different, but their topology may look the same. And so that allows for these effects, these superconducting effects and these other quantum effects. And so that's why I'm confident that there are other even higher temperature superconductors that work at even higher temperatures that also— yeah.

So yeah, we'll get to the higher temperature, but essentially when you change the 2 layers and it like locks into this, you're saying like the topology can transition from, say, like a donut, which is not superconducting, into the mug, which is superconducting.

Exactly. Yeah, that's correct. Yeah.

Okay, so one state is superconducting and they're sim— but they're similar. Okay, okay. Yeah, so that makes sense. Okay, so now we have had— we've had plenty of room pressure superconductors, but within the last few months, we found our first room temperature superconductor at a massive pressure.

Yeah.

So that was super exciting, right?

It was extremely exciting, very, very exciting, and I'll tell you why. So let's look at some of the magical properties of superconductors beyond the fact that they can, you know, conduct electricity with no resistance. What does that mean, right? So first of all, let's say, let's look at the power grid system that we have today. Most energy sort of, or power grid systems incur immense power loss when you're trying to transport electrical power across long distances, right? You'll have 10%, 20% loss of the power. But if you have wires that are made of superconducting wires transporting that power, there's exactly zero power loss. So you suddenly have a significantly more efficient grid system that we could create with it. But now here's something that I'm very interested in. There's a property that superconductors have that no other sort of material has. that's known to man currently. And though there are really 2 properties in one, it's called the Meissner effect plus quantum flux pinning. So, so that combination is very unique and rare.

And also define both of those.

Yeah, yeah, I'll define them. So first I'll give you an example of what it means for us physically, then we'll work backwards. So let's say, uh, I took my phone and I spray painted and I coated it with 2 millimeter thin worth of superconducting materials, and then I activated it so it entered its superconducting state, it would create such a powerful magnetic field to deflect other magnetic fields that I could levitate a 6,000-pound car off of my phone, off of just a millimeter-thin coating. So that's, that's amazing, right? Because, because of the no resistance, the quantum flux pinning, which I'll get to, You would be able to move this car if I had, let's say, an entire track that was made of this material. I can move the car and it would be floating, and I could turn it sideways and upside down, and it would still be locked to my phone in XYZ space. That's the quantum flux pinning that effect. That's what that is. Now there's a Meissner effect. The Meissner effect is what's allowing it to levitate and creating this sort of so superconductors will. expel the magnetic field, any magnetic field that comes near it. That's the Meissner effect. So this combination of expelling the magnetic field and then locking itself through quantum flux pinning, essentially new transportation systems.

Yeah, so a lot of people I think may have seen like going in a viral video or something, the, the track, and then it's like a foggy disc or something, and, and they move it around and it like stays and levitates, and then they push it and it will go around the track.

Yeah.

So that's like, that's a great party trick, right? And then it's steaming or it's fogging or whatever because it's super cold, super cooled.

You got it. Exactly. Yeah.

So if we wanted to put that on our roads, we'd need to find one that is room temperature and room pressure and works at, you know, at least, you know, -40 degrees Celsius to 40 degrees Celsius or whatever. But yeah, for sure.

You got it, you got it. And of course, the beauty is if you have a room temperature superconductor, it's still going to superconduct at lower temperatures. Let's say you live in Canada where I do, where it can get really cold, it'll still work. But of course, yeah.

So they have an operating range. So what's like their typical operating range? Because if you're supercooling these, the first one was within millikelvins, right? But as they get higher, do they sometimes have a wider range? And so I guess in your materials design engine, you're including the, the range of the temperature and the ranges of the pressure, I guess.

Exactly, exactly. So, so we have 2 sort of classes of superconductors at this point. It's just an informal way of classifying them. You have really high-pressure superconductors that carry these high temperatures with them. So they'll superconduct at really high temperatures, but they also— the caveat is that they need immensely high pressures. Then you have superconductors that operate at room pressure, sorry, but they don't have room temperature or high temperature superconducting per se. They're still high temperature, they're literally classified as that, but they're not nearly as high as their high pressure counterparts. So for example, just this year actually, we discovered, as you pointed out, the world's first room temperature superconductor. And of course it only operates at very high pressures. And by high pressures, we're talking about the pressure that you'll find at the center of the Earth. So it's very, very high, right?

Mm-hmm.

And so it's not something that we can scale or build out. But here's the kicker. Before this year, half of the field was split, you know, whether room temperature superconductors would ever be found, whether they could even physically exist in nature. There was a lot of skepticism that we would ever find it, but here we are in 2020, you know, discovering that. Now it's last year, but, and so, yeah.

And so now that they have a room temperature superconductor found, even though it's at high pressure, and a, you know, a low temperature superconductor at a at a normal pressure, room temperature, room pressure, sorry. Now that makes you super confident that there's going to be a room temperature, room pressure superconductor found.

Exactly. It's inevitable because that's always been sort of how it's trailed. We will often find a higher temp, a higher pressure superconductor, and then something will catch up where it's actually room pressure. And there's also the arguments from the topology side of things, right? We know that there should be based on what's called density functional theory, which is our method, it's a computational method of simulating materials or predicting them. They're not accurate or they're not amazing, but they've been accurate enough that we have discovered new materials with them before. And so based on DFT, there's just all these different scientific arguments we're seeing, all these trends. Basically all roads end in Rome. They all point to the same thing, that there is a room temperature superconductor.

And so you're— the algorithms that you're developing are essentially like modeling the atoms to see if it displays this quantum phenomena of superconduction.

Exactly. So we are learning that quantum phenomenon. Since going back to the whole BCS theory, we know now that superconductors are based on quantum phenomena. So imagine you have a quantum computing system that can actually model that quantum phenomenon of superconductors, and then it could work backwards. So let's say I have a system where I input the conductivity, the pressure, the temperature that I want this conductor to be a superconductor at. We would want our quantum computing platform or system to work backwards and tell you exactly what combination of atoms you need to get there, to achieve that material. So that of course applies to alloys too, right? And batteries and, you know, plastics and semiconductors as well.

Yeah, so you're also looking at, say, like some biomaterials, semiconductors. So what can you do for semiconductors? So basically, so I saw something in the chat that said, sorry, I may have missed it, but Deep's goal is to use quantum computing to simulate nature in order to find a room pressure, room temperature superconductor. And yes, yeah, that's exactly it. Like, you're building the engine so that you can essentially put in these— or I can let you describe it, but you can put in these constraints. Say you want the temperature, the pressure, and then these phenomena that you want to appear. And then you'll use quantum machine learning, hand-wavy, but like you'll use those and then you'll find the materials and then you'll also have constraints to be like, okay, we can manufacture it using like A current amount of energy, not like the energy of the sun or something like that. Like, you'll also have manufacturing constraints, and then you'll go manufacture it or license it out if you want. And then you, you can have an entire material design. That's, that's the goal.

That's exactly it. Automated materials discovery instead of accidental.

Yeah, that's amazing. I love that. Okay. Yeah. So I was asking you what, what would, like, for example, the semiconductors, what would those properties look like?

So it would be similar but very different as well. So one of the amazing use cases about this engine is that because it's constraint-based, let's say that you don't have the resources at your disposal, right? Let's say that you don't have access to germanium, but you still want to build a semiconductor. And so that's one of your constraints. And, you know, germanium is a big component in a lot of today's semiconductors, what we would be able to do is through this, let's call it quantum AI, it's, you know, a buzzword salad, but that's really what it would be.

Mm-hmm.

So, you know, we use these agents, these artificial intelligence agents that are going through the search space of materials, and it would find other semiconducting materials that don't use germanium. So it would offer you alternatives to the same semiconductors, or let's say you have a better semiconductor in mind, You know the connectivity, the heat resistance it needs, the heat capacity that it requires, the tensile strength. You have these things in mind that define a better semiconductor. We would help you find that through the system. We would accelerate it.

And, you know, another question from the chat is that, do we know for sure that the material, I guess the superconductor, doesn't exist naturally? So we haven't found any superconductors, but I think this question kind of You know where this question leads is to aliens and UFOs, right?

Yeah, that's a fair point. So yeah, I mean, let's go with the ultra-natural, so the truly no intelligence included possibility. We have not found, let's say, really high-temperature superconductors in nature. We often have to synthesize them. with a bunch of different chemicals. And that's what makes it so hard, right? Because you literally have trillions and trillions and trillions of combinations of different compositions you can have to create. And maybe some of them, a small subset, are actual superconductors.

It's not just taking like nickel and then supercooling it. Like, you're doing a lot of things.

Yeah, that was one of the first things Dr. Onnes did, right? Was like, they took every single possible material they could get their hands on and they just cooled it. To see which ones are superconducting.

Yeah.

So, so yeah, so you have, uh, there is a hypothesis though that metallic hydrogen, based on density functional theory, metallic hydrogen is a room temperature superconductor and even above room temperature. Now the problem is that metallic hydrogen has been created a few atoms at a time. It's not enough for us to test the actual resistance of it or the conduction of it. But we do know that there are star systems out there that have, you know, nucleosynthesis process that do have hydrogen at the center, which would be in its metallic phase. So in theory, there are naturally occurring room-temperature superconductors. We just can't—

Okay, but that's at a massive pressure. That's why it's metallic hydrogen. Yeah, exactly. Yeah, so Okay, so, so what, you know, another— so, you know, now that we've found room temperature superconductors and room pressure superconductors, even though they don't coexist at room temperature and room pressure, another— that makes you confident that you'll find the superconductors. But another thing that makes you confident or that got you interested or something like that, let's like start talking about the UFOs, the aliens. Like, how did you get interested in that and, and what's, what's your experience there? And let's, let's go from there.

Yeah, it's been a crazy ride. So very eye-opening in the sense that— so in 2017, you might recall that the New York Times themselves, CNN, all these major media outlets, they covered UFOs, right? They were talking about the Pentagon UFO program. And so when I first read that, it was— I found it extremely weird that, you know, more people weren't talking about this. That there was literally videos that were being discussed of UFOs. And so I kind of put it on the back burner, right? I didn't think much about it, frankly at all, for about a year later. And so around close to the winter of 2018, I decided to sort of investigate the topic. And you have to keep in mind, this is like peak quantum computing incubator. So I have all these other things to do, and there was a huge reputational risk. To be entertaining UFOs, right? And so I sort of lurked the the UFO Twitter community, if that's what you want to call it. And I kind of just like learned that there's actually more than one case. There's actually a lot going on here. You have very serious researchers. You have your fair share of let like let's say not very credible people. But but you know you do have lots of very hard-nosed, reasoned people investigating this. So I started doing a bit of digging, and I found this private space conference that was being hosted by the guys who ran the Pentagon UFO program.

Okay, you gotta go to that.

I will. Yeah, so, so again, in 2017, just to recap, what we learned was that— think of the historical context here— until 2017 People, you know, the US government, specifically the Pentagon, had maintained a hard-nosed stance that there is no such thing as a UFO, that anything that is a UFO is just a balloon. It's weather anomalies. You know, they can spend— they have trillions of dollars of defense equipment. They can identify everything in our airspace.

Hmm.

But then in 2017, they did a completely 180-degree turn, and they talked about This, uh, that— just kidding, you know, we've spent tens of millions of dollars investigating the topic, you know, we take it very seriously.

So I misheard you. I thought you like, uh, knew that this private space conference was happening and you, you could go, but no, it's private, it's in the government. Like, they won't let anybody go, they don't want anybody to know about it, and, and they're denying UFOs existing. Like, that's crazy.

I agree. So just to clear it up a bit. This was after they had come out.

Oh, okay.

Yeah, yeah. So they were inviting a very small group. They were very exclusive. They explicitly said that they only wanted scientists, and that too, you had to submit your resume, your interest in the space, and what you think you could contribute, and then you might get an invite. And they had limited seats. Managed to get an invite. I applied, I got lucky, flew out to Huntsville, Alabama to this Space conference on UAP.

Oh, awesome!

Yeah. And so I think at that point, you know, having a quantum computing materials science sort of background actually helped. Like I had actually spoken about, you know, using materials science at the conference when I got there. So there's a lot of synergy. So anyways, what struck me was that you had the guy who ran the UFO. program for the Pentagon. Uh, he was there, and their chief scientist was there as well, who was one of the guys who was in charge of, again, the science aspect, scientifically characterizing these phenomena and trying to understand how it is that these UFOs work in the first place. Because they're able to do things that no technology we've ever built, no aerospace vehicle we've ever created, uh, are able to accomplish. I'll give you an example. So one of the UFO videos that the Department of Defense released this year on their official channels was from the 2004 Nimitz incident. That incident is called the Tic Tac. That's because that's what the pilots described seeing. They had measured the thing with extremely powerful radars, electro-optical instruments, and visually they saw it as well. So this object was Very weird. Imagine you have a 50-foot-long cylinder, a white cylinder that just looks like a Tic Tac, and it was able to achieve velocities of 31 times the speed of sound. Now think think think of that in context with let's say the International Space Station, which is currently traveling around Earth at 25 times the speed of sound. So even in space, it's slower than this thing that we're seeing right above our waters. And, you know, they were routinely observing fleets of these objects for at least about 2 weeks until they sent one of the world's top gun pilots to go and intercept one of these objects. So he went and he did that. And I actually did the calculation. I looked at Elon's Falcon rocket. I think the Falcon 9, if I recall correctly, the model name. So I looked at the thrust of the Falcon 9 and I asked myself, In order to achieve the velocity and acceleration of the Tic Tac, how many Falcon 9s would I need to achieve that same acceleration in our atmosphere? And I want you to try to guess the number.

How many Falcon 9s would you— how many Merlin engines?

That's right, exactly.

I would guess like at least 100, 300, probably 100 to 300 is my guess.

That's reasonable. You would need 6,600 Falcon 9 rockets.

Oh my God, that's insane. That is insane. Okay, so it's going at that speed, but then the question becomes, like, is it using quantum phenomena so it's not going through the air, it's kind of just like teleporting or something like that?

Right, yeah, it's a great question. So thanks to, you know, our foray into superconducting, and by our I mean mankind's foray into, into quantum materials. We know that, like, okay, what is a superconductor? One way of looking at it is that it is just a material that has emergent phenomena, anomalous emergent phenomena. It's a property of matter that emerges from other behaviors, right? So that behavior isn't local to the material itself. It's how you configure it and the temperature and the environment. So it's possible that these UAPs or UFOs They're achieving these velocities because they are built with extremely interesting materials that have emergent properties of matter that we haven't discovered yet. So in theory, if you have a simulator, a quantum simulator that simulates the emergent properties of matter, it— in theory, it can discover other emergent properties of matter that we haven't discovered yet. And so one hope, for example, our system is that we can find these emergent properties that allow for these UFOs to exist.

So you think that emergent property might be like almost teleportation, or being able— not exactly teleportation, but being able to move with no air resistance?

Correct, exactly. So, so the latter is absolutely true. One of the observables that the Pentagon UFO program came out with was transmedium travel, that these objects can travel through space Water and air with no resistance. They they are totally unaffected by the water that they're inside of. They don't slow down. And of course, if you look at the fluid mechanics of trying to travel very fast underwater, water builds up. You essentially get an incompressible fluid when you're traveling fast enough. It's why it's so hard to create really fast submarines that are traveling at hundreds or thousands of miles per hour underwater. In fact, right now that's impossible. For something to be beyond, let's say, 2,000 miles per hour underwater. Yet we're observing these objects that can do that underwater, and they can easily move into the air and then into space with no—

So they're going cross matter, so they're able to go through air and water. That's insane. That's absolutely— so, and we keep observing this and nobody's talking about— this is what Mike Solana on Twitter— this is actually how I first came across you. is that Solana was like, we're talking about this in the New York Times, it's being reported, and nobody's losing their mind, right? So that is crazy. So now that we've observed the Tic Tac, which is going Mach 35 or 31 and then going cross matter, what else have we found? Any materials? And are there any properties there? Oh, I remember this. There's a material with an interesting isotope composition. Correct.

Exactly. Yeah. So, so we've discovered, uh, different groups around the world, private groups. Um, one that I'm affiliated with has, uh, has actually got their hands on some of these material, or, or they—

or—

and so these materials, one property that I noticed that seems to be unanimous across acclaimed debris, that's like the term for it, debris from these UAP, uh, they have essentially engineered isotopic ratios that are not naturally occurring. And sometimes they're engineered to ratios that we still can't achieve today. So that's one highly interesting anomaly because we—

One of them was like 33%, 33%, 33%, right? Of specific isotopes. Do you remember what the isotopes were?

So off the top of my head, these were isotopes of selenium, and I believe bismuth was involved as well. I can't remember the third one, but essentially, yeah, the actual isotopic ratios of them though were equal. It's extremely strange.

That's super weird. That's just like, why does 33 make sense? Like, why does splitting it into thirds make sense?

Yeah, I mean, hopefully we can simulate our way to an answer to that, right? Because like, it might just be— it might lead to some emergent property. that we haven't discovered. I do have a belief that we might just not even know how to activate or properly use these materials right now. It's like, imagine this, I draw— imagine if I dropped a piece of my phone, like let's say just a phone screen, the touchscreen, right? It has capacitive capabilities, and I just dropped it in the 1940s or 1930s before we even discovered transistors. They would just say, oh, it's a piece of glass, like this is kind of useless.

Yeah.

So that might be what we're dealing with.

Hmm, yeah, and so you're, you're giving us like the correct magnifying glass to let us actually see what's happening under the hood of the plastic.

Yeah, and so to answer your question, by the way, about the whole teleportation thing, that's interesting, right? Because let's look at what we can do today in terms of teleportation. So first of all, though, I think that these UFOs are It's interesting because even based on special relativity, we are able to accomplish— and general relativity— like, we are able to accomplish faster-than-light travel. That's where this whole idea of warp drive comes in, right? Where you're actually warping time or space, actually spacetime, in front of you, and you're stretching it behind you like you're just contracting it. So you're kind of zipping through. And that's based on the principle that spacetime itself Can expand faster than the speed of light. We do observe that. We do observe galaxies that are actually accelerating away from each other faster than light, but it's actual matter itself that can't achieve those speeds. You need infinite energy to reach you know light speed. So in theory, I think that these things might be able to generate. The kicker though is that for warp drive to be possible, you need immense. energy. You need such a, like, profoundly high energy density source, one that we have not discovered. It's almost definitely not oil. Maybe antimatter.

Could be. Definitely not oil.

I feel like somebody would figure it out if it was.

So, uh, it would also create an immense amount of energy to manufacture this, uh, triple isotope material, right?

what it truly was.

Like, to create that configuration. So hopefully we can, with your design machine, we can figure out a way to manufacture it as well. So what wasn't there? Was there any new compelling evidence of UAPs, or has anything new come out in the community? I remember seeing the New York Times posted some things, but there was some new information, right?

Yeah, so there's some really compelling information, which is The creation—it comes in the form of the creation of the Pentagon UAP Task Force. And so, just for context, a task force is created when the government or the Pentagon is trying to solve a problem, and they need to sort of cut through all the red tape and the bureaucratic obstacles that are generally in place from solving a problem quickly. So I'll give you an example: during the Iraq War. the Pentagon created a counter-IED task force, right? Improvised explosive device. And so they had to create this task force because of course, you know, we were losing too many people to these IEDs.

Yeah.

And so, right, so, so, so this— they created this interagency task force where you have the FBI, the CIA, the NSA, and the Department of Defense, and now they can communicate with each other. Normally they work in silos. And so that's the purpose of this.

It's exactly like police departments, um, that can't work across state lines, and then the FBI comes in to like catch serial killers. It's, it's essentially like that. Things get way more efficient.

That is so true. That's a solid analogy. Exactly.

I'm all about the analogy.

We saw the creation of that, uh, this year, this summer actually, for UFOs to get to the bottom of how— who is behind these things. Right? That's like the sort of million or trillion dollar question is what kind of immense intelligence is capable of creating these objects that Russia is observing, China is observing, India, Brazil, Peru, France, you know, almost every country with an army or with astronomical equipment are observing these things now. And a lot of them have been coming out publicly over the past couple years.

Now, was it just announced that that was that was created, or had it been created a while ago and it was just released, or is it new?

So this is truly new.

Now, that being said, when it first starts is what I was getting at. Now it seems like they're actually warming up the public.

Exactly. Yep. That's what we're seeing. Even with the 2017, what I learned was that It's not like the head of the Pentagon UFO program accidentally clicked upload, right? And then suddenly the whole world knows about UFOs. It was very strategic. It was very, very well planned or thought out.

Yeah.

So what we're seeing, from what I understand from talking to these individuals, is a slow acclimatization to this reality because you can't suddenly just jump the world with this information if they've never been used to it. They've never thought of this. You know, it's quite psychologically irresponsible, in my opinion. So, so, so what we're seeing is just a natural progression of that with this Pentagon UAP Task Force. And I'll give you compelling evidence to sort of, sort of, as a consequence, or to show you why, for example, or prove this statement. Consider that just 2 weeks ago, the Authorization Act was passed. And in that Authorization Act, it mandates that the Pentagon UAP Task Force has to publish a declassified report on what the intelligence community knows about UFOs in the next 6 months. So they have less than 6 months to tell the public everything they know. So whatever we're talking about—

there we go, we're moving into the future there. That's great. Yeah. So now that we're like getting to Declassified Aliens, like, um, you mentioned this book during our first conversation, uh, about what an imagined future society would look like. So I just want to like talk about Your materials design engine is looking to eventually create these materials. And I'll let you say the futuristic materials that you want decades from now. But first off, that book and the futuristic societies, how do you think about futuristic societies? And what was that book?

So the book was called Planet Yarga. And if anybody wants to read it, I recommend reading the Dutch version. Original version because the one that was published, you know, in America was severely augmented. It's not— it literally has almost no resemblance with the original version. Um, and yeah, you know, information matters and all that stuff, accuracy. So the beautiful thing about Planet Yarga is, of course, we can't verify the, the veracity of the claim, right, of this author. But the author, uh, named Stefan Derd Uh, Stefan Dyrde was a multi-millionaire engineer. So, you know, goals for us. Like, he was a very successful entrepreneurial engineer. And, uh, he went on record after writing this book and he said, and his whole family backed him up, you know, they were there. He claimed that he had actually, uh, run into these, these aliens for no, no other, no lack of a better term. He said that these beings, whatever you would like to call them, told him over the span of 2 days. They brought him into his ship, or however you'd like to describe it. That's how they described it, right? And they explained to him their philosophy, how their culture works, how their science works, how their society is built. And so there's incredible detail. And here's the cool thing. So this book was written in the '60s. It was released late '60s, and then later versions rehashed in the '70s and '80s. And if you look at what's described, the technologies that are described in this advanced society, he's literally describing iPads without using the word. You know, for example, there's things like, you know, glass where the text would change and you could touch it. You know, this is like Steve Jobs level stuff, like things that he was like thinking of.

Maybe Steve Jobs read it.

He might have.

iPads were definitely in a few science fiction novels, but I love that. For sure, absolutely.

There was also the fact that they had done the cost-benefit analysis and they realized that planes aren't the most efficient way of transporting mass people. So what they have is an interplanet, like around the entire planet, train system that connects everything. And you know what it's using? Superconductors, room temperature superconductors. So, so, so they had it figured out.

Uh, the air Air-resistant suspension by then yet? I mean, just kidding, it's a Mach 31. No, but that's awesome. They were using superconductors.

Yeah, they truly were. And, you know, they talk about physics that they claim we don't know yet, which allows for their faster-than-light capabilities. Uh, and so that's part of like why I, I do think even just looking at the observables, what these pilots have been talking about, our physics Aren't perfect. Like it's definitely not able to accurately describe how these things move. So we're very much in the 1911 scenario where we're seeing superconductors for the first time, and we our physics tells us that shouldn't be possible. And so it's just a matter of time before we find new physics that actually says nope, this is how it works. And so so this this book goes into detail about their engineering, how their their houses are built to be optimally spaced, and and all these things. Things. And so what I see as sort of the future is this— they're, by the way, hardcore sustainability type folks. They are extremely like pro-sustainability. All their engineering is based on that. So, you know, the future of the materials that we create through the simulator, eventually I want them to be as sustainable as possible, right, from the get-go. And something that, you know, the book doesn't talk about per se, but This is just my own sort of dream. And I remember this was one of the first things we talked about, was this idea of merging biology and technology to the point where technology is indistinguishable from biology and from nature, right? So imagine trees that legitimately distribute Wi-Fi and handle cellular connections and all that stuff. Imagine houses that you can grow and they're very technological. They have circuits all around, but they're super sustainable and they're biological. That's sort of the end goal of this engine, is to be able to create those kinds of highly advanced materials and also the materials that allow us to, let's say, decouple from the Higgs field, the thing that gives things matter, right, and allows for these almost anti-gravitational—

That's what I was waiting for, the anti-gravity play. Anti-gravity and the reproducing circuits is pretty amazing too. I love that. It's like a growing world. Yeah, it's a growing world of technology. I mean, that's beautiful. That's an amazing image. How do you spell the name of that book? Planet Yarga?

Yeah, Planet and then I-A-R-G-A.

Okay, great. And I'll put that in the show notes for sure, just so everybody can go check that out. I think you had mentioned that there was the— you want to read the 1960s version. You had sent me a PDF, not the '70s or '80s version that was rehashed.

Yeah, I'd say it's very original. Yeah.

Do we have any evidence of the circuits that can be reproduced or grow? Like, have you— where did that idea come from, or have we started building that?

So we haven't, uh, I don't think anybody has ever built one just yet. Um, it, it really just came from— this has just been like almost a, like a childhood kind of dream of mine, like at least since I was 17. 16. It was just an obsession, you know, because like that's what the body is doing. We can literally grow these mini supercomputers. Each cell is a supercomputer as far as I'm concerned, and a very efficient micromechanical system. So in theory, we should be able to do the same thing.

I love that. Okay, man, we're coming up on— I think it's been just over an hour. So do you think that there's anything else that I have to ask you? Does the chat have any questions? Otherwise, I think— is it the same name? I'm currently reading. Let's see. Okay, look, Deep, this was an awesome conversation. I really appreciate it. What do you want to shout out right now? What should people go check out that you're working on?

Okay, I would say just get interested in quantum computing because it is the future. If you want, you know, you can check out our website. There's some high-level information on what we're working on.

ReactiveQ.io.

You got it, exactly. Other than that, Jack, I told you this from the start, long before you invested, I love what you're doing. It's so important to educate people and make science accessible because there's so many amazing things that we're doing and that's being accomplished by humans, right? And so it's amazing that you can communicate that and you have this platform and you're a really smart guy.

I appreciate that, man. I'm excited to make some videos with you. That's gonna be some great videos, especially when we can do that. So that's gonna be super fun. I'm thankful that we met and that I was able to invest in you. The things that— so go follow Deep on Twitter. That's probably where you're most active. And then you also write some stuff on Medium as well. But Twitter, it's @DeepNeuron.

Yep.

That's the best place. Neuron, like the brain. And then you guys just go follow me on Twitter @jacknazjack. You know, follow, check out the TikToks. And I think I'm gonna be reposting summaries to nazjack.substack.com. That's the best way that I can like reach you guys. And then you can also support me there. It's essentially my Patreon. And then I'm also gonna maybe edit these, maybe not, and repost these to Spotify podcast feeds. So anchor.fm/nazjack. /nasdaq is where you can find these. Um, but Deep, thank you for taking the time. I really appreciate it, and, uh, I'll talk to you later, man.

Yeah, much love, man.