>> From the SiliconANGLE media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Vellante. >> Hello, everyone, and welcome to this week's episode of theCUBE Insights, powered by ETR. In this Breaking Analysis, I want to do a quasi post-mortem on AWS re:Invent, and put the company's prospects into context using some ETR spending data. First I want to try to summarize some of the high-level things that we heard at the event. I won't go into all the announcements in any kind of great detail, there's a lot that's been written out there on what was announced, but I will touch on a few of the items that I felt were noteworthy and try to give you some of the main themes. I then want to dig into some of the spending data and share with you what's happening from a buyer's perspective in the context of budgets, and we'll specifically focus on AWS's business lines. And then I'm going to bring my colleague Stu Miniman into the conversation, and we're going to talk about AWS's hybrid strategy in some detail, and then we're going to wrap. So, the first thing that I want to do is give you a brief snapshot of the re:Invent takeaways, and I'll try to give you some commentary that you might not have heard coming out of the show. So, to summarize re:Invent, AWS is not being on rinsing and repeating, they have this culture of raising the bar, but one thing that doesn't change is this shock and awe that they do of announcements, it comes out each year, and it's obvious. It's always a big theme, and this year Andy Jassy really wanted to underscore the company's feature and functional lead relative to some of the other cloud providers. Now the overarching theme that Jassy brought home in his keynote this year is that the cloud is enabling transformation. Not just teeny, incremental improvement, he's talking about transformation that has to start at the very top of the organization, so it's somewhat a challenge and an appeal to enterprises, generally versus what is often a message to startups at re:Invent. And he was specifically talking to the c-suite here. Jassy didn't say this, but let me paraphrase something that John Furrier said in his analysis on theCUBE. He said if you're not born in the cloud, you basically better find the religion and get reborn, or you're going to be out of business. Now, one of the other big trends that we saw this year at re:Invent, and it's starting to come into focus, is that AWS is increasingly leveraging its acquisition of Annapurna with these new chip sets that give it higher performance and better cost structures and utilization than it can with merchant silicon, and specifically Intel. And here's what I'll say about that. AWS is one of the largest, if not the largest customer of Intel's in the world. But here's the thing, Intel wants a level playing field. We've seen this over the years, where it's in Intel's best interest to have that level playing field as much as possible, in its customer base. You saw it in PCs, in servers, and now you're seeing it in cloud. The more balanced the customer base is, the better it is for Intel because no one customer can exert undue influence and control over Intel. Intel's a consummate arms dealer, and so from AWS's perspective it makes sense to add capabilities and innovate, and vertically integrate in a way that can drive proprietary advantage that they can't necessarily get from Intel, and drive down costs. So that's kind of what's happening here. The other big thing we saw is latency, what Pat Gelsinger calls the law of physics. Well a few years ago, AWS, they wouldn't even acknowledge on-prem workloads, and Stu and I are going to talk about that, but clearly sees hybrid as an opportunity now. I'm going to talk more on detail and drill into this with Stu, but a big theme of the event was moving Outposts closer to on-prem workloads, that aren't going to be moving into the cloud anytime soon. And then also the edge, as well as, for instance, Amazon's Wavelength announcement that puts Outposts into 5G networks at major carriers. Now another takeaway is that AWS is unequivocal about the right tool for the right job, and you see this really prominently in database, where I've counted at least 10 purpose-built databases in the portfolio. AWS took some really indirect shots at Oracle, maybe even direct shots at Oracle, which, Oracle treats Oracle Database as a hammer, and every opportunity as a nail, antithetical to AWS's philosophy. Now there were a ton of announcements around AI and specifically the SageMaker IDE, specifically Studio, SageMaker Studio, which stood out as a way to simplify machine intelligence. Now this approach addresses the skillset problem. What I mean by that is, the lack of data scientists to leverage AI. But one of the things that we're kind of watching here is, it's going to be interesting to see if it exacerbates the AI black box issue. Making the logic behind the machines' outcomes less transparent. Now, all of this builds up to what we've been calling next-gen cloud, and we're entering a new era that goes well beyond infrastructure as a service, and lift and shift workloads. And it really ties back to Jassy's theme of transformation, where analytics approaches new computing models, like serverless, which are fundamental now, as is security, and a topic that we've addressed in detail in prior Breaking Analysis segments. AWS even made an announcement around quantum computing as a service, they call it Braket. So those are some of the things that we were watching. All right, now let's pivot and look at some of the data. Here's a reminder of the macro financials for AWS, we get some decent data around AWS financials, and this chart, I've showed before, but it's AWS's absolute revenue and quarterly revenue year on year with the growth rates. It's very large and it's growing, that's the bottom line, but growth is slowing to 35% last quarter as you can see. But to iterate, or reiterate, we're looking at a roughly 36 billion dollar company, growing at 35% a year, and you don't see that often. And so, this market, it still has a long way to go. Now let's look at some of the ETR tactical data on spending. Now remember, spending attentions according to ETR are reverting to pre-2018 levels, and are beginning to show signs of moderation. This chart shows spending momentum based on what ETR calls net score, and that represents the net percentage of customers that are spending more on a particular platform. Now, here's what's really interesting about this chart. It show the net scores for AWS across a number of the company's markets, comparing the gray, which is October '18 survey, with the blue, July '19, and the yellow, October '19. And you can see that workspaces, machine learning and AI, cloud overall, analytic databases, they're all either up or holding the same levels as a year ago, so you see AWS is bucking the trend, and even though spending on containers appears to be a little less than last year, it's holding firm from the July survey, so my point is that AWS is really bucking that trend from the overall market, and is continuing to do very very well. Now this next slide takes the same segments, and looks at what ETR refers to as market share, which is a measure of pervasiveness in the survey. So as you can see, AWS is gaining in virtually all of its segments. So even though spending overall is softening, AWS in the marketplace, AWS is doing a much better job than its peers on balance. Now, the other thing I want to address is this notion of repatriation. I get this a lot, as I'm sure do other analysts. People say to me, "Dave, you should really look into this. "We hear from a lot of customers "that they moved to the cloud, "now they're moving workloads back on-prem "because the cloud is so expensive." Okay, so they say "You should look into this." So this next chart really does look into this. What the chart shows is across those same offerings from AWS, so the same services, the percent of customers that are replacing AWS, so I'm using this as a proxy for repatriation. Look at the numbers, they're low single digits. You see traditional enterprise vendors' overall business growing in the low single digits, or shrinking. AWS's defections are in the low single digits, so, okay, now look at this next chart. What about adoptions, if the cloud is slowing down, you'd expect a slowdown in new adoptions. What this data shows is the percent of customers that are responding, that they're adding AWS in these segments, so there's a new platform. So look, across the board, you're seeing increases of most of AWS's market segments. Notably, in respondents citing AWS overall at the very rightmost bars, you are admittedly seeing some moderation relative to last year. So that's a bit of a concern and clearly something to watch, but as I showed you earlier, AWS overall, that same category, is holding firm, because existing customers are spending more. All right, so that's the data portion of the conversation, hopefully we put that repatriation stuff to bed, and I now want to bring in Stu Miniman to the conversation, and we're going to talk more about multicloud, hybrid, on-prem, we'll talk about Outposts specifically, so Stu, welcome, thank you very much for coming on. >> Thanks Dave, glad to be here with you. >> All right, so let's talk about, let's start with multicloud, and dig into the role of Kubernetes a little bit, let me sort of comment on how I think AWS looks at multicloud. I think they look at multicloud as using multiple public clouds, and they look at on-prem as hybrid. Your thoughts on AWS's perspective on multicloud, and what's going on in the market. >> Yeah, and first of all, Dave, I'll step back for a second, you talked about how Amazon has for years had shots against Oracle. The one that Amazon actually was taking some shots at this year was Microsoft, so, not only did they talk about Oracle, they talked about customers looking to flee their SQL customers, and I lead into that because when you talk about hybrid cloud, Dave, if you talked to any analyst over the last three, four years and you say "Okay, what vendor is best position in hybrid, "which cloud provider has the "best solution for hybrid cloud?" Microsoft is the one that we'd say, because their strong domain in the enterprise, of course with Windows, the move to Office 365, the clear number two player in Azure, and they've had Azure Stack for a number of years, and they had Azure Pack before that, they'd had a number of offerings, they just announced this year Azure Arc, so three, we've had at least three generations of hybrid multicloud solutions from Microsoft, Amazon has a different positioning. As we've talked about for years, Dave, not only doesn't Amazon like to use the words hybrid or multicloud, for the most part, but they do have a different viewpoint. So the partnership with VMware expanded what they're doing on hybrid, and while Andy Jassy, he at least acknowledges that multicloud is a thing, when he sat down with John Furrier ahead of the show, he said "Well, there might be reasons why customers "either there's a group inside "that has a service that they want, "that they might want to do a secondary cloud, "or if I'm concerned that I might fall out of love "with this primary supplier I have, "I might need a second one." Andy said in not so, just exactly, said "Look, we understand multicloud is a thing." Now, architecturally, Amazon's positioning on this is that you should use Amazon, and they should be the center of what you're doing. You talked a lot about Outposts, Outposts, critical to what Amazon is doing in this environment. >> And we're going to talk about that, but you're right, Amazon doesn't like to talk about multicloud as a term, however, and by the way, they say that multicloud is more expensive, less secure, more complicated, more costly, and probably true, but you're right, they are acknowledging at least, and I would predict just as hybrid, which we want to talk about right now, they'll be talking about, they'll be participating in some way, shape, or form, but before we go to multicloud, or hybrid, what about Kubernetes? >> So, right, first of all, we've been at the KubeCon show for years, we've watching Kubernetes since the early days. Kubernetes is not a magic layer, it does not automatically say "Hey, I've got my application, I can move it willy-nilly." Data gravity's really important, how I architect my microservices solution absolutely is hugely important. When I talk to my friends in the app dev world, Dave, hybrid is the way they are building things a lot, if I took some big monolithic application, and I start pulling it apart, if I have that data warehouse or data store in my data center, I can't just migrate that to the cloud, David Floyer for years has been talking about the cost of migration, so microservice architecture's the way most customers are building, a hybrid environment often is there. Multicloud, we're not doing cloud bursting, we're not just saying "Oh hey, I woke up today, "and cloud A is cheaper than cloud B, "let me move my workload." Absolutely, I had a great conversation with a good Amazon customer that said two years ago, when they deployed Kubernetes, they did it on Azure. You want to know why, the Azure solution was more mature and they were doing Azure, they were doing things there, but as Amazon fully embraced Kubernetes, not just sitting on top of their solution, but launched the service, which is EKS, they looked at it, and they took an application, and they migrated it from Azure to Amazon. Now, migrating it, there's the underlying services and everybody does things a little bit different. If you look at some of the tooling out there, great one to look at is HashiCorp has some great tooling that can span across multiple clouds, but if you look at how they deploy, to Azure, to Google, to AWS, it's different, so you got to have different code, there's different skillsets, it's not a utility and just generic compute and storage and networking underneath, you need to have specific skills there, so Kubernetes, absolutely when I've been talking to users for the last few years and saying "Why are you using Kubernetes?" The answer is "I need that eject lever, "so that if I want to leave AWS with an application, "I can do that, and it's not press a button and it's easy, "that easy, but I know that I can move that, "'cause underneath the pods, and the containers, "and all those pieces, the core building blocks "are the same, I will have to do some reconfiguration," as we know with the migration, usually I can get 80 to 90 percent of the way there, and then I need to make the last minute-- >> So it's a viable hedge on your AWS strategy, okay. >> Absolutely, and I've talked to lots of customers, Amazon shows that most cloud Kubernetes solutions out there are running on Amazon, and when I go talk to customers, absolutely, a lot of the customers that are doing Kubernetes in the public cloud are doing that on Amazon, and one of the main reasons they're using it is in case they do want to, as a hedge against being all-in on Amazon. >> All right, let's talk about Outposts, specifically as part of Amazon's hybrid strategy, and now their edge strategy as well. >> Right, so Azure Stack, I mentioned earlier from Microsoft has been out there for a few years. It has not been doing phenomenally well, when I was at Microsoft Ignite this year, I heard basically certain government agencies and service providers are using it and basically acting, delivering Azure as a service, but, Azure Stack is basically an availability zone in my data center, and Amazon looked at this and says "That's not how we're going to build this." Outposts is an extension of your local region, so, while people look at the box and they say, I took a picture of the box and Shu was like, "Hey, whose server and what networking card, "and the chipset and everything," I said "Hold on a second. "You might look at that box, "and you might be able to open the door, "but Amazon is going to deploy that, "they're going to manage that, "really you should put a curtain in front of it "and say pay no attention to what's behind here, "because this is Amazon gear, it's an Amazon "as a service in your data center, "and there are only a few handful of services "that are going to be there at first." If I want to even use S3, day one, the Amazon native services, you're going to just use S3 in your local region. Well, what if I need special latency? Well, Amazon's going to look at that, and see what's available, so, it is Amazon hardware, the Amazon software, the Amazon control plane, reaching into that data center, and very scalable, it's, Amazon says over time it should be able to go to thousands of racks if you need, so absolutely that cloud experience closer to my environment, but where I need certain applications, certain latency, certain pieces of data that I need to store there. >> And we've seen Amazon dip its toe into the hybrid on-prem market with Snowball and Greengrass and stuff like that before, but this is a much bigger commitment, one might even say capitulation, to hybrid. >> Well, right, and the reason why I even say, this is hybrid, but it's all Amazon, it is not "Take my private cloud and my public cloud "and tie 'em together," it's not, "I've taken cloud to customer" or IBM solution, where they're saying "I'm going to put a rack here "and a rack there, and it's all going to work the same." It is the same hardware and software, but it is not all of the pieces-- >> VMware and Outposts is hybrid. >> Really interesting, Dave, as the native AWS solution is announced first here in 2019, and the VMware solution on Outposts isn't going to be available until 2020. Draw what you will, it's been a strong partnership, there are exabytes of data in the VMware cloud on AWS now, but yeah, it's a little bit of a-- >> Quid pro quo, I think is what you call that. >> Well I'd say Amazon is definitely, "We're going to encroach a little bit on your business, "and we're going to woke you into our environment, too." >> Okay, let's talk about the edge, and Outposts at the edge, they announced Wavelength, which is essentially taking Outposts and putting it into 5G networks at carriers. >> Yeah, so Outposts is this building block, and what Amazon did is they said, "This is pretty cool, "we actually have our environment "and we can do other things with it." So sometimes they're just taking, pretty much that same block, and using it for another service, so one that you didn't mention was AWS Local Zones. So it is not a whole new availability zone, but it is basically extending the cloud, multi-tenant, the first one is done for the TME market in Los Angeles, and you expect, how does Amazon get lower latency and get closer, and get specialized services, local zones are how they're going to do this. The Wavelength solution is something they built specifically for the telco environment. I actually got to sit down with Verizon, this was at least an 18 month integration, anybody that's worked in the telco space knows that it's usually not standard gear, there's NEBB certification, there's all these things, it's often even DC power, so, it is leveraging Outposts, but it is not them rolling the same thing into Verizon that they did in their environments. Similar how they're going to manage it, but as you said, it's going to push to the telco edge and in a partnership with Verizon, Vodafone, SK, Telecom, and some others that will be rolling out across the globe, they are going to have that 5G offering and this little bit, I actually buy it from Amazon, but you still buy the 5G from your local carrier. It's going to roll out in Chicago first, and enabling all of those edge applications. >> Well what I like about the Amazon strategy at the edge is, and I've said this before, on a number of occasions on theCUBE Breaking Analysis, they're taking programmable infrastructure to the edge, the edge will be won by developers in my view, and Amazon obviously has got great developer traction, I don't see that same developer traction at HPE, even Dell EMC proper, even within VMware, and now they've got Pivotal, they've got an opportunity there, but they've really got a long way to go in terms of appealing to developers, whereas Amazon I think is there, obviously, today. >> Yeah, absolutely true, Dave. When we first started going to the show seven years ago, it was very much the hoodie crowd, and all of those cloud-native, now, as you said, it's those companies that are trying to become born again in the cloud, and do these environments, because I had a great conversation with Andy Jassy on air, Dave, and I said "Do we just shrink wrap solutions "and make it easy for the enterprise to deploy, "or are we doing the enterprise a disservice?" Because if you are truly going to thrive and survive in the cloud-native era, you've got to go through a little bit of pain, you need to have more developers. I've seen lots of stats about how fast people are hiring developers and I need to, it's really a reversal of that old outsourcing trend, I really need IT and the business working together, being agile, and being able to respond and leverage data. >> It's that hyperscaler mentality that Jassy has, "We got engineers, we'll spend time "on creating a better mousetrap, on lowering costs," whereas the enterprise, they don't have necessarily as many resources or as many engineers running around, they'll spend money to save time, so your point about solutions I think is right on. We'll see, I mean look, never say never with Amazon. We've seen it, certainly with on-prem, hybrid, whatever you want to call it, and I think you'll see the same with multicloud, and so we watch. >> Yeah, Dave, the analogy I gave in the final wrap is "Finding the right cloud is like Goldilocks "finding the perfect solution." There's one solution out there, I think it's a little too hot, and you're probably not smart enough to use it just yet. There's one solution that, yeah, absolutely, you can use all of your credits to leverage it, and will meet you where you are and it's great, and then you've got Amazon trying to fit everything in between, and they feel that they are just right no matter where you are on that spectrum, and that's why you get 36 billion growing at 35%, not something I've seen in the software space. >> All right, Stu, thank you for your thoughts on re:Invent, and thank you for watching this episode of theCUBE Insights, powered by ETR, this is Dave Vellante for Stu Miniman, we'll see you next time. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2019. Brought to you by Amazon Web Services and Intel. Along with it's ecosystem partners. >> Okay, welcome back everyone. It's theCUBE's live coverage here in Las Vegas for Amazon Web Series today, 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 wave to ride on. I'm John Furrier, my cohost, Dave Vellante. We've been riding this wave, Dave, for years. It's so exciting, it gets bigger and more exciting. >> Lucky 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 Vass, VP of Technology, Storage Automation Management, part of the quantum announcement that went out. Bill, good to see you. >> Yeah, well, good 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 going to be the fastest thing in the world. Quantum supremacy. Andy referenced it in my one-on-one with him around quantum being important for Amazon. >> Yes, it is, it is. >> You guys launched it. Take us through the timing. Why, why now? >> Okay, so the Braket service, which is based on quantum notation made by Dirac, right? So we thought that was a good name for it. It provides for 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. (men chuckling) >> Yeah, it's a classic. >> These are classic computers all of a sudden right? And then, actually do execution of your algorithms on, today, three different quantum computers, one that's annealing and two-bit 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 the 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, you could see the cloud watch metrics coming out, and the data was going to an S3 bucket on the output. And we do it all in a Jupiter notebook. So it was pretty amazing to see all that running together. I think it's probably the first time two different machines with two different technologies had 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 is a leap in computing. >> Bill: Yes, it can be. >> It can be. It's still early days, it would be day zero. >> Yeah, well I think if you think of, we're about where computers were with tubes if you remember, if you go back that far, right, right? That's about where we are right now, where you got to kind of jiggle the tubes sometimes to get them running. >> A bug gets in there. Yeah, yeah, that bug can get in there, and all of those kind of things. >> Dave: You flip 'em off with a punch card. Yeah, 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-Wave, which is annealer, a little different than gate-based machines, is really quite mature, right? And so, I think as you go back and forth between these machines, the gate-based machines and annealers, you can really get a sense for what's capable today with Braket 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 on Hamiltonian simulations for molecules, and those kids of things, because 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 customer's problems. And the problem we're solving with Braket 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. And 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, I've been doing a lot on those, as well. And the customer should have that choice, and with quantum computers, we're trying to do the same thing. We will have annealers, we will have ion trap machines, we will have electromagnetic machines, and others available on Braket. >> Can I ask a question on quantum if we can go back a bit? So you mentioned vacuum tubes, which was kind of funny. But the challenge there was with that, 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 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 at all times, right? And if you don't have ECC, you'd get crashes constantly on your machine. And so, we've built in ECC, so we're trying to build the quantum computers with the proper error correction, right, to handle these things, 'cause 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 computing. The ability to reproduce them in volume from an engineering perspective. 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, 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, other things like that, so you have to sort of faraday 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 works is well understood, how it works is not, right? No one really knows how entanglement works, they just knows what it does, and that's understood really well, right? And so, 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. >> Talk about the practicality. Andy Jassy was 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, we do. >> John: What is the practical thing? Is it just kicking the tires? Is it 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 with the work we're doing with Cal Tech and others, that the number of available cubits are starting to increase at an astronomic rate, a Moore's Law kind of of 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 kind 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 affects on Monte Carlo simulations. It'll have affects 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 yet," right? (men chuckle) So there may be times when you say, "Okay, I did this on a quantum computer," and you can only do it on a quantum computer. But then someone's very smart mathematician 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. 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 happy with what they did. They had a very low error rate with a large number of cubits, and that's a big deal. >> Well, I just want to ask you, 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 collaboration maybe a model here? I mean, what do think? You mentioned Cal Tech. >> It certainly is for us because, like I said, we're going to have multiple quantum computers available, just like we collaborate with Intel, and AMD, and the other partners in that space, as well. That's sort of 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 at Amazon, we don't invent everything, right? (Dave chuckles) >> So I got to ask you, obviously, we can take cube quantum and call it cubits, not to be confused with theCUBE video highlights. 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 you get the classic cloud, you got the quantum cloud. >> Well no, they'll be together. So I think a quantum computer will be used like we used to use a math coprocessor 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 real, practical example. So let's say you had a machine with 125 cubits, okay? You could just 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 a NP-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. The 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 problemistic or deterministic equation like that, not deterministic, a best-fit algorithm like that, much faster. And so, you could have it every second providing that. So your classical computer is sending out the manifests, 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, 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. >> It's a fast job, yeah. >> And it comes right back with the result. And then it continues with it's thing, passes it to the driver. Another update occurs, (buzzing) and it's just going on all the time. So those kind of things are very practical and coming. >> I've got to ask for the younger generations, my sons super interested as 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 an 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 an extent, as much as you can understand the physics behind it, right? I think the other areas, 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 regular computer science, or regular mechanical and electrical engineering are all neat. Mechanical around the cooling, and all that other stuff. Electrical, these are electrically-based machines, just like a classical computer is. And being able to code at low level is another area that's tremendously valuable right now. >> Got it. >> You mentioned best fit is coming, that use case. I mean, can you give us a sense of a timeframe? And people will say, "Oh, 10, 15, 20 years." But you're talking much sooner. >> Oh, I don't, I think it's sooner than that, I do. And it's hard for me to predict exactly when we'll have it. You can already do, with some of the annealing machines, like D- Wave, some of the best fit today, right? So it's a matter of 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, you can't do it at all, but that's coming. As you get to around 52, 50, 52 cubits, 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 about 125 cubits, you probably are at a point where you can't just simulate it anymore. >> But you're talking years, not decades, for this use case? >> Yeah, I think you're definitely talking years. I think, and you know, it's interesting, if you'd asked me two years ago how long it would take, I would've said decades. So that's how fast things are advancing right now, and I think that-- >> Yeah, and the computers just getting faster and faster. >> Yeah, but the ability to fabricate, the understanding, 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 claim that, 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 guess. >> So you're having fun? >> I am having fun, yeah. >> I mean, this is pretty intoxicating, technical problems, it's fun. >> It is. It is a lot of fun. Of course, the whole portfolio that I run over 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 and management systems, and all the real-time streaming. So like Kinesis Video, that's the back end for the Amazon ghost stores, and working with all that. It's a lot of fun, it really is, it's good. >> Well, Bill, we need an hour to get into that, so we may have to come up and see you, do a special story. >> Oh, definitely! >> We'd love to come up and dig in, and get a special feature program with you at some point. >> Yeah, happy to do that, happy to do that. >> Talk some robotics, some IOT, autonomous systems. >> Yeah, you can see all of it around here, we got it up and running around here, Dave. >> What a portfolio. >> Congratulations. >> Alright, thank you so much. >> Great news on the quantum. Quantum is here, quantum cloud is happening. Of course, theCUBE is going quantum. We've got a lot of cubits here. Lot of CUBE highlights, go to SiliconAngle.com. We got all the data here, we're sharing it with you. I'm John Furrier with Dave Vellante talking quantum. Want to give a shout out to Amazon Web Services and Intel for setting up this 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. (upbeat music)