 From around the globe, it's theCUBE with digital coverage of AWS re-invent 2020. Sponsored by Intel and AWS. Hello and welcome back to theCUBE's virtual coverage of AWS re-invent 2020. I'm John Furrier, your host. This is theCUBE virtual. We're here not in remote, we're not in person this year. So we're doing the remote interviews and then this segment is going to build on the quantum conversation we had last year. Richard Moles, general manager of Amazon Bracket and Idwis Quantum Computing and Fernando Brandow, head of quantum algorithms at AWS and Brent professor of theoretical physics at Caltech. Fernando, thanks for coming on. Richard, thanks for joining us. You're welcome. It's a pleasure to be here. So Fernando, first of all, love your title, quantum algorithms, that's the coolest title I've heard so far and you're pretty smart because you're a theoretical professor at physics at Caltech. So which I'd never be able to get into but I wish I could get into there someday but thanks for coming on. Quantum's been quite the rage and there's a lot of people talking about it. It's not ready for prime time. Some say it's moving faster than others. Where are we on quantum right now? What are you seeing, Fernando, where the quantum, where Pegas in the evolution of where we are? Yeah, quantum, it's emerging and rapidly developing fields. But we're still early on both in terms of hardware development and in terms of identifying the most impactful use cases of quantum computing. So it's early days for everyone and we have like different players and different technologies that are being explored. And I think it's early but it's exciting time to be doing quantum computing and it's very interesting to see the interest in industry growing and customers, for example, customers from AWS be willing to take part in this journey with us in the development of the technology. Awesome. Richard, last year we talked to Bill Vass about this and he was, you know, he said expectations really well, I thought, but it was pretty much in classic Amazonian way, you know, makes the announcement, a lot of progress then makes but give us the update on your end. You guys now are shipping brackets available. What's the update on your end? And Werner mentioned it in his keynote this week as well. Yeah, it was great. I was relooking at your interview with Bill. It was, that was when we launched the service a year ago, almost exactly a year ago this week. We come a long way. So as you mentioned, we've gone general availability with the service now that happened in August. So now any AWS customer can log into the Bracket console and start programming quantum computers. You know, there's tremendous excitement, obviously, as you mentioned and Fernando mentioned, you know, quantum computers, we think have the potential to solve problems that are currently unsolvable. And the goal of Bracket is to fundamentally give customers the ability to go test some of those notions, to explore the technology and to start planning for the future. You know, our goal was always to try and solve some of the problems that customers have had for, you know, a decade or so now, you know, they tell us from a variety of different industries, whether it's drug discovery or financial services, whether it's energy or this chemical engineering, machine learning, you know, the potential for quantum computer impacts many industries could potentially be disruptive to those industries. And it's essential that customers can plan for the future, you know, build their own internal resources, become experts, hire the right staff, figure out where it might impact their business and, you know, potentially disrupt. So, you know, in the past, they found it hard to get involved. You know, these machines are very different, different technologies, building different ways, have different characteristics. The tooling is very disparate, very fragmented historically. It's hard for companies to get access to the machines. These tend to be, you know, owned by startups or in, you know, physics labs and universities, very difficult to get access to these things, very different commercial models. And as you suggested, a lot of interest, a lot of hype, a lot of claims in the industry, customers want to cut through all that. They want to understand what's real, what they can do today, how they can experiment and get started. So, you know, we see bracket as a catalyst for innovation. We want to bring together end users, consultants, software developers, providers that want to host services on top of bracket, try and get the industry, you know, revving along. And you spoke to lots of Amazonians. I'm sure you've heard the phrase, innovation fly wheel plenty of times. We see the same approach that we've used successfully in IoT and robotics, machine learning and apply that same approach to quantum machine learning, sorry, to quantum computing and to bring everybody together. And if we get the tooling right and we make it easy, then we don't see any reason why we can't rapidly try and move this industry forward. It's one of those fun areas where there's a lot of, you know, intellectual, computer science, technology, science involved and it's super exciting. You know, Amazon also says undifferentiated heavy lifting. And you know, it's like, there's a massive hierarchy of needs in the tech industry, you know, people say, oh, wifi, people freak out when there's no wifi. You know, you can't get enough compute, right? So, you know, compute is one of those things with machine learning is seeing the benefits and quantum, there's so much benefits there. And you guys made some announcements at re-invent around bracket. Can you share, just quickly share some of those updates, Richard? Sure, I mean, it's the way we innovate at AWS, you know, we start simple and we build up features, we listen to customers and we learn as we go along and we try and move as quickly as possible. So, since going public in August, we've actually had a string of releases, pretty consistent delivery new features. So, we're trying to tie in up the integration with the platform. Customers have told us really very early on that they don't just want to play with the technology. They want to figure out how to envisage a production, quantum computing service, how it might look, you know, in the context of a broad platform such as AWS. So, we've launched some integration with other AWS capabilities around security, managing limits, quotas, tagging resources, that type of thing. Things that are familiar to current AWS users. We launched some new hardware. One of our partners, D-Wave, launched some, you know, a 5,000 qubit machine just in September. So, we made that available on Bracket the same day that they launched that hardware, which is very cool. You know, we've made it easier for researchers. We've been impressed how many academics and researchers have used the service, not just large corporations. They want to have really deep access to these machines. They want to program these things at a low level. So, we launched some features to enable them to do their research. But at re-invent, we really focused on two things. Simulators are making it much easier to use hybrid systems. Systems that incorporate classical compute, you know, traditional digital computing with quantum machinery in the vein that follows some of the leads that we've seen in machine learning. So, simulators are important. They're a very important part of learning how to use quantum computers. They're always available 24 seven. They're super convenient to use. And of course, they're critical in verifying the accuracy of the results that we get from quantum hardware. When we launched the service, we have free simulator for customers to help debug their circuits and experiments quickly. But simulating large experiments and large systems is a real challenge on classical computers. You know, if it wasn't hard on classical, then you wouldn't need a quantum computer. That's the whole point. So, running large simulations is expensive in terms of resources. It's complicated. We launched a pretty powerful simulator back in August, which we thought at the time was always powerful managed quantum simulator could handle 34 qubits. And at Reinventures last week, we launched a new simulator, which is actually the first managed simulator to use tensor network technology and it can run up to 50 qubits. So, we think is probably the most powerful managed quantum simulator on the market today. And customers can flip easily between either using real quantum hardware or either of our stimulators just by changing a line of code. The other thing we launched was the ability to run these hybrid systems. You know, quantum computers we'll know don't get on to it in a moment is today's computers are very imperfect. You know, lots of errors. We're working obviously the industry towards fault tolerant machines. And Fernando can talk about some research papers that we've published in that area. But right now the machines are far from perfect. And the way that we can try to squeeze as much value out of these devices today is to run them in tandem with classical systems. We think of the notion of a self-learning quantum algorithm where you use a classical optimization technique such as we see machine learning to tweak and tune the parameters of a quantum algorithm to try and iterate and converge on the best answer and try to overcome some of these issues surrounding errors. That's a lot of moving parts to orchestrate for customers. A lot of different systems, a lot of different programming techniques. And we wanted to make that much easier. We've been impressed with an open source project that's been around for a couple of years called Penny Lane after the Beatles song. So we wanted to double down on that. We were getting a lot of positive feedback from customers about the Penny Lane toolkit. So we decided to make it first class citizen on bracket, make it available as a native feature in our Jupyter notebooks and our tutorials and learning examples. The open source project has very similar guiding principles that we do. It's open, it's cross-platform technology agnostic and we thought it was a great fit to the service. So we announced that made it available to customers and already getting great feedback. So finishing the year strongly, I think, looking forward to 2021, looking forward to some really cool technology that's on the horizon from a hardware point of view, making it easy to use and always also trying to work back from customer problems and so on. Congratulations on the success. I'm sure it's not hard to hire people interested at least they find and qualify people. They'd be different, but you know, sign me up. I love quantum. Great people are right. Fernanda real quick understanding the relationship with Caltech unique to Amazon. Tell us how that fits into this. Right John, as I was saying it's early days for quantum computing and to make progress, AWS put together a team of experts to work both on finding new use cases of quantum computing and also building more powerful quantum hardware. So the AWS Center for Quantum Computing is based at Caltech and this comes from the belief of AWS that in quantum computing is key to keep close to stay close of like fresh ideas and to the latest scientific developments, right? And Caltech is a pioneer in quantum computing. So it was the ideal place for doing that. So in the center, we put together researchers and engineers for computer science, physics and other subjects from Amazon, but also from other academic institutions. Of course in Caltech, but we also have Stanford and University of Chicago among others. So we broke ground in the beauty for the AWS Center for Quantum Computer in the summer and under construction right now. But as we speak, John, the team is busy building stuff in temporary lab space that we have at Caltech. Awesome, great. And real quick, I know we got some time pressure here, but you published some new research. Give a quick plug for the new research. Tell us about that. Right. So as part of the effort of the AWS Center for Quantum Computing, we are developing a new qubit which is a combination of acoustic and electric components. So this kind of hybrid acoustic electric qubits has their promise for a much smaller footprint. Think about like a few micrometers and much longer storage times like up to a second which is a big improvement over the state of the art on superconducting all electrical based qubits. But that's not the whole story, right John? So if you have a good qubit, you should make good use of it. So what we did in this paper that we just put out is a proposal for an architecture of how to build a scalable quantum computer using these qubits. So we found from our analysis that we can get more than a 10X overheads in the resources required for building a universal photo around quantum computer. So what are these resources? This is like a smaller number of physical qubits. This is a smaller footprint. It's fewer control lines and like a smaller progenic system, right? And these are all like, I think this is a solid contribution. It's a theory analysis, right? So the experimental development has to come, but I think this is a solid contribution in the big challenge of scaling up this quantum systems. So John, as we speak, like the AWS Center for Quantum Computing is working on the experimental development of this in the hybrid acoustic architecture, but we also keep exploring other promising ways of building scalable quantum computers and eventually to bring more powerful computer resources to AWS customers. It's kind of like machine learning and data science. The smartest people work on it, then you democratize it. I can see where this is going. Richard, real quick, for people who want to get involved and participate or consume, what do they do? Give us the playbook real quick. It's very simple. Just go to the AWS console and log on to the bracket console. Jump in, create a Jupyter notebook, pull down some of our sample applications, run through the notebook and program a quantum computer. It's literally that simple. There's plenty of tutorials. It's easy to get started. Classic cloud style, right? Now up front commitment, jump in, start simple, get going. Once you go quantum, you can't go back. Go quantum, you can't go back to regular computing. I think people will be running quantum and classical systems in parallel for quite some time. So yeah, this is definitely not a one-way door. Go explore quantum computing and see how it fits into solving some of the problems that you want to solve in the future. But definitely, this is not a replacement technology. This is a complementary technology. It's great. It's a great innovation. It's kind of intoxicating technically to get think about the benefits. Fernando, Richard, thanks for coming on. It's really exciting. Looking forward to keeping track of the progress. Thanks for coming on. Thank you. Thank you. It's the cube coverage of re-invent. Quantum computing going the next level, co-existing, building on top of the shoulders of other giant technologies. This is where the computing wave is going. It's different. It's impacting people's lives. This is the cube coverage of re-invent. Thanks for watching.