 Our next speaker, Talia Gershon, will tell you a little bit more about how they work and how the way we think about them is going to change within the next five years. Talia is a good friend of mine and a passionate advocate for quantum computing. She leads a team of software engineers and designers that make quantum computing available in the cloud and also grows and nurtures a community around our quantum computing platform. Please welcome our last speaker, Talia. All right, thank you, Jamie, for the introduction. And I want to start off with just a quick poll of the audience. So how many of you have heard some buzz about quantum computing? Probably most of you. OK, and how many of you really feel like you know what it is? OK, well, thank you for your honesty. And it's a good thing you're all here at Think because we have four awesome days of programming that should help give all of you a flavor for what quantum computing will do and what quantum computing will do. And we also have a booth here, so I encourage you all to come by and talk to us. Whether or not you know it, there's problems we just can't solve today, even using our biggest classical supercomputers. Take, for an example, accurately simulating the bonding in large molecules. It sounds like we should be able to do this, but the computation required for the job grows exponentially the bigger the molecule you're trying to simulate. That's because to do this properly, you have to account for the effect of every single electron on every other electron. The more electrons you have, the exponentially more computation is required. And the fact that there are problems we can't solve today is why exploring fundamentally new ways of doing computation might open up new doors. So enter quantum computing. Let me summarize it as follows. Quantum computing is a technology that encodes information into complex quantum states. It uses operations performed on those states to process the information, and it uses a measurement of the final state to record a result. Seems simple enough? Actually, no. It's still pretty complicated. And it's an interdisciplinary problem. And even just the theory alone is interdisciplinary. It's built on a foundation of the physics of quantum mechanics and quantum information. And it's written in the language of linear algebra, which we use to represent a quantum state and how it transforms throughout an algorithm. And we weave in computer science to translate the theory into executable commands that we can run on a machine. And experimental quantum computing is interdisciplinary, too. We're building real systems that can implement the theory, meaning real devices that behave like qubits or quantum bits with quantum properties that can be manipulated. This requires physics, material science, and device fabrication expertise. And we need to be able to control the qubits, which requires microwave signal processing and electrical and controls engineering. And we need to cool these chips down to 15 milli Kelvin, or 460 degrees below zero Fahrenheit, which requires advanced cryogenics. My point is that quantum computing is not just a game for physicists. And building it into a scalable technology is going to require breakthroughs across a whole range of STEM disciplines. And it's going to require that we fundamentally change the way we think. My friend and colleague, Jay Gambetta, leads our quantum theory and software teams in IBM Q. And I've often heard him say to people, including me, you're thinking too classically. What he means by that is that you're trying to apply linear, classical, logical thinking to understand something quantum, and it doesn't work. And he said this phrase enough times that it's become a mantra and a sticker that adorns all of our laptops. You're thinking too classically, hashtag IBM Q. And as funny as it is, thinking too classically is a real problem that hinders progress. So how do we get people to change the way they think? Well, we start in the classroom. When Einstein first discovered relativity, I'm sure nobody intuitively got it and understood why it was important. And today, it's in every modern physics classroom in the world. Within five years, the same thing will happen with quantum computing. Not only will physics departments offer quantum information classes, but computer science departments will offer a quantum track. Electrical engineering departments will teach students about quantum circuits and microwave signal processing. And chemistry classes will teach students not only how to simulate molecules on a classical machine, but also on a quantum computer. I did my undergraduate at MIT and I majored in material science. And I remember that the class that really inspired me the most and made me want to pursue a career in this field was 315, electrical, optical, and magnetic materials and devices. It taught me about every device of technological importance. Transistors, lasers, LEDs, magnetic hard drives you name it. What is it made of and how does it work? Within five years, that class will teach students about qubits. What are they made of and how do they work? And the same thing will happen across a whole range of disciplines. And these changes will be enabled by the fact that more and more teachers will use quantum computers in the classroom. Students and teachers will use quantum computers in the classroom and they'll have access to tools that we never had. Thanks to the IBM Q Experience, they can already access quantum computers today. It's a set of three prototype quantum computers that we've made available through the cloud with two different ways of programming them. A graphical interface with drag and drop operations and an open source software developer kit called Qiskit. Today over 1500 universities around the world have people with registered accounts on the IBM Q Experience. And more and more universities will join the ranks of Oxford and Kayo universities and the University of Melbourne as hubs in the IBM Q network to access our more advanced hardware. A few months ago, I was working late one night exchanging Slack messages with Jay when a photo popped up in my Slack window. It was a photo of Jay's nine-year-old daughter sitting on the couch playing with the IBM Q Experience. And it came with a caption that read, she's always asking to play with the quantum computer. She was nine years old. And this photo really stuck with me because she represents a generation of up-and-coming scientists that are gonna grow up without being constrained by thinking too classically. The existence of tools like the IBM Q Experience and Qiskit mean that she will have the resources and the community that she needs to learn about and then shape the field of quantum information. And the fact that these tools are open and available to everyone means that she could have been anyone's son or daughter. And that's pretty cool. Over the last five talks, you've heard a lot about AI and quantum computing. And the thought I wanna leave you with is that these fields are not fully independent. We believe that applying AI to the development of quantum computing will help accelerate our rate of progress in that field. And we also believe that by developing universal quantum computers, we'll have new tools that we can use to accelerate our rate of progress in AI. Thank you.