 For those of you that may be new to quantum computing, there's a few fundamental concepts that make it remarkably different from classical computing. We're all familiar with the term bits. It's the fundamental unit of information that classical computers use today. We've seen endless representations of this binary system in the string of ones and zeros that people can to think of as data. However, in quantum, the fundamental unit of information is called a quantum bit or qubit. The basic idea is that this qubit could carry information quantum mechanically, or in other words, the same way that nature carries information. Simply put, a qubit is not bound to a binary system of information like ones and zeros, and that very simple difference is what makes quantum computing so powerful and so complicated. For you to truly appreciate what we've achieved and going to introduce you to two physicists who can tell us more about how we got here. Jerry, an exciting quantum research lab, tell us what did it take to build the first programmable quantum computer on the cloud in 2016? Really, in order to be able to get a system on the cloud, it started a lot in labs like this. We're working on fundamental research and understanding how to make the underlying qubits better, reproducible, reliable, and stable. We had to work on a lot of things to basically make them to be usable and actually accessible from anyone on the cloud. Now, it's actually very interesting looking back where we are today from even a decade ago. If you take a look right here, this was state-of-the-art in terms of our qubits in 2011. What happened since then? That was a decade ago, then 2016 first computer on the cloud. Then what happened in the last five years? Yes. Really in the last five years, it's all been about actually deployed real systems. We've deployed over 30 systems since 2016. Over 20 systems accessible right now through the IBM Cloud serving 150 clients, over 300,000 users running over a billion executions a day. Wow. That is amazing to just see that and just realize that now there's over 20 quantum computers. It's just an amazing progress. What's next? Yes. Really now what we're doing is we're building up towards new generations of systems. Last year we had the 65 qubit machine coming bird. This year we're going to have an Eagle processor over 127 qubits and moving towards 2023 over 1,000 qubits. 1,000 qubits. We're going to get a chance where that can be built. That's going to be built in this lab here, but then we're even looking beyond that. We need to look even how do we go beyond 1,000 qubits. So this is super fridge. Our project really to build a refrigerator that's going to be large enough to give us runway beyond 1,000 qubits. Yeah, so Jerry, so what are we seeing here? What is this giant thing? So in the other room we saw that there are actually these dilution refrigeration systems that allow us to cool down our qubits, our quantum processors to 15 milli Kelvin. And how cold is that? That's many, many times colder than it is outer space. But the point is that in order to actually cool them down, we also have all these other components that are part of it. So there's wires and there's filters and attenuators, all these different components. And as we scale up along that roadmap towards 1,000 and beyond, there's just more and more stuff. And so planning for say even up to a million qubits, we need to build bigger refrigeration systems and we're doing that right here. So it is a testament though of what it takes to succeed in quantum computing. You have to invest for a long period of time on these sustained roadmap. And it's also a reflection of the theme of today, of talking about hard tech in computing. And I gotta tell you, Jerry, the work that you and the team do, it is the hardest form of tech in computing. And I wanna thank you for all the fabulous work and keep up the great results. We're gonna be now talking to Jay Gambetta about how we are putting quantum to good use. Hey, Jay, how are you? Good. Good. Just came back from spending some quality time with Jerry. And it brought back memories of the launch of the IBM Quantum Experience. And it's a story that is not just about hardware. It's a huge software environment that makes all of this possible and makes quantum computing a reality. So first, what was a memory of that time in May, 2016? I think what I learned most and I learned a lot was there's a big difference between doing a science experiment and building a practical system. Yeah, because in the end, there's a difference. Once you expose it to that first week, you went from a few dozen people to thousands of people using the system. I mean, and the numbers are now what? Yeah, so as you say, we got up to 7,000 people in the first week and now we're up to around 300,000 users and they're running at least a billion circuits a day. You brought up quantum circuits and sometimes people get confused about what is a circuit. They imagine some physical connecting thing. But circuits, it's a software construct behind the scenes. What is a quantum circuit? Yeah, a quantum circuit is the fundamental unit for quantum computing. You can think of it as the instructions that can only be done on a quantum computer. It does the marvelous math that makes quantum mechanics possible. We sometimes draw the analogy of MIPS, like the number of instructions per second that you can run on a classical machine. But in quantum world is how many of these circuits can you run on an ongoing basis? Because some of the math that you get to do there, you can only do with quantum computers, but also you gotta run a lot of it. So how much do you need to run? So you can think of quantum computing as I need to run like a billion of these circuits. So take this nature paper from 2017 that we did. In this, we actually ran around four billion circuits. So let's take a billion circuits as a typical application. And if you think about that, if I need to run a billion circuits and I have to wait a microsecond for it, that means I'm gonna run it in basically 16 hours or so. If I need to run it at a millisecond, it's gonna be about 11.5 days. So now you see how fast I can run these circuits really matters for doing these practical applications. So I think that that's not widely appreciated, right? Any practical application, machine learning or chemistry or optimization that you wanna leverage the power of quantum systems, you're gonna need to run hundreds of millions or a billion quantum circuits iteratively, right? To get to your answer. One of the reasons I really love the superconducting system is the fundamental physics allows us to run these with fast gates, fast reset. In fact, our latest Falcon processor has an update that gives you ability to reset the qubits in less than a microsecond. And you ask for the comparison to irons. Irons have done wonderful demonstrations. They keep pushing the fidelity, they're great. But at the moment, they're time to cool and get their trap ready. So to get the quantum two-cubic gate to happen takes 100 milliseconds typically. And this is a big challenge for them. They've got some great demonstrations that are showing some ways to get beyond it. But at the moment, it's really, really slow for them to run it. And this is why for a superconducting technology, we can imagine we can run our circuits at a much faster pace. But again, it's milliseconds versus microsecond. There's a factor of a thousand X there. So let's bring it back to an application. You're saying to be able to reproduce state-of-the-art results, so say of a chemistry experiment, but that would be true for machine learning as well. You're talking then down the road of comparing technology that would deliver your result in tens or hundreds of days versus being able to do things in days or hours. That's the difference. This is one of the reasons we like this technology because we can see how we can build a business on it. We can run for the users, maybe thousands of applications per day with all the systems we have. And we can see that we'll be able to get lots of results. Whereas I look at these ions as a great example of a scientific experiment. It gets us to today's announcement, right? Of something called the Quiskit runtime. You had set the goal for the team of achieving a 100X speedup. So tell us what it is. Yeah, so I would like to correct you slightly. We got 120 times, and as a combination of the runtime, better devices, better software, and some algorithmic improvements. I'm very happy that we got what we promised. I'd love to be corrected when it's better. But let me show you how it works. Okay, let's take a look. For this problem, the first step is the user needs to define a molecule and its electronic structure. The next step, the user needs to specify the quantum program and the circuits that will be used. Then the user constructs the VQE program that they want to run. This is based on the Quiskit runtime as we talked about. Now they simply just call solve. So now here's where the fun starts. The quantum computer is now this quantum system plus a hybrid classical server plus the user's computer. Let's start with the user in San Francisco. The runtime program now goes to the user's computer through the cloud. And it actually in our case goes to the IBM cloud that's in Austin, where it's authenticated and sent to the IBM quantum data center in Poughkeepsie. Here the runtime manager starts. It sets up this new container program and this does the classical computing and it makes the circuits to be run. As you see, there's lots of circuits that are being sent to the quantum systems. These are run on our quantum systems and the results come back and you'll see there's lots of zeros and ones. Now it goes to the classical server again and it processes those results. And if the algorithm calls, it resends those circuits through to the quantum system and it comes back again, processes the results, gets the final answer and sends it back to the user that's in San Francisco and now they see, as in this example, the chemistry plot. I think everybody's gonna be feeling a set of relief to say they're not gonna need to know quantum mechanics to benefit from quantum computing. But this vision is powerful, right? Because you're gonna run your everyday program that you like and behind the scenes, this is what's gonna enable right through this runtime. So Jay, that's amazing. What's next? So what's next? There's beyond the chemistry, we also have an exciting result in AI where we actually use this hybrid classical computer combination to find the correct circuits to improve an AI task. And I'm excited to bring that out. And ultimately the release of our 127 qubit system this year. Yeah. So that's the thing. We talked a lot about chemistry but there is a burgeoning field of the intersection of quantum and AI and the theory team and the software team has a really seminal work that is also really influencing deeply the field and now this roadmap of more powerful machines. Thank you for you the team and the whole Qiskit community and the IBM Quantum Community that are really pioneering a whole new industry. So a pleasure and talk to you soon. We've defined the industry's leading roadmap for quantum advancement through our family of superconducting and cubing processors to deliver generation after generation the most capable quantum computers in the world. A new system every year with the goal of unleashing the era of quantum advantage where we aim to achieve computational speeds that will drastically exceed classical computers. We're making the hard tech of quantum frictionless for the user. That's why we've curated, created and nurtured a global quantum community through our open source software Qiskit the world's most popular software development environment. It has helped usher a fast growing quantum developer community and we brought the power of all of this to business with our IBM Quantum Network a global network of quantum computing partnership consisting of hundreds of businesses, startups institutions and governments. It's been an incredible journey so far but know that we're just getting started. 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