 Live from Las Vegas, it's theCUBE! Covering AWS re-invent 2019. Brought to you by Amazon Web Services and Intel, along with its ecosystem partners. Okay, welcome back everyone. It's theCUBE's live coverage here in Las Vegas for Amazon Web Services. AWS re-invent 2019. It's theCUBE's seventh year covering re-invent. Eight years they've been running this event. It gets bigger every year. It's been a great way to ride on. I'm John Furrier with my co-host, Dave Vellante. We've been riding this wave day for years. It's so exciting, it's bigger and more exciting. Okay, seven. This year more than ever. So much stuff is happening. It's been really exciting. I think there's a sea change happening in terms of another wave coming. Quantum computing, big news here amongst other great tech. Our next guest is Bill Vaz. VP of Technology, Storage Automation Management, part of the Quantum announcement that went out. Bill, great to see you. Yeah, welcome to see you. Great to see you again. Thanks for having me on board. So, we love Quantum. We talk about it all the time. My son loves it. Everyone loves it. It's futuristic. It's going to crack everything. It's the fastest thing in the world. Quantum supremacy. Andy referenced it in my one-on-one with him around Quantum being important for Amazon. You guys launched it. Take us through the timing. Why? Why now? Okay, so the Bracket Service, which is based on Quantum notation made by Dirac, right? So we thought that was a good name for it. Provides to you the ability to do development in Quantum algorithms using gate-based programming that's available. And then do simulation on classical computers, which is what we call our digital computers today now. These are classical computers all of a sudden, right? And then actually do execution of your algorithms on today three different Quantum computers. One that's annealing in the two gate-based machines. And that gives you the ability to test them in parallel and separate from each other. In fact, last week I was working with a team and we had two machines, an ion-trap machine and an electromagnetic tunneling machine solving the same problem and passing variables back and forth from each other. And you can see the CloudWatch metrics coming out and the data was going into S3 buckets on the output and we do it all in a Jupyter notebook. So it was pretty amazing to see all of that running together. I think it's probably the first time two different machines and two different technologies have worked together on a Cloud computer fully integrated with everything else. So it was pretty exciting. So Quantum Supremacy has been a word kicked around a lot of hand-waving IBM, Google, depending on who you talk to, there's different versions, but at the end of the day, Quantum isn't a leap in computing. Yes, it can be. It can be. It's still early days, it would be day zero. Yeah, well I think you think of a, we're about where computers were with tubes, if you remember, if you go back that far, right? It's about, that's not where we are right now. Where you got to kind of jiggle the tubes sometimes to get the running. A bug gets in there. Yeah, a bug can get in there and those kind of things. You flip them off with a punch guard. Yeah, so for example, a number of the machines, they run for four hours and then they come down for a half hour for calibration and then they run for another four hours. So we're still sort of at that early stage, but you can do useful work on them and more mature systems like, for example, D-Way, which is a kneeler is a little different than gate-based machines, it's really quite mature, right? And so I think as you go back and forth between these different machines, the gate-based machines and the kneelers, you can really get a sense for what's capable today and with Bracket and that's what we want to do is get people to actually be able to try them out. Now, quantum supremacy is a fancy word for we did something you can't do on a classical computer, right? That's on a quantum computer for the first time. And quantum computers have the potential to exceed the processing power, especially on things like factoring and other things like that, or Hamiltonian simulations for molecules and those kinds of things, because that's a quantum computer operates the way a molecule operates, right? In a lot of ways, using quantum mechanics and things like that. And so it's a fancy term for that. We don't really focus on that at Amazon, we focus on solving customers' problems and the problem we're solving with Bracket is to get them to learn it as it's evolving and be ready for it and continue to develop the environment and then also offer a lot of choice. Amazon's always been big on choice. I mean, if you look at our processing portfolio, we have AMD, Intel X86, great partners, great products from them. We have NVIDIA, great partner, great products from them. But we also have our Graviton 1 and Graviton 2 and our new GPU type chip. And those are great products too. We've been doing a lot on those as well. And the customer should have that choice and with quantum computers are trying to do the same thing. We will have, you know, annealers, we will have ion trap machines, we will have electromagnetic machines and others available on Bracket. Can I ask you a question on quantum if you go back a little bit? So you mentioned vacuum tubes, it's kind of funny. But the challenge there was, whatever it was, cooling and reliability system downtime. What are the technical challenges with regard to quantum in terms of making it stable? Yeah, so some of it is, you know, on classical computers, as we call them, they have error correction code built in. So you have, whether you know it or not, there's alpha particles that are flipping bits on your memory all the time, right? And if you don't have ECC, you'd get crashes constantly on your machine. And so we built in ECC. So we're trying to build the quantum computers with the proper error correction, right? To handle these things, because nothing runs perfectly. You just think it's perfect because we're doing all the error correction under the covers, right? And so that needs to evolve on quantum computers. The ability to reproduce them in volume from an engineering perspective, you know, again, standard lithography has a yield rate, right? I mean, sometimes the yield is 40%, sometimes it's 20%, sometimes it's a really good fab and it's 80%, right? And so that you have a yield rate as well. So being able to do that, these machines also generally operate in a cryogenic world, that's a little bit more complicated, right? And they're also heavily affected by electromagnetic radiation and things like that. So you have to sort of ferrite a cage them in some cases and other things like that. So there's a lot that goes on there. So it's managing a physical environment like cryogenics is challenging to do well. Having the fabrication to reproduce it in a new way is hard. The physics is actually, I shudder to say well understood. I would say the way the physics reworks is well understood, how it works is not, right? No one really knows how entanglement works. They just know what it does and that's understood very well, right? And so a lot of it is now why we're excited about it. It's an engineering problem to solve and we're pretty good at engineering. So talk about the practicality. Annie Jassy's on the record with me quoted, said, quantum is very important to Amazon. Yes, it is. You agree with that? He also said, it's years out, you said that. He said, but we want to make it practical for customers. We do. What is the practical thing? Is it just kicking the tires and some of the things you mentioned? What's the core goal? So in my opinion, we're at a point in the evolution of these quantum machines and certainly what the work we're doing with Caltech and others, that the number of available qubits are starting to increase at an astronomical rate, you know, in the Moore's law kind of a rate, right? Whether it's, no matter which machine you're looking at out there, and there's about 200 different companies building quantum computers now. And so, and they're all good technology. They've all got challenges as well as reproducibility and those kinds of things. And so now's a good time to start learning how to do this gate-based programming, knowing that it's coming because quantum computers, they won't replace a classical computer. So don't think that because there is no quantum RAM. You can't run 200 petabytes of data through a quantum computer today and those kind of things. What it can do is factoring very well or it can do probability equations very well. It'll have effects on Monte Carlo simulations. It'll have effects specifically in material sciences where you can simulate molecules for the first time that you just can't do on classical computers. And when I say you can't do on classical computers, my quantum team always corrects me. They're like, well, no one has proven that there's an algorithm you can run on a classical computer that will do that. Yeah, right. So there may be times when you say, okay, I did this on a quantum computer and you could only do it on a quantum computer, but then someone's very smart and efficient says, oh, I figured out how to do it on a regular computer. You don't need a quantum computer for that. And that's constantly evolving as well in parallel, right? And so, and that's what's that argument between IBM and Google on quantum supremacy is that, you know, and that's an unfortunate distraction in my opinion. What Google did was quite impressive and if you're in the quantum world, you should be very, very happy with what they did. They had a very low error rate with a large number of qubits and that's a big deal. Well, I just want to ask you, I mean, this industry is an arms race, but with something like quantum, where you've got 200 companies actually investing in it so early days, is, you know, collaboration maybe a model here? I mean, what do you think that you mentioned Caltech? It certainly is for us because we, like I said, we're going to have multiple quantum computers available just like we collaborate with Intel and AMD and all of our other partners, right? In that space as well. That's the nice thing about being a cloud service provider is we can give customers choice and we can have our own innovation plus their innovations available to customers, right? Innovation doesn't just happen in one place, right? We got a lot of smart people to Amazon, we don't invent everything, right? So I got to ask you, obviously, we could take the cube quantum and call it qubits, not to be confused with the cube video highlights. You know, joking aside, classical computers, will there be a classical cloud? Because this is kind of a futuristic- Or you mean a quantum cloud. Quantum cloud, well, then they get the classic cloud, you get the quantum cloud. Well, no, they'll be together. So think of a, I think a quantum computer will be used like, we used to use a math coprocessor, right, if you like, or FPGAs are used today, right? So you'll go along and you'll have your problem and I'll give you a practical example. So let's say you had a machine with 125 qubits, okay? You could start doing some really nice optimization algorithms on that. So imagine there's this company that ships stuff around a lot, I wonder who that could be, and they need to optimize continuously their delivery for a truck, right? And that changes all the time. Well, that algorithm, if you're doing hundreds of deliveries in a truck, it's very complicated. That traveling salesman algorithm is an MP hard problem when you do it, right? And so what would be the fastest best path? But you got to take into account weather and traffic, so that's changing. So you might have a classical computer do those algorithms overnight for all the delivery trucks and then send them out to the trucks next morning they're driving around. But it takes a lot of computing power to do that, right? Well, a quantum computer can do that kind of a problemistic or deterministic equation like that, not deterministic, a best fit algorithm like that much faster. And so you could have it every second of providing that. So your classical computer's sending out the manifest, interacting with the person, it's got the website on it, and then it gets to the part where here's the problem to calculate, it does, we call it a shot when you're on a quantum computer, it runs it in a few seconds that would take an hour or more and it comes right back with the result and then it continues with its thing, passes that to the driver, another update occurs and it's just going on all the time. So those kind of things are very practical and coming. I got to ask for the younger generations, my son's super interested, I mentioned before you came on. Quantum attracts the younger, smart kids coming into the workforce, engineering, talent. What's the best path for someone who has either advanced degree or no degree to get involved in quantum? Is there a certain advice you'd give someone? So the reality is, I mean, obviously, having taken quantum mechanics in school and understanding the physics behind it to a certain extent, as much as you can understand the physics behind it, right? I think the other area is there are physics, there are programs at universities focused on quantum computing, there's a bunch of them, so they can go into that direction. But even just, you know, regular computer science, a regular mechanical and electrical engineering are all needed, you know, mechanical around the cooling, all that other stuff, electrical, these are electrically based machines, just like a classical computer is. And, you know, being able to code at low level is another area that's tremendously valuable right now. You mentioned best fit is coming, that use case. I mean, can you give us a sense of a time frame? And people will say, oh, 10, 15, 20 years, but you're talking much sooner. I think it's sooner than that, I do. And it's hard for me to predict exactly when we'll have it. And you could already do some of the annealing machines like D-Wave, some of the best fit today, right? So it's a matter of, you know, people want to use a quantum computer because they need to do something fast. They don't care how much it costs, they need to do something fast. Or it's too expensive to do it on a classical computer, or you just can't do it at all on a classical computer. Today, there isn't much of that last one, can't do it at all, but that's coming. As you get to around 50, 52 qubits, it's very hard to simulate that on a classical computer. You're starting to reach the edge of what you can practically do on a classical computer. At 125 qubits, you probably are at a point where you can't just simulate it anymore. But you're talking years, not decades, for this year's case. Yeah, I think you're definitely talking years. And you know, it's interesting, if you'd asked me two years ago how long it would take, I would have said decades. So that's how fast things are advancing right now. And I think that- It's getting faster and faster. Yeah, yeah, but the ability to fabricate the understanding, you know, there's some, you know, there's a number of architectures that are very well proven. It's just a matter of getting the error rates down, stability in place, the repeatable manufacturing in place. There's a lot of engineering problems. And engineering problems are good. We know how to do engineering problems, right? And we actually understand the physics, or at least we understand how the physics works. I won't say, I claim that, you know, what is it, spooky action at a distance is what Einstein said for entanglement, right? And that's a core piece of this, right? And so those are challenges, right? And that's part of the mystery of the quantum computer I got. So you're having fun? I am having fun. I mean, it's pretty intoxicating, technical problems. It's fun. It is, it is a lot of fun. Of course, the whole portfolio that I run at AWS is just really a fun portfolio between robotics and autonomous systems and IoT and the advanced storage stuff that we do and all the edge computing and all the monitor management systems and all the real-time streaming. So like Kinesis video, that's the back end for the Amazon Go stores and working with all of that. It's a lot of fun. It really is. Well, Bill, we need an hour to get into that. So we have to come up and see you. Do a special story. We'd love to come up and dig in and get a special feature program with you at some point. I'm happy to do that. Happy to do that. We've got some robotics, some IoT, autonomous systems. You can see all of it around here. We've got it, got it running around here. What a portfolio. Congratulations. All right, thank you so much. Great news on the Quantum. Quantum is here. Quantum cloud is happening. Of course, the cube is going quantum. We've got a lot of cube bits here, a lot of cube highlights. Go to siliconangle.com. We've got all the data here. We're sharing it with you. I'm John Furrier with Dave Vellante. Talk to Quantum. Want to give a shout out to Amazon Web Services and Intel for setting up the stage for us thanks to our sponsors. We wouldn't be able to make this happen if it wasn't for them. Thank you very much and thanks for watching. We'll be back with more coverage after this short break.