What is the potential impact of Quantum Computing on your enterprise IT organization? This podcast discusses how Quantum Computing is upending our knowledge of cryptography and security by cracking things that are otherwise invincible.We look at where Quantum Computing falls within emerging technologies and how i’s moving rapidly through the Hype Cycle.
The Impact of Quantum Computing on Your Enterprise IT
Greg Turner: Welcome to our continuing podcast series at the Disruptive Enterprise. Today, we’re going to talk about disruptions that may occur in the future as a result of new technology being developed today, specifically quantum computing. And to help me explore this topic is Bill Kleyman. Bill Kleyman is an Advisory Board Member for MTM Technologies, and he is the Executive Vice President of Digital Solutions. He is a writer, contributor, speaker, author, industry analysts, and all-around good guy. And we are very pleased to have him here today. Welcome to the Disruption Enterprise, Bill.
Bill Kleyman: Oh, my goodness. Thank you so much, Greg. You and I are going to have to pump this energy up because we are seriously talking about quantum computers today. And I think everybody who’s listening to this is on the edge of their seats just as excited as you and I are to be talking about this because who doesn’t want to talk about the future. I mean, you’re talking about quantum machines, like beyond the realm of the normal. I think this is really cool. I’m excited to be here. Thanks for having me, Greg.
Greg Turner: Thank you, Bill. Yeah. So, you’re absolutely correct. There is a lot of buzz around quantum computing. I’ve seen recent articles from IBM, Microsoft, and Google, just to name a few of the big players, but why is it, Bill? Why is there so much buzz around quantum computing?
Bill Kleyman: Oh, my goodness. You know what? Quantum computing aims to revolutionize the way we do things, right? They promise to run calculations far beyond the reach of any sort of conventional, even supercomputer. They’re aimed to revolutionize the discovery of things like new materials by making it possible to simulate the behavior of matter – and check this out – down to the atomic level. They can upend our existing knowledge in concepts of cryptography, and even security by cracking things that are otherwise invincible. I mean, there’s new concepts around things like quantum cryptography. And even – this is where it gets really interesting – supercharge, things like AI by crunching through data far more efficiently. So, we are, theoretically, Greg, and everybody listening, approaching the point where quantum computing and a quantum computer can effectively solve problems that classical computing simply cannot. Effectively, we’re getting to a point – and we’re going to talk about this little bit later – of something known as quantum supremacy.
Greg Turner: That’s awesome, Bill. And knowing what I know about quantum computing and technology, I can see why people are so excited, In our Disruption Enterprise series, we talk a lot about intelligent automation and artificial intelligence as being a driver of disruption in today’s market, not to take you out of your rhythm. But could you tell us a little bit more about what is quantum computing?
Bill Kleyman: Oh, my goodness. Not to take me out of my rhythm, Greg, you are so kind. Listen, if I don’t even know my own rhythm, I don’t know how you’re going to take me out of it, but you’re asking me to talk about quantum computer. So, I’d love to do this. Obviously, I’d love to do this with a white board, and so you guys could see me. But if you’re listening to this alone, just sit down and follow with me along, okay? So, imagine you have a traditional computer, a traditional computer in its normal state. If you’re sitting on a machine right now, you might have a phone with you, you might have a laptop, you might have a traditional computer right underneath your desk. Those things have very, very traditional, let’s call them processors. And a normal state of a machine is either (A), follow me here, a 0 off or a 1, the on. That’s called a classical bit, either a 0 or a 1.
Bill Kleyman: But quantum bits, also known as qubits, they process tasks in a revolutionary way. So, again, where we see information being stored and created as a series of ones or zeros, on or off, the very simple basics of mechanical operations – check this out – there is no classical architecture here because qubits, quantum bits can represent both values at the same time. And this is known as superposition. So, kind of like a light switch, right, where you have on or off. Well, the superposition element here is that it could be both on and off at the same time. It’ll be like shortage if it’s CAD, but we’re talking about quantum computing. And as you add more qubits, that computational power, obviously, increases. So, qubits can further be linked with other quantum bits in a process called entanglement.
Bill Kleyman: Now, we’re not going to get to sci-fi here and too down into the weeds here, but when combined with superposition, these supercomputers, where you’re able to have a truly coherent state, are capable of processing a massive number of possible outcomes at the exact same time. Now, the really cool part is that we’re starting to scratch some of the stuff. Last November, IBM unveiled its very first 50 quantum bit or quantum computer. It actually lives in a lab with a giant white case, and it pumps this crazy, crazy, cool architectures cooling stuff that completely lets it be operating in a very, very cool temperature. Actually, liquid helium temperatures. I think it’s cooled down to about 4 Kelvin, which is down, and it cools it down to like 800 millikelvin, and a hundred, and, finally, 10 millikelvin.
Bill Kleyman: And just to give you an idea that’s ten-thousandths of a degree that’s above absolute zero. Then, that’s the coldest temperature that’s theoretically possible at which the motion of particles that constitute heat would be minimal. I think it’s to actually stopped moving. So, that’s the cool part about this. If you ever see, Greg, a supercomputer, it looks straight out of something that needs to be in Tony Stark’s house. I mean, these things are crazy. So, just kind of kind of summarize it up. There’s classical States, 1 and 0, on or off. And then, there’s the quantum state, where that 1 or 0, it could be either one at the exact same time.
Greg Turner: Yeah. So, it’s like really using more of all a multidimensional model for decision-making versus the standard linear or binary on/off.
Bill Kleyman: Absolutely. And you have to have that kind of revolutionary state. So, I kind of want to stay a little bit pie in the sky here and talk about why this is so cool. So, this podcast, everybody listening is extraordinarily relevant because just a couple of days ago, and if you’re Googling or searching for quantum supremacy or quantum computers, you’re probably in the right spot because guess what, Google, just a couple of days, finally announced that it has achieved its long-proposed goal of quantum supremacy. And it’s a huge, huge milestone in quantum computing because it begins this era in which a quantum computer can actually start to outperform classical supercomputers for certain types of applications.
Bill Kleyman: Now, I think that’s a really important point, Greg, before we go on because if you have a machine, a computer that can do one quantum bit, you really don’t have that much because you would need, at least, 50 quantum bits to have that idea and concept of quantum supremacy, where you could actually do some really cool simulations, compute architectures, and actually solve some of these world’s biggest mathematical or genomic sequence challenges out there. So, we’re just starting to scratch the surface of a machine that can actually do some of this stuff.
Greg Turner: That’s very neat. Where does quantum computing kind of fall within emerging technologies do you think?
Bill Kleyman: We’ll call it the hype cycle. How hyped up are we? We’re definitely on the upswing because there’s definitely still some challenges out there as far as what quantum computing is doing, but we’ll—let’s kind of settle back into reality a little bit later. I still kind of want to talk about the coolness of it because there’s practical use case around this – quantum chemistry, simulations, communication, using algorithms, and, obviously, things like even quantum machine learning where you can do things like – and this is great, great singularities – personalized medicine bioinformatics. You can create advanced differential equations for physics use cases. You can research biomolecules for biology, linear algebra code-breaking. But to really sort of understand the actual applications and use cases of it, there’s a little bit of hype right now, but there are some real-world use cases out there.
Bill Kleyman: So, machine learning, for example, we’re hearing about this all the time left and right, and a lot of things we see quantum computing impacting would be improved ML through faster structured prediction. So, these machines can learn and do deep learning both supervised, as well as unsupervised, and be able to make decisions at a far faster level. And that’s the same thing with AI. Faster calculations can prove perception comprehension and self-awareness. In the world of finance, for example, you could use a quantum computer to do things like faster and much more complex simulations for trading, trajectory optimization, market instability, price optimization.
Bill Kleyman: Me personally, Greg, and everybody listening, I think healthcare is really where it’s going to make the biggest differences in our lives. DNA, gene sequencing, radiotherapy treatment that optimizes the way we treat things like brain tumor detections. And you could perform some of these calculations, genomic sequences, in seconds to create very, very specific things, like drug algorithms for unique cancers, for example, in seconds instead of even hours or weeks. I mean, that’s where I think where going to see some life-altering examples of what quantum computing can do.
Greg Turner: That’s awesome. And it’s a pleasure, Bill, for our listeners for you to bring this to us and really give us this snapshot into the future because this is really cool stuff. Is this the type of things that companies today should be investing in? Or are there more practical use cases than others? And you’ve talked about health care as being one of them.
Bill Kleyman: So, it’s funny you’re mentioning this. Should we be investing? I’ve done several seminars with very large financial organizations that are very excited about some of these new and emerging technologies. It’s definitely something I think everyone should be researching. Back in 2013 or ’14, I wrote an article for a defense magazine – actually, it was the United States Government Defense Magazine – that talked about quantum cryptography. And we’d finally been able to achieve a quantum cryptographic algorithm, but it was really just point-to-point, Greg. So, if you’re taking a look at these two points, it was aligned. There was a laser that’s connected between these two points. And you were able to create a network-based quantum cryptography algorithm. The problem is it was only line of sight. If you start to introduce the complexities of the modern network, it’s pretty much going to break. And you really couldn’t introduce any corners into this thing as well.
Bill Kleyman: So, I want to say that we’re early on, still early on in this hype cycle, this growth of this technology, but you’ve got these articles. You’ve got Google that’s coming out with a new versions of a supercomputer that’s got like 53 quantum bits. That’s arguably saying that they’ve reached this dramatic speed up relative to classical computing and creating an architecture that actually supports quantum supremacy. Now, I’m sorry if I’m a little skeptical mainly because there’s a lot of things that are under the engine that we’re not going to have time to talk about the people need to understand. So, these machines are really, really, really sensitive. And this is why they need to be cooled to some millikelvin amount because a slight gust of air, any sort of change in the environment, will cause an error in the machine. And these errors are irreversible. And even with things like advanced error correction, you’re going to have to start the entire process over again.
Bill Kleyman: So, these machines, there’s definitely still some challenges, but what’s really fascinating and what’s really exciting is that we’re getting there. We’re legitimately starting to overcome this challenge known as quantum coherence or being able to maintain the quantum state. Our first problem was we didn’t have the hardware to do it. We were unable to cool this environment down to a specific point. But really, now, we are. So, having the gear to actually support this kind of architecture is becoming a reality.
Bill Kleyman: The next part about this is building a stable architecture that’s capable of doing multiple use cases and actually do some of this actual work. There are other interesting organizations out there. Obviously, IBM, Google. I would definitely take a look at D-waves quantum annealing computer capabilities, but there’s a lot of folks who are investing into this. And you shouldn’t be surprised, right? What takes us weeks, and days, and months, and years sometimes will literally take us seconds because in the quantum realm of computing, the computer already knows the answer when you’re asking it. I mean, that’s the crazy part.
Greg Turner: Right. And I think Microsoft actually said it best, it’s not a question of when quantum computing will be here, but what will we solve first with it?
Bill Kleyman: I agree with you 100%. Personally, I can’t wait to go into the science areas and in the healthcare field. I kind of want to make this point clear though for everybody listening. It’s not like you, Greg, and I are going to go out to Best Buy if it exists by then, and buy a quantum computer to put under our desks, so that you and I can play like, I don’t know, Super Mario Kart or whatever. That’s not the point of these things, these machines. They really are use case-specific to do extraordinarily complex mathematical computations and allow us to get to an ultimate answer like gene sequencing, for example, or doing like hedging strategies or price optimization, like I said earlier, at a completely unprecedented level.
Bill Kleyman: So, kind of like when supercomputers came out, some gamers got excited, but then realized that that’s not really something I’m going to be putting in my basement here. And it’s the same thing with quantum computers. They’re going to have very cool use cases and very specific ones as well. But it’s exciting to be in this phase where we’re starting to realize some of these impossibilities are actually becoming real in terms of the types of solutions and evolution that we’re seeing in the quantum computing realm.
Greg Turner: Yeah, I agree. And I think clearly, it’s going to be led by probably science and defense leading the way, much likely space exploration in the race to the moon back in the ’60s and ’70s. And so—but coming out of that will, ultimately, lead us to some commercially robust models and solutions. And I think some of the things that you pointed out in terms of healthcare, the sciences, biology, physics, robotics, and cybersecurity are really great practical use cases.
Bill Kleyman: No, absolutely. I mean, there’s a lot of real use cases that are out there. And a lot of times, these terminologies that you and I throw around, like digital transformation, and cloud computing. and, now, it’s quantum computing, can be very elusive. And it’s very hard to grasp where these kinds of technologies are actually going to make a difference. So, again, machine learning, AI, finance, healthcare, the enterprise, and even—I mean, even computer science, faster multi-dimensional search functions, for example, query optimization, advanced mathematics and simulations, I mean, these are all real things that you could be taking a look at that can change the way we do things on a daily basis. I mean, your capabilities of driving an autonomous vehicle will fundamentally change as soon as a quantum computer can help you make better and safer decisions when you’re on the road, as well as predictive and prescriptive decisions around what’s going to be happening around you. I mean, you’re really talking about the future of what we do every single day, and even some of these technologies that were leveraged already.
Greg Turner: I think, maybe for our listeners, if you could just maybe go through and enumerate some of the different applications and uses. I think we have like a list of things like machine learning, and finance, and healthcare.
Bill Kleyman: So, there’s a couple of different things that you can do. The biggest point of quantum computing is our ability to crunch mathematical algorithms and vast amounts of data, let’s say, almost instantaneously. And that’s going to revolve around AI, machine learning, traditional computing, mathematics, physics, chemistry, biology, the sciences, and obviously, a lot of the industries that revolve around what we do. In the world of finance, for example, we have an extraordinary amount of data that we leverage every single day.
Bill Kleyman: And it’s actually kind of funny because my brother works at a very, very large capital firm, and he talks to me every single day about market trends, hedge funding, creating algorithms to be able to understand how markets are going to form, deviate change based on different kinds of variables. A lot of times, programming this stuff into MATLAB, programming this stuff into AI engines, working with the cloud. It takes time to process some of these things. So. just using the financial element alone, doing things like searching, pattern matching, being able to do things like understanding deep levels of trading fluctuations, being able to do things at trajectories and trajectory optimization for different variables around a certain type of money, or product, or service, there’s a lot of different kinds of things that you can start to take a look at here.
Bill Kleyman: In terms of AI. I mean, being able to do things like fault diagnosis, better classifiers around things like self-awareness. And I swear, the next blog we’re going to be seeing, Bill and Greg talked about the next Terminator movie here. Yes, the idea is to create a singularity but, again, these are all controlled environments that allow these machines to think more effectively around what we program them to do. So, obviously, machine learning and AI, don’t get scared. I think these are going to be really, really important parts of our future. Again, self-driving cars, in my opinion, are absolutely going to be powered by quantum computers in the near future. But again, there’s real world applications.
Bill Kleyman: So, if you’re listening to this, and you’re in the healthcare space, or in the financial space, or you just deal—maybe you’re in a retail space, you have an extraordinary amount of data, and you’re trying to revolutionize the way you do things like AI and ML, quantum computing could absolutely be a way that you approach that. Obviously, pharmaceuticals should be absolutely paying attention to this because it’s going to change the way to deliver new products. And here’s the other big thing. Everybody, you’re going to see a personalization of technology because quantum computing is capable of doing that.
Bill Kleyman: Again, healthcare is a big part of that. If you have a cancer, hopefully you don’t, but if you do or a loved one, doing things like genomic sequencing as well as DNA gene sequencing, you’re capable of creating extraordinarily specific radiotherapy treatments and even drug treatments that can be created and sequenced, again, in seconds instead of hours or weeks that somebody might not necessarily have. So, it’s huge. I mean, in the healthcare world alone, chemical modeling as a possible use can speed up drug recovery while your ability to handle these extraordinary problems with machine learning are really going to be able to take care of some of these really thorny problems that we experience today.
Greg Turner: That’s amazing. And I think if anybody’s listening today to our show, they can really get a sense of the passion and enthusiasm you have for this topic. And I know that others that are researching this and that are developing these technologies have the same passion because it really is the holding the key to a lot of very complicated locks that you and I have talked about in the past. And so, I’m excited about it. I do think security is certainly a real concern. And you and I have had long conversations about it’s almost like an arms race. And that for every time you come up with the great security solution, there’s somebody else that’s figure out a way to hack into it.
Greg Turner: And one of the things that I’ve been thinking about a lot is with IoT, the internet of things, it’s really becoming ubiquitous and prevalent. And in fact, I had a client tell me that they’re buying trucks with over 500 IoT sensors onboard. Quantum computing might just be the ticket for keeping these things under control. The security concerns in IoT are almost infinite. Any thoughts on that, Bill?
Bill Kleyman: So, here’s the really, really scary question, Greg. And everybody listening, please don’t freak out. How long until the quantum computer next door is capable of breaking your encryption? Now, that’s a scary, scary kind of conversation here where that’s—believe it or not, when the very first quantum algorithm was developed, one of the things we were asking was, is this an actual encryption-breaking quantum computer? It’s kind of funny. There’s one algorithm that’s called Shor’s algorithm, and quantum can completely break RSA, an elliptic curve cryptography, as soon as the quantum computer has enough logical qubits to do that.
Bill Kleyman: The other is called Grover’s algorithm. These are quantum algorithms. It can drastically reduce AES encryption from 128 bits to 64 and can actually, then, be broken by your traditional PCs. And you can attempt to increase the bits on each algorithm to try and defend yourself, but once the quantum computer can break the lowest level of encryption, we’re only a couple of years away from them break these strongest versions of encryptions as well. Now, if you’re sweating, and you’re a chief security officer, don’t worry, there’s good news because it’s that these thousands of logical qubits are going to be needed to achieve what you can actually do to currently break some of these most common encryption algorithms that are being used.
Bill Kleyman: There is a really interesting study done by a Canadian company called Cryptera that they said they believed that you would need close to 3000 – 3000 quantum bits to break an AES 128 encryption and almost 6700 logical qubits to break an AES 256 encryption. And you can only imagine how many you’d need for even stronger encryption beyond that. You need to have more than 4000 logical bits to break in RSA 2048 encryption as well. So, that’s quite a lot. And don’t get too optimistic here because the assumption is also around things like error correcting, error rates. I mean, we have to make sure that these are all working perfectly in unison. So, can they break traditional encryption? Yes. But will they do it tomorrow? I don’t think so. And I think by the time that these machines are capable of breaking maybe some of these more AES and RSA-based algorithmic encryptions, we’re probably going to have some advancements in encryption in general.
Greg Turner: Excellent, excellent. I wonder if by combining machine learning and predictive analytics with quantum computing, science could improve the theoretical guarantees. Any thoughts on that, Bill?
Bill Kleyman: Theoretical guarantees, right that. So, you’re talking about outcomes, your confidence in a certain type of outcome. So, there’s a couple of them. There’s an example called the Boltzmann machine, the Quantum Boltzmann Machine, which allow you to create a machine learning through faster structure prediction. And there’s two types of learning that you can create based on this – semi-supervised and unsupervised learning and deep learning. So, these machines will literally learn on their own and create better structure predictions.
Bill Kleyman: And one example that I use here are self-driving cars. So, the question back at you would be like, wouldn’t you want an architecture that can learn and give you better predictions, and better on outcomes, and understandings, especially when you’re in a car, and your hands are off? You’re letting Elon Musk drive for you, for example? So, the ultimate answer here is yes. Through machine learning and the integration of quantum computing, you are going to get up to a point where you have an extraordinarily greater amount of confidence around what these things are doing because, simply put, you get the answers faster, and you could leverage that data much more effectively. So, the future is absolutely going to revolve around machines that can make better and, obviously, much more accurate decisions faster.
Greg Turner: Bill, this has been absolutely amazing. And I really don’t know how to end our podcast. We could probably go on, and on, and on. And let me just give you a chance for any last words.
Bill Kleyman: I’d love that. And what I really want to do here, Greg, as we sort of wind this down a little bit, as I implore everybody to do your own research here. We see these articles that are coming out. Google achieving Quantum Supremacy. We’re seeing greater levels of quantum coherence being achieved as well. But I want to bring it down to reality a little bit. Quantum computing and supremacy, still elusive concept. Not everybody is getting it. You need all of these 50 qubits to work perfectly to actually do something for you.
Bill Kleyman: But reality is that quantum computing is beset by errors that need to be corrected. And it’s also devilishly difficult to maintain these quantum bits for any length of time because they tend to, like we talked about earlier, decohere, which means that it loses that delicate quantum nature. So, like a smoke ring breaks up at the slightest air current, that’s what happens with quantum bits if something bad happens or if there’s any sort of deviation or fluctuation in the environment.
Bill Kleyman: The other challenges that—it’s useful in a good, and right, and structured environment. You can’t just throw any tasks at a quantum computer. In fact, even currently, many calculations are still slower on a quantum computer than on a classical machine, but this is something that’s going to be changing, and something that’s going to be evolving here very, very soon. Remember, these machines, and when you look them up, they’re very delicate. Engineers have to work to isolate that quantum chip from any noise at all. This includes electrical, magnetic, thermal, and even in the temperature has to be extremely well controlled. And soon as we get to a point where we get better error correction, because that’s still somewhat lacking, we are able to do some amazing things as far as deep neural networks, complex mathematical systems that learn discrete tasks, such as image recognition or machine translation, by analyzing this vast amount of data
Bill Kleyman: So, we’re getting there, but it’s a lack of theoretical guarantees right now. And we’re getting there. We’re certainly going to be getting there very, very soon. I think it’s an extraordinary time to be working with quantum computing, but know the limits of it, Know where it’s probably applicable. And believe it or not, over the next few years, you might be using a service, or an application, or even be driven in a car where the back end – guess what – is powered by quantum computer. So, it’s really exciting times.
Greg Turner: This has been amazing. Thank you, Bill. And thank you for listening. I hope you found this podcast helpful and, also, a real snapshot of the future. For any questions, comments, or feedback, please feel free to send me an email at email@example.com. For more about us, visit mtm.com. At the Disruptive Enterprise, this is Greg Turner. Thank you.
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