Accelerating Quantum Computing Research and Innovation with AWS

How will democratizing access to quantum computing create advancements that will redefine AI?

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At the Six Five Summit, host David Nicholson is joined by Amazon Web Services (AWS)' Eric Kessler, General Manager, Amazon Braket. The discussion offers an in-depth look into how AWS is spearheading the quantum computing revolution through a dual strategy aimed at democratizing access to quantum technologies and pioneering advancements in the field.

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Key takeaways include:

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🔹Democratizing Quantum Access: Explore how AWS is making quantum computing accessible to a wider audience, breaking down barriers to entry and fostering broader innovation.

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🔹Pioneering Quantum Science & Hardware: Delve into AWS's significant advancements in quantum science, including the exciting development of their Ocelot chip, pushing the boundaries of quantum hardware.

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🔹Integrating Quantum and Classical Computing: Understand the critical role of Amazon Braket in seamlessly integrating quantum and classical computing, enabling hybrid solutions for complex problems.

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🔹Driving Scalable & Practical Quantum Futures: Gain insights into AWS's contributions to error correction and hardware efficiency, crucial steps towards making scalable and practical quantum computing technologies a reality.

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Learn how to begin your quantum computing and start experimenting with quantum algorithms at Amazon Web Services.

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Watch the full video at Six Five Media, and be sure to subscribe to our YouTube channel, so you never miss an episode.

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Or listen to the audio here:

David Nicholson: Welcome to the Six Five Summit: AI Unleashed. I'm joined today by Eric Kessler, General Manager of Amazon Braket at AWS for the Quantum Spotlight session on accelerating quantum computing research and innovation with AWS. Welcome, Eric.

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Eric Kessler: Thanks, Dave. Very great pleasure to be here.

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David Nicholson: Good to see you. Well, quantum computing is always a very interesting subject. We've been talking about quantum for years. There's always room to sort of separate where we actually are from where we hope to be one day. So if we accept that quantum computing is in its early stages, what are you doing at AWS to make this technology accessible and accessible to who?

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Eric Kessler: Yeah, Dave. At Amazon, every question, including this question starts with a customer. And as a matter of fact, it goes back to 2019 when I was actually still working on the machine learning side at AWS. But already there, I heard from customers anecdotally that they were wondering about this technology and what does it mean for their particular business if it matters, and if they should get started to get involved, and if so, how? Right? And we had many more of these types of conversations, and ultimately that led us to launch Amazon Braket, the quantum computing service of AWS with the goal to make access to quantum computers easier for customers so that they, for themselves, can cut through the hype, distinguish what is narrative from what is reality, and understand what this technology is really capable of. 

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I think since our launch in 2020, we have seen customers go way beyond that, right? So we have customers that are really trying to push the boundaries with these devices, using these devices, early quantum computers for scientific discovery to do application development. For example, we have been working over the past two years with JPMorgan Chase through our Amazon Quantum Solutions Lab to develop novel protocols that use analog quantum devices in this case for specific types of optimization problems and trying to understand the scaling laws that govern these protocols. And that's an example of the enterprise, but also a lot of academics are using Amazon Braket. We have a study with Purdue University together with Oak Ridge National Lab, where they were looking into using quantum computers to study a particular quantum mechanical models and investigate phase transitions. Again, very physical, very, very foundational, physical. I just want to show you, the range of applications that our customers are interested in today.

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David Nicholson: Well, you talk about the range of applications. If I were to do an old-fashioned web search on AWS and quantum, I would hear about Braket, but I would also hear about other things like Ocelot. So how do you, tell us about this multiprong. There's at least two prongs to it. Tell us about your multipronged approach and where does Braket end and Ocelot begin? How are they related?

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Eric Kessler: Yeah, absolutely. So Ocelot is a quantum prototype, a quantum computing prototype that was developed by the Center of Quantum Computing. That's a part of our organization, an R&D lab, located at the campus of Pasadena, of Caltech. And I think in the long term, we all believe that quantum computing will have a transformational impact on a variety of different verticals, but we also think that it's going to be a long way. And that quantum error correction is a fundamental ingredient to this. And that's why we founded the CQC, the Center for Quantum Computing as an R&D lab to focus on the development of techniques and technologies specific to quantum error correction and making quantum error correction viable. And Ocelot is the first prototype that we announced out of this effort, which is an architecture that combines bosonic so-called cat qubits with transmon qubits to enable a more efficient type of quantum error correction that we believe is 10 times more resource efficient than traditional approaches.

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But of course, we also know like any other technology is not going to be that we one day wake up and we have a fully functioning fault-tolerant quantum computer with applications and industry ready to go, right? When you take the analogy to machine learning and artificial intelligence, that field, despite a lot of theoretical work in the last century, only really took off when customers had access, ready access to compute and the data to work with that. And we see the situation very similar in quantum computing, right? We want to drive a similar kind of flywheel and that is why we launched Amazon Braket, one of the motivations where we launched Amazon Braket, where we want to bring early quantum computing devices as they mature to our customers, expose them, make them accessible to a broad range of customers and researchers so that they can explore applications and develop protocols along the way to that end goal. And in turn, inspire and show new applications to hardware developers and drive that flywheel.

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David Nicholson: Yeah, and as you drive that flywheel, obviously, classical computing doesn't disappear one morning or it does, little quantum humor there, right? It does and yet it doesn't at the same time. But do you expect this to be a hybrid scenario when it comes to quantum plus classical computing for a while and what's AWS's strategy there?

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Eric Kessler: Yeah, really, I think our perspective is that really, all quantum computing is hybrid quantum computing. There is no such thing as a pure quantum computer, right? Even if you think about very close to the hardware on the lowest timescale, maybe on the lifetime of a qubit, when you think about quantum error correction. That is a hybrid system of a classical controller and classical logic to decode the information that comes from a quantum chip to correct the errors. And if you zoom out a little bit, of course, we have a different timescale where there are protocols that use quantum computers iteratively between classical and quantum operations. This is a feature that we have supported on Amazon Braket for many years through Amazon Braket hybrid jobs. So we try to optimize that kind of workflow.

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And then finally, when we zoom out all the way and look at the applications that we believe quantum computers ultimately will be used for, we look at how customers are doing this today on AWS. It's not a single monolithic step. These are processing pipelines that use various types of HPC processing in a state function pipeline. And we don't think that, and we are very confident that quantum computers will not replace this entire pipeline. Quantum computers will be used as a very specific form of an accelerator that takes on one particular slice in that workflow that is amenable for accelerations to quantum properties, and will accelerate that piece. So in the long term, we think that quantum computers are, in quotes, "just another type of accelerators" that will be embedded in a variety of different classic compute forms.

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David Nicholson: So Braket allows you to access a whole variety of different computing technologies from a variety of providers. Why wouldn't you just sort of pick the best horse ride only it? I want to get your answer to that first and then I've got a follow-up.

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Eric Kessler: Yeah, sure. Well, I think one lesson that we learn over and over and over again at AWS is that there is not a single tool to rule them all, right? It's not the case in analytics, it's not the case in databases. It's not the case in AI, and it surely is not the case in quantum computing, right? Customers want the choice, and especially in quantum computing, as the technology is still very nascent. There are a lot of different technology platforms with different pros, different cons, and part of the challenge is to figure out what are the properties of different technology pathways and what are the most promising ones?

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And we see ourselves actually very closely related philosophically with Amazon Bedrock, our service for large language models, right? There also, we have a suite of third-party large language models that are available to customers for different use cases with different pros, different cons, and at the same time, we're developing our own models, the Nova models that we have released recently that are also available through Bedrock. And if you think about it, that's exactly the model that we want to pursue with Amazon Braket to give customers really the choice of technology that they want.

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David Nicholson: Yeah, that was actually my follow-up. So it sounds like the answer to my follow-up question, which was, is it a proper analogy to draw between what we're seeing with AI, let alone just using the term AI, but when someone says a model, it doesn't look like at any point in the near future there will be one model that will rule them all. In the field of quantum computing, we haven't even settled on how to derive these qubits yet. Can you envision a scenario in the future where there will be multiple ways to leverage quantum, just like there are multiple ways to leverage large language models as an example? I think that's what I heard you just say.

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Eric Kessler: Yeah, no, absolutely. I mean, I think it's far from being a foregone conclusion that this is a winner-take-all technology, so to say, right? These technology pathways that we see at the moment from Rydberg atoms to ion traps to superconducting qubits, spin qubits, photonics, right? There's five to six prominent technologies that are actively being pursued and all of them with very different properties, right? So you could think about, there are certain trade-offs for communication networks that might be suitable as certain algorithms might require higher throughput, which would point you in the direction of a certain technology platform. I think time will tell, but at the moment, I think it's way too early to call a winner.

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David Nicholson: So I'm going to toss in a bonus question, and this comes from some of my students in the CTO/CIO program that I teach. A lot of them are struggling right now to answer the question, how do I get ROI out of AI, let alone, let alone quantum. They're looking at how to leverage AI to make money and/or save money. What's a good way for them to keep on top of or get started with quantum so that they're not blindsided by these developments? So let's say that AWS is here with me. I'm the CIO of a large organization. What's the answer to that? How do I get started? What should I... Do you have a version of Braket that I can play with so I can become familiar? Where do I start, Eric?

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Eric Kessler: Yeah, absolutely. So Amazon Braket, we provide a number of different resources to get started quickly. We have our open source GitHub repositories with a host of different getting started tutorials, explanations of different technologies. So I would encourage everyone to take a look at that, and you can use it for free with the simulators that are included in our Amazon Braket SDK, which is also open source and available to download. And then as a next step, you can also use the hosted simulators on the service. I would also encourage folks to take a look at our Quantum Technologies Blog on AWS, where we often highlight interesting work that people are doing with Amazon Braket, as well as results from our own research at the Center for Quantum Computing and solutions that our partners are building.

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David Nicholson: So Eric, you work in the quantum computing field. In your wildest dreams, let's say five years out, what is the sort of intractable problem that you hope leveraging quantum computing will help us solve that we haven't been able to solve with classical computing? Have you given that any thought?

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Eric Kessler: Yeah, Dave, of course. You see, I think the important thing about quantum computing is that it is not just making things that we do today a little bit faster, a little bit cheaper. It is very profound in the sense that it enables us to compute a whole new class of problems, most famously understanding nature at the microscopic scale where quantum effects come into play. And ultimately, that is a very profound shift in our ability to compute things in nature, right? So that, as a scientist, gets me just extremely excited. And of course, the dream is to exploit that capability to understand phenomena like high temperature superconductivity or important molecular reactions, for example, in the production of ammonia, which would've a very large economic impact.

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But I guess, in practice, I am a little bit more humble because I know how big of a scientific and engineering challenge that is. But already in the field of material science, when we look at fairly simple materials, the computation of time dynamics, right? Dynamic reactions of materials to external factors are extremely difficult to compute with classical means. And I think this will be one of the first real impact applications of quantum computers to help us understand time dynamic simulations on materials which exhibit quantum effects. And that will be a new capability for us that we hope we will find interesting applications for.

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David Nicholson: Exciting times ahead. Eric Kessler, AWS, specifically talking about quantum computing. Thanks for joining us for this quantum spotlight at The Six Five Summit. Stay connected with us on social and explore more conversations at sixfivemedia.com/summit. More insights coming up next.

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