Not Your Father’s Data Center - Changing the World Through Quantum Computing with Dr. Bob Sutor

Episode Date: May 11, 2021

The phrase, ‘The future is now,’ without question, applies to quantum computers. What was not so long ago a science fiction fantasy is now a reality that’s not only closer than one might think, it’s here. Dr. Bob Sutor, a technical leader in the IT industry, working for IBM for over thirty years, joined Raymond Hawkins for an exciting talk about quantum computing, how it works, and how this revolutionary technology is poised to change the future of computing.

Welcome to Not Your Father's Data Center podcast, brought to you by Compass Data Centers. We build for what's next. Now here's your host, Raymond Hawkins. Welcome to another edition of Not Your Father's Data Center. I'm your host, Raymond Hawkins. Today we are recording on Wednesday, April 14th, as we continue to pull out of a global pandemic. Happy to have with us today 30-plus-year IBM veteran Dr. Robert Suter. He is the chief quantum exponent inside of IBM. Dr. Bob, good to have you today. Thank you. Very glad to be here.

So tell us real quick before we finish intro on what is the chief quantum exponent? Well, you know, sometimes you just have to make up a title for when you're doing new things. So my training is as a mathematician. I'm a longtime IBM executive, both on the business side, but really primarily in IBM research in two stints. And over the last few years, I've been moving away from managing people to talking more about technology.

And in 2019, the end of 2019, I published a book called Dancing with Qubits, which is an introduction to quantum computing with a lot of math. But, you know, I bring you along on that. And I discovered I just really, really like writing. I really like talking. And I like somehow making these new technologies make sense to people. So whether it's through analogies or just, you know, as I said, maybe teaching a little math along the way, helping people understand what they really are. So when they're bombarded with all this information from in the news and in marketing and things like this, they have a little bit of a foundation. So we're trying to come up

with a new title here. And a lot of times, people talk about brand evangelists, and that didn't quite seem right. Well, it turns out that the concept of an exponent is really important in quantum computing, and people talk about exponential technologies. So, I've jokingly said, well, you can't have an exponential technology without an exponent. So that's me. That's right. I'm the chief one. The person who believes and promotes the truth about an idea.

So you are the official quantum computing exponent. I like it. All right. Good stuff. Well, I'm looking live as we record at Dancing with Qubits on Amazon. It comes with a four and a half star rating. So highly rated. I do have to ask.

I love books. I'll probably push the definition of a bibliophile, but I'm a big hardback guy. Is there a way to – did you ever do it in hardback? I see I can get it in Kindle and paperback. I've been talking to the publisher about that. I've been talking and we're, I believe plans are underway, but, you know, I'm looking forward to that too. I too enjoy having a good hardback book in my hands and particularly in my library. Yeah. Implied shelf life. There's a whole section in my library of signed books from the author, whether they're

people I've met in person and know that are friends of mine who've written books. So I would love to, if the publisher goes their route, if they don't, I'm still going to buy a paperback and talk you into signing it, Dr. Bob. All right, let's get rolling. So as our listeners know, we do trivia here. We give out four trivia questions. We'll do three at the beginning and we'll do one at the end. In honor of Dr. Bob's experience at IBM, they will be all IBM-related trivia questions. We're not giving you the answers today. We're just giving you the questions. Contrary to popular belief, IBM does not stand for I've Been Moved. So the easy trivia question number one is email us and tell us what IBM stands for.

Trivia question number two, tell us what year IBM was founded. And trivia question number three, tell us what IBM's original name was. It was not IBM. So those are our three trivia questions. We'll get you the fourth one at the end of the show. Thank you for listening to us. And now let's get into quantum computing. Dr. Bob, before we get into quantum computing,

can you back up, and I don't want to use the right term, whether we call it traditional computing or legacy computing, what's the right way to think about the way we do computing in an 8088, 886, x86 world where we're running processing through a microchip? How do we think about that world? Can you set us up a little bit with that before we switch to explaining to people what a qubit is? Sure, and as well as, I mean, not just the Intel line and now, of course, AMD, but the processors in mainframes, IBM's Z series.

Yeah, risk-based processors too as well. Yeah, absolutely, yeah. But they're all of a family. And the term we use is classical computing. Yeah. But they're all of a family. And the term we use is classical computing. It's the one that seems to have stuck. I know what you meant when you said traditional computing. This is the type of computing that goes back

to roughly the mid-1940s. And there are people you may have heard of, like John von Neumann. In fact, we talk about the von Neumann architecture for these classical computers. You are surrounded by them. The processor that's in your phone, that's in your laptop, desktop, maybe your thermostat, many of them in your car, these are all classical computers. And one way of thinking about it is the information they process, and that all boils down to zeros and ones, lots and lots and lots of zeros and ones. And just to kind of build it up,

when you have, that's a bit is a zero or one. When you have eight bits, you get a byte. And when you get a million of those, you get a megabyte. And then you keep moving on up to gigabytes and petabytes and terabytes and so forth and things like that. I guess I reversed terabytes and petabytes, but it's all zeros and ones. And it's absolutely astounding the infrastructure we have built up from what you actually do in the processor to what you're doing in the onboard memory. And of course, the data storage, right? In all its different forms. All comes down to pushing zeros and ones around in very specific ways. And at the low level, they're what we call logic gates. And a lot of it looks like true and false. So you look at zero and

one, and you look at zero or one. And so they have all these common names, exclusive ors. There's just a handful of them. But from that, we build up addition and multiplication and eventually get to C, and we get to Python and PHP and Java and things like that, higher level and higher level languages. It's all classical computing. And for many years, we had Moore's law, which was a hardware statement, which roughly said, and you can post this in different ways and you can put different timescales, but said roughly every 18 to 24 months, we could jam twice as many transistors

on the chip as we used to be able to. And what that means is, well, we double the functionality. But if we only did that, the chips would just keep getting bigger and bigger and bigger, and a single chip would take up a room or a house or a football field or something like that. Well, what also happened with this was that the chips, every two years, were getting half as big. So we were reducing the size and we were also reducing the amount of energy they used. And that's why your iPhone or your Android phone would have been a supercomputer 30 years ago, right? I mean, it uses very little energy. The amount of storage, of memory, of computing capacity is ridiculously large compared to what we have.

So that was Moore's Law. And there's always a debate. Is Moore's law still active? Has it slowed down? Is it asleep? Is it dead or whatever? And the fact is, with classical computing, clever people will always figure out ways of making it faster. But is it enough? Well, the theory says that anything you want to compute, don't worry, we can compute. We have the so-called theory with Turing machines and all these things, theoretical computer science, right? But when you translate that to practice, yes, in theory, I can compute something, but it'll take a million years. So that's not quite so practical anymore. It's the separation of the great hypothetical, if you will, and really building machines to do this. Or it would require so much memory, when I think of RAM,

that the number of zeros and ones, the number of bits you would need, would be the same as the number of atoms in the Earth. Well, we're not gonna build storage. I don't think any of your data centers are that large to fit a copy of the Earth. Cannot handle that much storage, that's right. Can't do that much.

Yeah, hear, hear. So therefore we hit this very practical limit, and it says, which says, are there certain types of problems that we just will never be able to really handle using classical computers? What are those types of problems? And are there alternative computing models that are not simply based on zeros and ones, that maybe will let us tackle those problems, make them tangible, right? Tractable, rather. And quantum computing is one such method.

And that's why we're focusing on it. Yeah. Dr. Bob, you gave the great example in one of the talks I watched of you around the caffeine molecule and this concept of how big. Can you give us a little bit of understanding about that? Because I thought it was a great analogy going exactly where you're going as we transition from classical computing to quantum computing, how we understand the scale of just something simple like the caffeine molecule.

Molecules and chemistry are always of interest to people when they think about computing and even not just chemistry, but biochemistry and personalized medicine and pharmaceuticals. And of course, with the pandemic, can we use computers to learn more about COVID to help us come up with perhaps additional vaccines or ways of handling it in the future. You have to start small, though. When you talk about antibiotics and you talk about viruses and you talk about DNA and so forth, those are very large. Let's roll it way back to something that's a little bit more manageable to think about. I talk about caffeine because wherever I am in the world, either virtually or in person, I can be pretty sure somebody there knows what caffeine is. It's not a very large

molecule. And if you look at any of the little stick figures, you know, it's got a few carbons and some more hydrogens and some nitrogens and some oxygens, and it's really not very big. It's not tiny. Let's call it the very small side of medium. But here's the question. If I have this very modest molecule, yet we hear about supercomputers, right? And as I discussed before, Moore's law. Shouldn't it be the case that I could take this molecule and exactly model it in a computer? And it's more sophisticated than maybe my just saying exactly model. I mean, if you think of all the ways that caffeine interacts. So how does it really work in your brain? What are the molecular reactions? How eventually does what it does keep you awake? What happens within the molecule itself?

Molecules, we're talking about atoms. Within atoms, we have electrons. Electrons move around according to the laws of quantum mechanics and things like this. So let's begin a very simple question, which is, if I were to put a caffeine molecule in a computer, how much storage would I need to represent? Is it 50 bytes? Is it 90 bytes? Is it a megabyte? A gigabyte? I mean, all of these are easily handled by even your phone, right? Is it 90 bytes? Is it a megabyte? A gigabyte? You know, I mean, all of these are easily handled by even your phone, right? Well, this is what I was hinting at before when I was talking about the number of atoms in the earth. Turns out to represent one caffeine molecule at one instant in time. And here we're just talking, if you will, about the electronic structure, relates electrons and energy and things like this. It would take in number the same size as roughly between 1 and 10% of the atoms in the Earth. So, to give you a number, that's about 10

to the 48th bits, zeros or ones. So, imagine one with 48. Yeah, one with 48 zeros. The number of atoms in the earth are between 10 to the 49th and 10 to the 50th. So one with 49 zeros, one with 50 zeros. So 10 caffeine molecules in the worst case, you need all the atoms in the earth. So think of how many molecules are in your cup of coffee, your soda, your tea, whatever it is. And of course, you know, we're talking trillions and things like that. So, we're never going to do that classically. But, you know, to nature, you know, and by nature, I mean, you know, just the way things work and the molecular reactions in your body and around you and in the planet, in the universe like this. One caffeine molecule is nothing. It's one of many, many, many, many. So nature harnesses an extraordinary amount of information, unbelievably large, and acts as a computer in

some sense, right? It controls the processes. So just as we might think of as an application, right, or software running on hardware in a data center, you could think of nature running chemical processes, right, the way molecules interact, just to control your own body, right? And as I said, everything else. That gets you thinking, saying, well, if nature is a great big computer, could we build a computer that operates the way nature does? And if we could, does that mean we could start to get some of those advantages, like being able to deal with things like caffeine? And well, the answer is yes. And the part of physics that we talk about for this part of nature, and there are different parts of physics, right? It's called quantum mechanics. And that's

where quantum computing comes from. The quantum mechanics goes way back to the early 1900s and evolved, and it's strange and wonderful and occasionally confusing, and it changes the way you think. And it's just marvelous in so many ways. And of course, the potential power as we're making larger and larger, more powerful machines, the sorts of problems that we'll be able to tackle, those are quite incredible too. So who do we think of when we think of the original quantum mechanics? Who are some of the original minds that came up with this and help us lay the foundation for what is now becoming quantum computing? There are people like Niels Bohr, Paul Dirac, Walter Heisenberg, Schrodinger.

I try to avoid references to some cliched references to Schrodinger's cat, but yes, that was actually a thought experiment regarding quantum mechanics. After a while, once people tell you these things a thousand times, it's like, please don't talk to me about the cat anymore. Or if you do, you better know the physics, what he was actually trying to do. Right, right. And also people like Einstein. And Einstein wasn't a big believer in some of the core features of it. In particular, there's something called entanglement, which is the way these quantum

systems get correlated, tightly coupled to each other, potentially from light years away. It's a standard process. It happens in your body all the time. It's just the way things work. Einstein didn't like it. A lot of quantum mechanics is fundamentally probabilistic, which means that you can't necessarily tell something, a certain property, but you can give a probability that it is probably in this state or another. And to a lot of people are saying, what do you mean? It's right there. I'm saying, well, no, it's not actually right there. It's got a 75% chance of being there and a slightly different probability of being somewhere else. And so, the mathematics behind quantum mechanics can be pretty daunting to a

lot of people. So, with quantum computing, and in particular in my book, which you mentioned earlier, I try to simplify this to the point where people can understand essentially basic math that goes into this to give them the foundation for quantum computing and then they can reason about it as a type of computing as opposed to physics got it all right so we're transitioning out of classical computing so i'm going to take the the land grant educated host and take what the princeton and harvard educated guest is saying hey frankly classical computing just doesn't have the horsepower or the capacity to handle really complex problems. The great example is nature. Nature handles an enormous

amount of information, an enormous amount of calculation, and we'll never be able to replicate it in a classical sense. So there's got to be another way that transitions us into quantum computing and the concept of, hey, is there another way to think about solving problems and looking at problems and studying problems? And that is, hey, let's frankly replicate or look a little bit more like nature looks instead of the ones and zeros. Like you said, it's either zero or it's one or it's a combination in a string of eight of ones and zeros.

That's pretty limiting. That's a brute force way of going about it. Let's be a little bit more elegant. And now we switch into qubits. So with that basic foundation, let's head down the qubit and quantum computing route. And one thing I want to make clear is, first thing is quantum computers aren't going to up and replace classical computers. They're going to work together. Classical computers do many things perfectly well. In fact, you can't even talk to a quantum computer unless you've got several classical computers. Great point. So they're complementary. The other thing is, quantum computing isn't necessarily suitable for every type of hard problem that we might

come across that classical computing may have. Certain classes of problems. We're learning much more about that. We're learning much more about saying, hey, we have a feeling that this is amenable to it. We will develop algorithms. We'll reuse what we have and try to attack that problem. But there certainly are going to be things that quantum's not going to help you either.

Let's put it that way. Okay. Not the answer for everything, but answers for big, complex things. Got it. Okay. At the basic level, let's start with a qubit and the challenges that come from there. And let's grow from there. Okay. So we started with a qubit and the challenges that come from there and let's grow from there. Okay. So we started with a bit and a bit, as I said, was zero or one. And we're never going to

lose the bits, right? We're going to start with bits and we're going to end with bits. And in the middle, we're going to use some other things. And so we're going to extend the idea to a quantum bit and that's where qubit comes from. It's kind of a merger of those idea to a quantum bit. And that's where qubit comes from. It's a kind of a merger of those two words, quantum bit. And it's spelled Q-U-B-I-T, just to fix it. Got it. Quantum bit. Got it.

And people often hear about it accompanied by a statement, which, again, bugs me a little bit when they say it, because it's mostly cute if they don't actually know what they're talking about, but I'll explain what it is. And that statement is a qubit can be zero and one at the same time. Okay. So let's dissect that a little bit. So suppose I told you this, so I'm going to translate the problem somewhere else. Just for a moment, I'm going to say, Raymond, I want you to walk four blocks north and three blocks east. And you might say, okay, that's easy. And, you know, when you get there, you call me on your phone. You say,

I'm here. And I'm going to say, Raymond, the most amazing thing happened. You are north and east at the same time. Isn't that incredible? Could you imagine anything so special? And you're saying, big deal. Okay. Imagine that I just walked it. Of course, I can. Yeah. Yeah. And you're saying, okay, well, this idea of what I'm essentially saying is two dimensions, right? Walk north and walk east, you know, walk vertically and horizontally, you know, we get this idea and we get this idea of two coordinates, if you will, right? So, four blocks north, three blocks east. And from high school in geometry, we could draw lines and parabolas and things like that and, you know, xy coordinates. Quantum computing for one qubit is that with a few extra rules. And so, I'm going to replace north and east with things I'm just going to happen to call

zero and one. And if it helps you not to get confused with the number zero and the number one, you write them out, O-N-E-T-W-O, right? And that will replace the words north and east. And so now if I say four blocks one and three blocks east or three blocks zero, right? You'll say, okay, I'm with you. I don't know why you're going there, but you know, words and things like this. And I'm going to write them a little differently, right? So, okay, instead of using letters, I'm going to use some fancy notation.

In fact, I mentioned Paul Dirac before, beginning part of the 1900s. He came up with what he called the braquette notation. So, I'll write zero as a vertical bar, a zero, and then a greater than sign. Mathematicians love to make up new symbols and representations for things. There was nothing handy. He came up with that. It allows you to manipulate these. He, in fact, was a theoretical physicist. So there are new symbols, and you might see this, you know, vertical bar zero, greater than symbol, vertical bar one, greater than symbol.

That's the zero and one that we're talking about. All right. OK, so we're still good. We're still saying, well, you go a certain amount in one direction, a certain amount the other direction.

Well, it turns out that I'm going to put restrictions and Raymond, I'm not going to actually let you walk four blocks and three blocks. I'm going to make you do some stranger numbers in front of this. I'm going to make you walk square root of three over two in this direction and one half in that direction. And the reason why, if you think of a circle, that point, square root of 3 over 2 and 1 half, is actually on a circle of radius 1 around the origin, the so-called unit circle.

And so, all the points next to my 0 and 1, right, are going to, in some sense, correspond to points on the unit circle. Raymond, I'm not going to quite let you go the four blocks north and the three blocks east. With quantum computing, I have to put other sorts of restrictions on those numbers. And so, for example, what I'm going to do is for the first number, just in this example, I'm going to choose square root of 3 over 2. Now bear with me, you know, that number, that seems a little weird. But for the other number, I'm going to choose a much more standard number, which is 1 half. Well, square root of 3 over 2 and 1 half may seem like strange numbers, but they're not

if you look at geometry. Those are points on the unit circle, which you may remember from high numbers, but they're not if you look at geometry. Those are points on the unit circle, which you may remember from high school, from trigonometry. You look at all the points just that live on a circle around the origin, right? And the circles of radius one. They're a whole lot. They're an infinite number. And so, what I'm really saying is that those numbers in front of my zeros and ones are going to be restricted in that way, right? They have to fall on the unit circle.

Ed's saying, all right, Bob, I'll accept that. Why not? It seems like a math sort of thing. Well, it turns out something else weird is going on here because I went from a bit which was 0 and 1 to a qubit. So remember, I just, you know, could be either a 0 or 1, but a qubit could be, well, is two numbers. As I said, one number is in front of the 0 and one number is in front of the 1.

And I just said one of them could be square root of 3 over 2, and the other could be 1 half. Okay. Point is, a qubit has two pieces of information, two very rich pieces of information. And in fact, it can represent an infinite number of pieces of information. One bit can just be zero or one, but one qubit can represent an infinite number of pieces of information or the values that it can be. And that's what gives you so much power. You're going from really just zero one to two whole dimensions worth of space, really. I gotcha.

Right. And then we have to put some restrictions on this, as I said about the unit circle and things like this. Now, there's one other thing which I got to tell some restrictions on this, as I said about the unit circle and things like this. Now, there's one other thing which I got to tell you about with this, because I said we start with bits and we end with bits. Raymond, I made you walk across the city there and first remember four blocks north and three blocks east. I'm going to make you decide whether you'd like to tell people that you are north of where you started or east. You know, I'm not going to let you, Raymond, say you're northeast. I'm going to force you or assert you are north of where you started or where you are east. And so, you know, I said, well, four blocks north and three blocks east. And you're going to say, you know, I'm a little bit more north than east. So, probably if I had to choose, I would tell people that I'm north.

And somebody else I might ask, you say, you know, I really like being east. And I am actually a little bit east, you know? And so, what the heck? I'm going to tell people I'm east. Well, these numbers correspond to probabilities because once we're done working with qubits, and I haven't really talked about what we do with them, but once we're done manipulating them, we have to force them back to being zero or one. And these numbers in front of them correspond to probabilities of whether we'll get zeros or ones. So, if I roll on back, right, to first of all, let's keep it on north and east for a little while. There'll be more than a 50% chance that

people will say they're north versus east. Okay. My slightly more mathematical example, square root of three over two and 1 half, turns out that the probability of choosing that first one is 75%. And the probability of getting the second one is just 1 half. For those of you following along with the math, I squared each of those, right? And that's how I got those probabilities. So, not only is there geometry to qubits, and not only is there this representation of an infinite number of values, but there's this tie-in with probability. So putting all this together and adding more qubits,

what we're doing with quantum computing and all the manipulation is being able to move from just very simple zeros and ones and lots and lots of those to these gigantic spaces, really huge, huge spaces. In fact, one might even say exponential spaces, right? In which to solve our problems. And the things we do once we do that is we're nudging the state of the system toward the most likely answer. And then at the end, we say, you got to decide. Are you zeros or ones? This is called measurement.

And we end up with a sequence of zeros and ones. And there are rules here that tell us to say, okay, well, this is a certain probability of being the correct answer. Perhaps we have to repeat the calculation a certain number of times to get even more confident. But it is this growth with qubits, the amount of information. And every time we put in one more qubit, we double the size of our space.

We go from two dimensions to four to eight to 16 to 32. So this is why quantum can handle so much. And in fact, with 160 qubits, we could represent that caffeine molecule, the one that's impossible forever, the one-tenth of the earth. Yeah, just can't get big enough in a traditional computer, right? Classical computer. But within a quantum computer, right? With an appropriate amount of work, and there's future work that we have to do that I'm glossing over a little bit here. But the idea is that we'll be able to actually manipulate problems inside a quantum computer that use a tremendous amount of information.

All right. So, I'm going to go back to the land grant guy from the South, trying to dumb it down to make sure I get it. So when I think of ones and zeros, I think of simple like a dip switch. It's either zero or one, it's A or B, it's up or down, whatever. This is dip switch computing. And I'd multiply it across eight to get my bite. What I think I hear you saying is, Raymond, don't think of that dip switch as only having two positions. Think of it of having not countless, but a large number of positions in a two-dimensional layout. And I love the unit circle idea of all the different positions. That's what I get with a qubit. I don't get the restriction of a one or zero, open or shut, A or B. I get a wealth of positions is really what you're telling me. That's right. That's right. And that those positions grow

exponentially as I pair, as I grow my number of qubits in that sequence or processing or computer. That's right. Another way, I use the word dimensions and I do tend to fall back to mathematical terms. Another way of thinking about this is I said a qubit can represent two pieces of information. Two qubit represents four pieces of information. Three, we double that. Eight, we double that again. So by the time you get to just 10 qubits, that state that you have right there is representing over a thousand pieces of information. In fact, they're very significant numbers. They're not just zeros and ones, they're significant numbers. So, we've estimated that by the time you get up close to 300 qubits,

and here I'm talking about a slightly future quantum computer. We're not there quite yet. I'm still a little bit in the theory, but so just roll forward a few years here. By the time you get to about 300 qubits, the amount of information it can process is greater than the number of atoms, corresponds to, greater than the number of atoms in the observable universe. At 300. At 300. And by the way, we've got to make a lot more than 300. We have to get up. These are the so-called logical qubits. We're going to need thousands, tens of thousands of these. Got it. Got it. So it just blows your mind. And so this is why at some point, you got to let go of these traditional analogies to classical.

Right. Linear ways of thinking of how it compares to classical. All right. Let's go down two different tracks and I'm going to lay them all out because I want you to weave them together however you want. I've got two or three questions that burn in my brain as I think about computing and I'm going to lay them out and you take them how you want, Dr. Bob. Question number one, customers say to me all the time and come to us and ask, you know, hey, how does this data center, how big, how do we future proof it? How big does it need to be? Because computers keep getting in smaller and faster and, you know, quantum computers are going to be here next summer.

And when they get here, everything's going to change. So sort of that, where are we on the roadmap? Are they coming next summer and going to change the world? That's question number one. Question number two, I don't understand the temperature component of quantum computing. I understand, I mean, in our business, right, we provide a building, we provide electricity, and then we provide heat rejection to cool the computers. I don't understand why quantum computers, where they have to be so cold, I mean, ridiculous cold. So that question. And then third, where are we, you know, as a race? Where are we and how many qubits we can do? What's practical and where do you see it going? So that's three kind of questions all rolled into one. But if you'll take those three themes and help me understand all three of those.

So quantum computers are primarily cloud-based and they are contained in a unit. You might call them a pod, if you will. The electronics and the cooling, which I'll return to in a moment, are all contained in a unit. The IBM Q-System 1 that we talk about, if you've ever seen a photo of this, it's a glass enclosed quantum computer. It has a stainless steel cylinder in the front. Just to give you an idea of the dimensions of that, it's about nine feet by nine feet by nine feet or three meters by three meters by three meters. That's about the size of it. Most people will want to access quantum computers via the cloud because over the next few years, we'll be significantly increasing their capacity. We will be adding more qubits. The qubits will be better. We'll be doing miniaturization.

We'll be doing lots of the normal things that happen with hardware. So there's really nothing anyone has to worry about in terms of existing data centers right now. So in the middle of a calculation, wherever it's happening, it could be on the cloud, it could be running in a container. Anywhere in the world, you could reach out across the cloud,

talk to a quantum computer, get your result back, go on with your business. So it's not going to impact you that much. We don't anticipate quantum computers being powerful enough to do better than what classical computers can do until roughly mid-decade. And I'm fudging on that because there are going to be small examples of this, but people are going to want to know about their use cases and things like this. This is what we call quantum advantage. It's when really- Mid this decade, Dr. Bob. Yeah, that's right.

And the idea is that you've got to be able to get to the point of doing significantly better than classical computers. If you're just doing about the same, why bother? Just keep doing what you're doing. And so once we comfortably start doing, as I termed it significantly, whatever that means, you know, I'm not defining it, then we'll start seeing quantum computing getting integrated into work streams. Now, one thing I will say is that the Cleveland Clinic, we had an announcement with them a couple of weeks ago. We will be installing a quantum computer in Cleveland for their use

because they will be doing a lot of direct research related to, of course, to health care and biochemistry and things like that for which they want full access to. But primarily, most people should think of it as cloud-based. Second thing I believe was about temperature. So I started by talking about atoms and electrons and molecules. Well, there are other things, photons, right? If you think of a particle of light, a photon. Quantum computers work by very careful, very low energy manipulations of quantum states. And so, forgetting for the moment just the cold temperatures, if I were to hit a quantum computing chip with one photon, just one photon of light, and I think

becoming one single photon coming out of a laser, that would have so much energy, it would completely destroy the quantum computation. So what this means is that any stray RF interference, right, any variations in temperature that could somehow affect the quantum state inside the physical qubits would disrupt the calculation and cause them to be wrong, right? It would introduce noise. You could think of it as static. So, you know, kind of in a perfect world, what you do is you completely isolate this. You chill it down to close to absolute zero. So this means everything else slows down. The only thing that's happening is what you are intentionally forcing through that device.

Stray, as I said, photons, RF, whatever, just isn't happening. But you can't completely isolate it because you have to talk to it, right? And so you have to expect there's going to be a certain amount of noise with it. We try to minimize that. We do noise mitigation, it's called. And eventually we will get to the point

where we'll be able to do error correction, make it fault tolerant. And there's a lot of research on that. Toward the end of this decade. You'll probably start seeing even some of that. So that's why there are different qubit technologies that say they are more or less tolerant or that you don't need temperature, it's this cold or that, but there's always a gotcha. It's always a gotcha. The big thing with quantum computers, and as I said, you can build them using different technologies. We do what's always a gotcha. The big thing with quantum computers, and as I said,

you can build them using different technologies. We do what's called superconducting. They're ion-trapped, they're photonic, there's a few others like this, is scalability. To be honest with you, I don't care about anybody who has a two-qubit quantum computer. You can't do anything useful with two qubits. You have to start getting more and more qubits. And you have to start breaking 100. You have to eventually break 1,000. You have to think of ways of connecting more and more qubits. When you add qubits, it's not like just adding memory. You don't walk over and stick in a car and say, suddenly, your device has more memory. All the qubits have to work together. You have to have very sophisticated control systems to do this.

So our roadmap, the IBM roadmap, is that later this year, in 2021, we will offer a quantum computer that has more than 100 qubits. We will roughly triple that to a little bit more than 400 next year. And for the first time ever, we anticipate 2023, we'll have over a thousand qubits in a quantum computer. At that point, we will be moving from, if you're thinking of a classical board, circuit board, you move from individual chips to multiple chips talking to each other to quantum motherboards. And these will all be kept very cold by virtue of the way the freezers or the refrigerators look. They will be round. And you can imagine them almost being stacked like pizzas with many qubits and control systems that allow us to talk to qubits on one being able to interoperate with

qubits on another. So that's how they will grow. So the next three or four years are going to be really critical as we push up and beyond to 1,000 qubits. So Dr. Bob, a couple of quick questions around that. If my Q1 today is nine feet by nine feet by nine foot cube, that's pretty significant. What do you imagine a 1,000 qubit machine looks like? That's question number one. Question number two, you gave me the notion that at 10 qubits, you know, with thousands and thousands of analysis, at a thousand qubits, what are we talking about

as far as compute power or computational power? Well, I'll let you do the math. It's two to a thousand. It's a bunch. Yeah. It's a whole bunch. Yeah. Yeah, so's a whole bunch. Yeah. Yeah.

So it will physically get bigger. So the complete system now pretty much fits in that nine by nine by nine. The actual fridge today. So it's an enclosure that's kept it vacuumed. That, as we said, at the very bottom of it's kept close to absolute zero. You want to think of that cylinder as maybe two feet across by about four feet high. Okay. For the so-called super fridge, which will house thousands and thousands of qubits,

these so-called pizza-shaped quantum motherboards, that you're going to be thinking about something, just the fridge about five feet across and 10 feet tall. Oh, wow. Okay. There's a huge difference between 27 qubits and thousands or tens or hundreds of thousands. That's not counting the extra refrigeration units and things like that. So, it will take up a little bit of room, but room is not the problem at this point. Even add that for the extraordinary computational power, that's cheap space-wise. Because remember,

we're not just replacing classical computers for the heck of it. These are going to be reserved for the most difficult and certain classes of problems. So, we'll need more of them, but you're not going to imagine filling your entire data center with them, right? Right. And you're concerned about footprint. As I look at the pictures of quantum computers today, I see lots of what I would call coiling or tubing. What's going on? What's the right term and what's going on there?

So the, yeah, if you see them, and I encourage anyone, if you just look IBM Quantum Flickr, there are many, many photos out there if you're just curious what some of these things look like. It looks like a chandelier, first of all, to be clear, a golden chandelier. Its proper name is a cryostat. Cryostat comes from the Greek meaning cold and stable. And the quantum device is actually way, way down at the bottom of that. Okay. And that is what is enclosed in the dilution refrigerator, the freezer, if you will. And everything you see there is really, it's either structural to hold it together. It's either the electronics to control what's happening in the quantum device,

or it has to do with the refrigeration. And so if you look at one, you can see some golden cables that come down and then they loop around in a circle and they continue on their way down. Those are microwave control cables. And that's how we talk to the qubits through microwaves. And so signals are brought down to the qubits and signals are returned from the qubits. What does the loop do for us in that path? May I ask just where you're calling in from geographically? Yeah. Oh, I'm in Dallas, Texas. I'm calling in from upstate New York.

Typically, we have more of a winter than you do, though you had some quite an experience this winter. We got one this year. Got one this year. If you are in the north, you're very used to seeing on telephone poles loops of extra cable. And what they are is their thermal protection because when temperatures get very low, below freezing, wires shrink. And if you didn't have those loops, the wires would snap. And so you can imagine as we chill that down

close to absolute zero, the loops, which are maybe the size of a nickel right now, shrink down. And I don't know how small they get, but maybe you could imagine they're shrinking down to about the size of a dime, right? I gotcha. Okay. Also, within the cryostat, there are many different types of metals. There are exotic metals, right?

But there's brass and there's gold. It's actually gold-plated. Gold reflects infrared radiation, which corresponds to heat very well. If you look very carefully, you'll see some hinges and some other structural devices so that the entire cryostat, as we chill it down from room temperature to close to absolute zero, it just very nicely shrinks slightly and doesn't rip itself apart. I got you. I see. Fascinating. Well, Dr. Bob, this is incredible stuff. I think you debunked a few myths of quantum computing is going to take over the world and take over the data centers next year and help us understand a little bit better. I'll be candid, Dr. Bob. I think if you'd be

willing to come and do another episode with us, I got about 65 more questions that I just didn't get to. If you'd be willing to join us again, our listeners are sort of three or four continents worth of them, but mostly data center folks. And I think they'd be fascinated by what you know and what you understand. I'm going to get us one more IBM centric trivia question in and thank you for your time. And then we'll get out of here IBM-centric trivia question in, and thank you for your time, and then we'll get out of here. So once again, thank you for joining us for Not Your Father's Data Center. Dr. Bob Suter, the exponent for quantum computing at IBM. And our last IBM trivia question, IBM has had five Nobel Prize winners to qualify for our Amazon $500 Amazon gift card.

Answer our first three questions and then give me one IBM Nobel Prize winner. Again, you can email that to me at rhawkins at compassdatacenters.com or you can tweet us at Compass DCS. So question number one, what year was IBM founded? Question number two, what was its original name? What does IBM stand for? And name any one of five of IBM's Nobel Prize winners. Dr. Bob, you've been awesome.

This is so, so good. I really, really appreciate it. Would love to have you again. Thank you for demystifying a little bit of quantum computing. And stay safe. I think you told me you got both vaccines, so you're in good shape. And I hope our whole world is that way soon enough. Thank you.

Well, thank you for inviting me, Reverend. It's been a lot of fun.