 on theCUBE studios in Palo Alto and Boston. It's theCUBE, covering IBM Think. Brought to you by IBM. Welcome back everybody, you're watching theCUBE and our continuous coverage of IBM Think Digital 2020 event. It's, we've been wall-to-wall for a couple of days now and we're bringing you all the action. Dave Asfa is here. He is the global lead for quantum education and open science at IBM Quantum. Gabe, great to see you, thanks for coming on. Yeah, thanks for having me here, Dave. You're very welcome. Love the discussion on quantum, but I gotta say, so I'm reading your bio. In your bio, I see quantum algorithms, experimental quantum computation, nanoscale device fabrication, cryogenic measurements and quantum software development, hardware programming, et cetera. So you're obviously qualified to talk about quantum, but how can somebody learn about quantum? Do I have to be like a rocket scientist to understand this stuff? So Dave, this is one of the things that I'm very passionate about. It's also my job to make sure that anyone can learn about quantum computing today. So primarily what I'm focused on is making sure that you don't need a PhD to program a quantum computer. When I was going through my graduate studies trying to learn quantum computing, I needed access to a lab. So I had to go to graduate school to do this, but in 2016, IBM put a quantum computer on the cloud and that dramatically changes the field. It allows access to anyone from the world with just an internet connection to program a quantum computer. So the question I'm trying to answer on a daily basis now is the question that you asked, how do I learn to program a quantum computer? Well, I'm trying to make several resources available for you to do that. Okay, well, let's talk about those resources. I mean, you have quantum, you have access to quantum computers. I talked to Jamie Thomas the other day. She said that you guys, it's all available in the IBM cloud. I can't even imagine what the infrastructure behind that looks like, but as a user, I don't have to see that. So how do I get access to this stuff? So there are several quantum computers available on the cloud now. And every time I think about this, it's fascinating to me because I needed access to a lab to access these things, but now you don't. You can go to quantum-computing.ibm.com and get free access to several quantum computers. Now the question becomes, if I give you this access to the quantum computers, how do you learn to program them? The software that you use to program them is called Kiskit. Just like we've made access to the quantum computers open for everyone, our software is also open source. You can access it by going to kiskit.org. That's Q-I-S-K-I-T.org. And if you go in particular to kiskit.org slash education, we've put together a textbook to help you go through everything that you'd learned in a classroom about quantum algorithms and to start programming the real quantum systems yourself. So everything's ready for you to program immediately today. What was the, can you give me the IBM quantum-computing URL again? Yeah, that's quantum-computing.ibm.com. Once you create an account there, you immediately get access to several quantum computers, which is an impressive thing to think about. The cryogenics that you mentioned earlier, the hardware, the software, all of it is ready for you to take advantage of it. I got to ask you, I know it's sort of off topic here, but if I had a look under the covers, I'm going to see some big cryogenic unit with a bunch of cables coming in. Is that right? That's exactly it. Very cold inside of that unit. That's right. So the way to, here's the way to think about it. Outer space is about 200 times colder than room temperature. And the temperature where the chip, the quantum chip sits is another 200 times lower than that. So we're talking very cold here. We're talking only 15 milli kelvins above absolute zero. That's 0.015 degrees above absolute zero. So it's a very cold system and you'd have several wires that are going down into this cold system to try to communicate with the quantum chip. Well, and what's exciting to me about this whole thing, Abe, is it brings me back to the sort of the early days of computing and huge rooms and now look where we are today. And so I would expect that over the next many decades you're going to see sort of similar advances in quantum and being able to actually execute at somewhat higher temperatures and miniaturization. It's a very exciting time. And we're really obviously at the very, very early innings. But I want to ask you just in terms of, if I'm a programmer, I'm a Java programmer, can I actually come in and start using quantum computing? What do I need to know to get started? So you need to know two things. The first thing is you need to be familiar with any programming language. The easiest programming language to pick up today by far is Python. So Kiskit is built based on Python. So if you're able to quickly catch up with a few things in Python and we have a chapter dedicated to this topic in our textbook, that's the first thing. The second thing is simply having the ability to learn something new, simply being excited about this field. Once you have those two together, you can learn quantum computing very quickly within a few months. The question then becomes catching up with the research and reading research papers. That can take some time, but for us to be able to talk through a quantum program takes only a few days of reading. Let's talk about what some of the folks are doing with quantum. We talked again to Jamie Thomas and she gave me some examples. Not surprisingly, you saw, for instance, some examples in pharmaceutical and sort of other obvious industries, but then banking came in. But what are people doing with quantum today? Maybe you could add some color to that. Primarily, most of the work in quantum today is focused on understanding how to take problems in industry, whether it is to understand how to simulate molecules, whether it is to understand how to optimize a financial portfolio, taking those problems and mapping them onto a quantum computer so that they can get solved. So you'll see various industries exploring how to take their problems and map onto a quantum computer. So one exciting one that I'm seeing a lot of progress in is chemistry, learning how to simulate molecules using these quantum computers. As someone with a physics background, for me the exciting thing to see here is also how people are using these quantum computers, which fundamentally are taking advantage of quantum mechanics to simulate other quantum systems. So to understand nature better by using nature itself. So this is another exciting progress that we're seeing in the field. So exciting both from industry and from educational and science purpose. So obviously it's a fascinating field and people, as you say, with curiosity can get excited about it, but let's say I actually want some kind of career in quantum. I mean, what? Well, how would people sort of get involved? Do you see on the horizon that this is going to be something that is actually going to be a vocation for young folks that want to get involved? Dave, I could not tell you how challenging it is to find people who have the right combination of quantum computing knowledge and classical programming knowledge. So in order to be able to take full advantage of the quantum systems today, we need people who understand both the hardware and the software to some level. And there is an extreme shortage of that kind of talent. So the work that I'm focused on is exactly this problem of solving the workforce development problem. So we're trying to make sure that people have access to anything that they need in order to be able to program a quantum computer and to learn how to then map their own problems into these quantum computers. In the future, the question becomes, let's say we now understand how to use quantum computers to make financial portfolio optimization. Every bank in the world is going to want someone to implement this in their systems, which immediately creates lots of jobs. So this is going to become something that's in demand once it becomes possible on a large quantum computer. So today's the right time to learn how to work with these quantum systems so that when the time comes that there are industries that are needing quantum skills, you're ready to be hired for those positions. Okay, so big skills gap. You kind of gave an example in financial services, what maybe some of the other things that you hope that people are going to be able to do over time with these skills? I cannot overstate how important it is to learn how to simulate chemistry problems on these quantum computers. That will have impacts anywhere ranging from whether it's drug design, whether it's making better efficient solar panels, more efficient batteries. There are many applications where you'll see impact from these. So there are many industries that can benefit from understanding how to work with quantum computers. And that's something exciting I'm looking forward to see. You read in a press that we're at least a decade away from quantum being a reality, but you're giving some examples where it's sort of here today. I feel like it's going to come in layers. It's not going to be one big bang. It's going to come over time, but maybe you could frame that for us in terms of how you see this market developing. I don't even want to call it a market, but just this technology developing into a market. What has to take place and what kind of things can we expect along that journey? Sure. So I think it's very important to keep in mind that quantum computers are a fairly young technology. So we're improving the technology as we go and there has been dramatic improvement in the technology itself, but we're still learning as we go. So one of the things that you'll find is that all of the applications work that's being done today is exploring how to take advantage of a quantum computer in some way. If I immediately gave you a fully functional, perfect quantum computer today, you wouldn't even know what to do with it, right? You need to understand how to map problems onto that quantum computer. So in preparation for that time several years away, you'll see a lot of people trying to learn how to take advantage of quantum computers today. And as they get better and better, learning how to take advantage of whatever incremental progress is being made. So as much as it seems like quantum computers are several years away, many people are learning how to program them today just in preparation for that time when they're ready for use. And my understanding is we're going to get there with hybrid models today, you're using traditional microprocessor technology to sort of read and write data from quantum. That's likely going to continue for quite some time, maybe indefinitely, but perhaps not. Right, so Dave, the important thing to remember is that a quantum computer works jointly with a classical computer. If you ask me the question of how do I optimize my portfolio, the numbers that I would need to compute with are classical, there's nothing quantum about them, these are numbers. So there's classical information that you then have to take and map onto the quantum computer. And then once the quantum computer is done, you have to take the data out of that computer and then turn it back into classical information. So you'll always have a quantum computer working jointly with a classical computer. The question now is how do you make those two work together so that you can extract some benefit that you couldn't have attained with just the classical? What do you see as the big sort of technical challenges that you're paying attention to? I mean, is it getting more qubits? Is it coherence, working at higher temperatures? What are the things that you see as the scientists are working on to move things forward? So one of the things that I can do immediately, Dave, if you and I agreed right now is we can go to the lab and take a quantum chip and put a thousand qubits on that quantum chip. That's fine, we can do that immediately. The problem that you'll find is that it doesn't matter that you have a thousand qubits if the qubits are not good quality qubits. So the technology should focus on improving the fundamental qualities of the qubits themselves before scaling them up to larger numbers. In addition to that, as you're scaling to larger and larger numbers, new problems come into the picture. So making better qubits, scaling up, seeing how the technology is doing, learning new things and then scaling further up, that seems to be the model that's working today. So in addition to monitoring the quality of the qubits themselves, I'm monitoring within the technology how people are implementing solutions to scaling problems. In addition to that, another important problem that deserves a lot of attention is the question of how do you make good software that can take problems and map them onto quantum computers? In quantum computing, when I say I'm running a quantum program, really what I'm doing is building a quantum circuit and then running that quantum circuit on the real device. Well, if that circuit has certain operations in it, maybe you want to tailor the way you transfer that circuit onto the device in a way that takes full advantage of the device itself. But then in order to do that, you need to write good software. So improvements in the software, along with improvements in the quantum technology itself, will be how we get to success. And at IBM we're focused on finding a metric that wraps all of these things together and it's called quantum volume. And we're seeing improvements in the quantum volume of our systems as we go. Yeah, Jamie talked about that. You're essentially taking the key metrics and putting them into a single observable metric that obviously you can track over time. So I want to ask you about security. A lot of people are concerned that quantum is just going to blow away everything that we know about cryptography and all the passwords and security systems that we've put in place. Is that a legitimate concern? Will quantum both get us into that problem and take us out of that problem? I wonder if you could talk about that. So there are two ways to think about this problem. One is just fundamentally, if you ask me, what does it take to put the cryptography that has our bank accounts safe over the internet connections that we use, it takes roughly about a thousand good qubits. Okay, if I tell you a thousand good qubits, that doesn't seem like a lot of work. But when you think about it, what it really requires is an overhead of about a thousand qubits for each qubit that we have today. So the numbers of qubits that you'd need are in the millions in order to put the kind of cryptography that we're using today at stake. So certainly there's a long way to go. That's one aspect of the story. The other aspect to the story is that we should never underestimate the progress of technology. So even though the time when we can use Shor's algorithm, which is the algorithm that can be used to break the cryptographic algorithms like RSA, even though that's several years away, you still want to be ready for that time. And what that means is, if you have sensitive information today, you need to be making sure that that information itself is protected with quantum resistant cryptographic techniques so that when the time comes, you can't use a quantum computer to get back the data from today and break. So two perspectives, one is we're quite a while away from this kind of danger, but at the same time, it doesn't mean we should be complacent today. We should be taking preparations to make sure that our critical information is protected. Yeah, so that makes a lot of sense. But when you say we're a ways away, are we decades away? Are we years away? I mean, can you quantify that in any reasonable way? It's hard to speculate on that number. So I'll refrain from giving you a specific timeline. Just to give you an idea, the quantum bits that were in development 10 years ago had a coherence time. So the amount of time that they can store the quantum information of roughly a hundred times smaller than they are today. And 10 years ago, if you asked people, how do we get to a hundred times better qubits? Nobody would have been able to give you a clear answer. You could have guessed some ways, but nobody would have been able to tell you, we'll get there in 10 years, but we did. So instead of coming up with estimates of timelines that depend on what we know today, it's probably a better idea to monitor the technology as it goes and keep adapting to it. We're probably talking this century. We're talking this century, hopefully. It is my luck's mission to enable enough people to learn quantum such that it happens within my life. Very exciting field, Abe. I can't thank you enough for helping us educate the audience and myself personally. It's really, I'm so fascinated by this. It's something that John Furrier and I and the team have been really focused on. And I think it's really time to your point to start digging and start learning. You've given us some resources there. Give us those two resources one more time. There's the IBM site and the QKit site. What are those again? Just to wrap. So you can access the quantum computers at quantum-computing.ibm.com. And once you're there, the way to learn how to program these quantum computers is by using Qiskit, which you can learn about by going to Qiskit.org slash education. Once you're at that education page, you can access our textbook, which we make open source. It's a textbook that's co-written with professors in the field and is open source. So it's continually getting updated. You can access that textbook at Qiskit.org slash textbook. If you go to our YouTube channel, you'll find several videos that allow you to also learn very quickly. So Qiskit's YouTube channel is another great place to look. So lots of resources, Dave. And that's Qiskit with a Q, which is why I wrote it that way. So, all right, Dave, thanks so much. It was great to see you stay safe. And next time, hopefully we'll see you face to face and you can draw some cool pictures to help me understand this even better. Dave, it was nice talking with you. I look forward to learning quantum programming with you. All right, cheers. And thank you for watching everybody. This is the cubes coverage of the IBM Think 2020 digital event experience. We'll be right back right after this short break.