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Welcome to the EY Think Ecosystem podcast, a series exploring the intersection of technology, collaboration, and innovation. In each episode, we orchestrate insights, stories and perspectives from across the EY partner ecosystem, our client base and our leadership team to address the important issues and challenges of today.

Brad Artigue  

I am your host, Brad Artigue, Global Leader of the IBM Tech Hub at EY.

In this episode, we will explore the intersection of quantum computing and the race to deliver useful applications beyond what even our supercomputers could ever do. 

As the world grapples with daunting challenges in business, science, and society at large that we know our classical computers won't be able to solve, we are increasingly seeking innovative solutions using innovative, but still nascent, technology like quantum.

What are some of those challenges? Well, EY recently joined the IBM Quantum Network to start collaborating on a number of them, including sustainability use cases like the reduction of CO2 emissions from classical computing.

During this podcast, our guests will explore cutting-edge quantum research and its practical application within the context of sustainability. 

We will speak with experts in both quantum computing and sustainability, delving into the ways in which quantum computing could be applied in the future to support industries' efforts to apply more sustainable, renewable – green – business practices. 

We're in very good hands with two esteemed thought leaders to take us through the challenges and opportunities associated with this fascinating topic. But before I introduce them, please remember: Conversations during EY podcasts should not be relied upon as accounting, tax, legal, investment nor other professional advice. Listeners must consult their own advisors.

Joining us from North Carolina is Richard Padbury, global lead of GSI and consulting partner at IBM Quantum. Great to have you on board, Richard. IBM is at the forefront of quantum research and recently unveiled the Osprey, the world's most powerful quantum processor. So I can't wait to hear your thoughts.

Richard Padbury  

Thank you, Brad; I really appreciate the introduction. And I'm excited to be here today to talk about this exciting topic.

Artigue  

And from Washington, DC, I'm delighted to welcome Kristin Gilkes, EY's Global Quantum Leader. Thanks for fitting us into your busy schedule, Kristin. As a quantum expert and racecar driver with links to the supercar automotive industry, I'm sure you have some great insights on the race to net zero.

Kristin Gilkes  

Thanks, Brad. And hi, Richard. Super excited to join you both today, and hello to everyone listening. Look, quantum and motorsports are two of my favorite subjects. I'm delighted to be here. Thank you. The race to net zero drives innovation. And just this week, we had the debut of the world's first super sport V12 hybrid electrified vehicle. I mean, that's progress in and of itself. Four years ago, when I was racing around the track, we only began to imagine what it would be like to go from zero to 100 kilometers in 2.5 seconds in something electric. But now it's here and available, and quantum-based physics made that happen, Brad.

Artigue  

It's amazing technology. It's amazing just to be in the presence of one of these machines. It's amazing to be with the people who built them. And the people who continue to engineer innovation. We're seeing the next generation of computing unfold really right before our eyes. 

Gilkes  

Yeah, very much so. 

Artigue  

Well, let's start with you, Richard. I think we should begin with some background. So we're all on the same page. I'm going to challenge you to try to sum up quantum computing in a few sentences and why it's causing so much excitement.

Padbury  

Okay, so this is a great question to start with but a very challenging one to describe. So here we go, my best effort. So quantum computing draws on the fundamental laws of nature to carry out calculations using what we call quantum bits or qubits. And unlike the types that we use in classical computing, which can be, you know, one bit can either be a one or a zero at any given time, qubits can be in a complicated mix of one and zero, which we call superposition. And this allows us to explore very complicated computing spaces out of reach of classical computers. And so this gives quantum computers the potential to solve very, very complicated problems.

Gilkes  

And in a really illustrative manner, sometimes when I answer that question, I like to say, in a classical computing world, two plus two equals four; everybody can relate to that, right? But in quantum two plus two has this probability of being pink. It's producing a result to something in a probability kind of way of saying this answer over here is possible because we were never able to combine all of those elements that you were saying a moment ago together. And so it presents a different result or a different answer to a question than we would have seen before.

Padbury  

Yeah, absolutely. And I think the probability aspect that you mentioned is also another key aspect here that our answer is a probability. And so we have to run our ones and zeros many, many times over to get the answer that we're looking for. But still, I think, you know, it's exciting that we can process information in this new way. And hopefully, that helps us to ask new questions that we couldn't before. And, you know, really think about problems in new and exciting ways.

Artigue  

It's not just about speed, right? That's the sort of what I call the common man's correlation between classical computing and quantum. You keep hearing that, so it's a billion times faster. And I don't know if we need to calculate two plus two equals four billion times faster. It's pretty quick on a regular machine. But it's a different kind of computing. Right, Kristin? It's a paradigm shift in technology.

Gilkes  

Yeah, it absolutely is. And I think we should just talk about a little bit of what that means in terms of society, right? So at EY, our mission is to build a better working world, and our quantum team is focused on solving some of our client's most challenging problems, from drug discovery that one day could cure cancer to how do you make supply chain logistics more efficient, that optimize for speed, cost, and sustainability. So Brad, the impact that quantum will have on societies, it's going to be huge. And as a quantum scientist, I don't even think we know all the potential problems that quantum is going to be able to solve. The future of quantum will include those intersections between wildly divergent disciplines and subject areas.

Padbury  

So I completely agree with Kristin. So at IBM Quantum, we're interested in three areas where we believe quantum may play a role. So simulating nature, nature itself behaves in a quantum mechanical way. So we believe that quantum computing will obviously have an impact there. So that ties into the drug discovery that Kristin mentioned, as well as other chemistry problems. Then there's processing data with, you know, very complicated structures and optimization problems. And as Kristin says, you know, these three areas map to a large number of challenges across different industries. And some were exploring today, but there are likely many, many more out there that we've not even come across yet, which is very exciting. 

Artigue  

Yeah, let's talk about progress. Talk about what you're building. Today, I was on LinkedIn, and someone posted a picture of one of the original IBM System 360s. So you're talking about an eight-megabyte computer that took up a pretty big room. And that was considered a small machine at the time. But it was really the big evolutionary leap in the classical computing that IBM helped bring about in the 1960s. 18 months after that machine was built, you could put its entire set of memory into a shoebox, and it evolved, evolved very quickly. So talk to us a little bit about that evolutionary arc with quantum.

Padbury  

So I'll start by saying the, you know, the ideas for quantum computation they've been around for a number of decades. And all of these ideas build again on the principles of quantum mechanics. But what I think's interesting about technology is that as these fundamental ideas are developing, all it takes is the right ideas and the right needs converging at the right point in time for these ideas to really take off. And so I think for IBM Quantum, that was probably 2016. And a few years later, we put our System One on the cloud available for everyone to access today, and if you've seen the System One, If you've been to our labs, and you've seen the System, it's a beautiful machine, and we have the famous golden chandelier that brings all of the components together. But I think that the key here is that we were able to make it available to the general public. And so it takes a scientific problem to a real reality that people can interact with. And I'm always amazed actually talking to some of our researchers that were doing, you know, their PhDs maybe a few decades ago. And, again, they're working on all of these ideas but didn't necessarily have a machine that they could actually run their experiments on. And again, we have that opportunity today. So you know, anyone can access a quantum computer, they can run experiments, they can learn how quantum computing works. And so we're seeing huge numbers of people from all around the world accessing these systems. So the first systems we put on the cloud were sort of five or, you know, five and seven qubit devices. But today, we have 127 qubits, and we'll be introducing our latest 433-qubit device later this year. So we've made a lot of progress over the last few years. But of course, it's really important to keep in mind that we're still not quite at the big goal of achieving quantum advantage. So we still have some work to do there. 

Artigue  

And Richard, it's accessible through Python. You take a nonquantum person like me, and you gave me a very classical computing way to access this amazing technology.

Padbury  

Exactly. So the programming language, if you're familiar with Python, it's very easy to create an account, get online, and you can start programming today. So, Brad, you could start programming a quantum computer today if you wanted to.

Artigue  

You could say I'm not ready. But I did make it say hello, world. And that was a nice little experiment for me to perform. So Kristin, tell me a little bit about joining the quantum network. I mean, its quantum is mind-blowing on paper; a lot of the concepts we're talking about on this podcast today are really incomprehensible. 10 years ago, we weren't having these conversations. So can you give us a sneak peek at those sustainability use cases you've been working on? Or is it too soon to share?

Gilkes  

I love sneak peeks, Brad. So yes, let me pull back the curtain and share a little bit about what we've been doing at our EY quantum lab. All of these things will be released very, very soon anyways. So in keeping with the supercar racing theme, our lab has produced an energy demand planning quantum model, where we're harnessing quantum physics to support renewable energy, which can be used across several different industries, from the automotive sector, to the energy sector itself, we have also developed a portfolio optimization algorithm that can be used in the financial sector. But it's a little bit different; we've put a twist on it with a sustainability angle, where we're looking at providing a trading desk with a strategy to optimize for return, the portfolio risk, and then also for sustainability factors. So we're excited about that. We're also creating a transparent and green trade portfolio by adding that sustainability variable to that equation. But you know, I think you probably would have expected a lab of our scale to be researching those kinds of topics, right? Demand planning, portfolio analysis. So I think it's a little bit of a surprise for our guests listening who are passionate about solving the food crisis, the big sustainability problem that's out there. 345 million people in 82 countries, you know, have limited access to food. And that problem is unfortunately only growing. And so one of the things that our team at EY has been double clicking into, and we're using the IBM computers to help solve for is utilizing data output from one of our optimization models, to also leverage quantum sensors that are able to provide precise light the variables to critical vegetable crops that are growing in harsh environments. And that problem set, when you think about it, is that we are leveraging both the quantum mechanics in the quantum sensor to provide that precise light to grow the vegetable, but we're also using an optimization algorithm that has a call out to the quantum computer. So we are really trying to solve for this sustainable agricultural research implication.

Padbury  

It's absolutely amazing. For me working within the IBM Quantum Network, one of the privileged opportunities I have is working with partners like yourself on, you know, and learning about these creative ways that you're using these technologies to solve these problems. So as we're developing the hardware, it's really exciting to see how our partners are thinking about the problems out there that we can potentially solve with quantum computing. So this is really exciting to hear, Kristin.

Artigue  

Richard, on this note about IBM and EY working together on quantum computing. Is there anything else your team is starting work on with EY, and what other sustainability-oriented use case do you see emerge? Maybe there are some promising areas in materials development, for example?

Padbury  

Yeah, so you've touched on material science, which is a topic very dear to my heart since I have a background in material science. But before I go there, what I will say is that, you know, at EY, you're building a really great team; I think some 200 practitioners are actively learning how to program quantum computers. And so you know, from my side, I'm just really excited to see how some of the use cases that Kristin just mentioned, you know, just seeing how they evolve and how we can obviously support those developments. But on the material science aspect, that's certainly something I can speak more to. And from my personal experience, you know, there are materials that we've not yet discovered. But there are also materials that exist today that we've just, you know, perhaps we've not tested them yet for a certain application. But one of the biggest challenges we face is the time it takes to really develop these new materials for an application. So it can take anywhere from 10 years to maybe multiple decades to develop a new material, that's, that's ready for an application. So if we're, if we're trying to meet industry challenges in a timely fashion to meet some of these emerging challenges, we obviously need to speed that process up. And so I see quantum as a tool in the toolbox with the other technologies we have available to us to help in that process. And I think another important thing we should focus on is confidence and risk. So if I'm discovering new material, and I know I've got a lengthy process that I have to go through to get those materials approved for a ready-made product, I want to make sure that the material I've discovered is fit for that application. And so there's a huge amount of risk in that. And obviously, we don't want to get to the end of our process and find that we perhaps pick the wrong material. So again, I think for these big challenges and to speed up the development pathway, we need new tools. And I think, again, quantum is something that we can leverage that can really help us improve that development pathway. And I can, you know, discuss some of the areas that we're actively working on. But I think for me that the key is how we approach the problem. And how can we speed up the process? Because we do have some significant challenges out there that need to be addressed. 

Gilkes  

Yeah, you're absolutely right, Richard. And I think that's where our partnership is being leveraged, is our ability to write optimization algorithms is so applicable across so many different sectors. But that optimization process and the way you think about optimizing an equation is where we're going to see that lift of how you produce that supply chain that you're describing, of getting the material, getting the new drug discovery into the hands of the right engineers faster. And so shortening that supply chain length is key. And it all goes back to that demand planning and optimization algorithms that we're researching on your quantum hardware.

Padbury  

Exactly. And we're really excited to see what your team discovers and develops, and perhaps I can share some areas that we have been working on. So thinking about renewable energy and energy storage, we've been working on projects related to lithium-sulfur batteries, and you know, these batteries involve very complicated chemical reactions. And so we see potential in quantum computing, helping us to understand those chemical reactions more effectively, again, so that we can speed up that discovery process.

Artigue  

In speaking about quantum as a tool and quantum as part of your toolkit, there are a number of global efforts, from technologies to policies, to reduce emissions. So Kristin, how do you see quantum technology being applied to this topic as it matures?

Gilkes  

So we've talked about some of them, Brad, like the energy demand planning, but I think it's time to say that as quantum scientists, we are researching things that we can leverage today with classical computing. So think hybrid, right? The process that's 98% classical will have just one small call out to a quantum hardware, and we'll feed that back into the classical loop. So as our global society is rapidly searching for ways to reduce emissions, we're able to study battery optimization and material discovery so that perhaps one day, we can reduce emissions by introducing new materials. And being able to do all of that, I think it's important that we do not have to wait until there's a quantum advantage or this really, really large quantum computer that can handle all aspects of that very large problem. We can start making progress against those large problems today by utilizing this hybrid kind of approach.

Padbury  

I agree with Kristin here. And this very much ties into the next step in our IBM Quantum roadmap. So the next phase, we're calling quantum-centric supercomputing, very much ties into the fact that now and in the future, quantum computers will be working with classical computers. And so the next phase of our development roadmap involves all of the underlying technologies to actually bring classical and quantum together and get them communicating in a seamless, modular way. So that we can leverage the benefits of both. So you'll see more of this from IBM Quantum as well.

Artigue  

And look, I think quantum, these are very few computers in the world. They're installed in very specific locations. And they're only available to a select few. Right, Richard?

Padbury  

So you know, obviously, you're not going to have a quantum computer on your desktop anytime soon. But these systems are available over the cloud today. And, you know, they will be available, obviously, in that way in the future. And that does make them widely accessible. So as I mentioned previously, anyone can create an account and access these systems for education and research. And obviously, as the technology progresses, we hope to make that even easier for many more people to access these systems in the future.

Artigue  

And I was picking a little bit because what I know is you have close to half a million users worldwide on these quantum systems available through the cloud, and probably more using simulators and learning how to gear up in this technology. So it's a phenomenal tool but talk to me about ensuring some equitable spread. Avoiding geographic isolation and economic pockets. How do we get this technology into the hands of everyone who needs it? Versus everyone who can maybe afford to build and install one of these machines?

Padbury  

Absolutely. That's a great question. And from day one, we've taken the approach that we want as many people using quantum computers as possible. And so, as you mentioned, Brad, we have more than 450,000 users to date. And we do see an interesting split between, you know, the use of emulators that simulate the properties of the real hardware, but also a large number of users are really digging into the capabilities that we've provided and running interesting projects on our systems. And, of course, diversity, equity, and inclusion are critical to the success of quantum computing, now and in the future. So we are very proud of the IBM Quantum HBCU center. This was an initiative built from the ground up by my colleague Kayla Lee, with her close collaborators and support from IBM. And the goal of the center is to collaborate with HBCUs in a way that would not only advance quantum information science but also STEM-based opportunities for underrepresented communities. And so today, the center has directly engaged with 50 post-secondary students at HBCUs in research projects across fields like quantum materials, quantum chemistry, and quantum computing. And we've also worked with more than 80 HBCU faculty members who have participated in faculty development opportunities to serve as student mentors. And just to give you some more numbers, obviously, diversity, equity, and inclusion are critical to the success of the quantum computing ecosystem. And since 2016, when the IBM Quantum program launched, our investments in quantum workforce and education have resulted in, I think, over four million learners around the world who have built skills in quantum. We've got 374 plus classroom courses taught with IBM, quantum and Qiskit tools. So we're leading a number of initiatives to support DEI. We've also engaged the global quantum community with multiple quantum challenges, open science prizes, so we're really excited to support these initiatives and really hope that it helps us to drive quantum computing across many different communities.

Gilkes  

Richard, I think that's great, and at EY, we have a center for Neurodiversity. And one of the things that we've been able to do is focus on having 12 teammates from that center go through the EY-IBM Quantum certification. So I'm really, really excited about how together our two firms are really, really focused on driving diversity and inclusion. And we are really putting that into practice.

Artigue  

Richard, and Kristin, everything you talked about in the last topic was all about demand, demand, demand; we're getting more and more people involved and more interested. But we're talking about sustainability here. Data centers already account for about 2% of global power consumption. So how do quantum computers fit into that picture of data centers and their energy use?

Padbury  

I think the honest answer here is that it's very, very difficult to compare quantum computers to, you know, huge, huge data centers. So we've already talked a lot about how quantum computing is, you know, it's a different way of processing information to classical computers and HPC. It's certainly not an apples-to-apples comparison. And I think that's particularly true today because, obviously, technology is still developing and evolving. So I think what I would also say is it's perhaps important to understand that quantum computers are not necessarily more powerful than classical computers, certainly not yet in terms of their capability to solve problems that classical computers can't. But I think we also have to acknowledge, as we've discussed, that classical computers and quantum computers, they work together under the same framework. And so to deliver useful quantum computing, you know, we have to combine other technologies to make that happen.

Artigue  

Kristin, alongside the other technologies, such as AI, I mean, how can quantum be used along with these other technologies that minimize our future energy impact?

Gilkes  

Well, you're onto something there, Brad; the hybrid nature of where we are today, much of what we're doing, and what we will continue to do includes AI. So the EY quantum lab, we only have room to research a handful of these use cases. And I'm really proud that we included energy demand planning as one of those. There are so many uses for that one study; optimizing the routing of energy inside of data centers to reduce that carbon footprint is a big one. 

Padbury  

Yeah, I think I think that's really interesting. And as we're talking, you know, I'm thinking about a particular case study that we're working on with CERN. And so the amount of data that these particle accelerators pump out of that System is absolutely enormous. And you know, in a few years, they may have more data than they know what to do with and maybe more data than, you know, large HPC centers can handle. And so perhaps quantum can actually help in that problem by analyzing data using these fundamentally different ways of processing information. Maybe we can do new and interesting things with those very large data sets that perhaps we couldn't do before.

Artigue  

But no quantum computer is sitting on my desk anytime soon. I made space for one. 

Padbury  

Yeah, unfortunately not. But that's really noisy, Brad. So I don't think you'd want one too close.

Artigue  

Not too close to me. I've seen them. They're a little bit too big for my house, but they are here; they are in the cloud. They've hosted off-prem. What is the reality for users in getting into quantum technology?

Padbury  

Yeah. So I think, you know, the reality is that, again, just building on some of the points we've already discussed, it is very easy to get access. And as you mentioned, Brad, they're available over the cloud. So they are widely accessible today. And you know, I encourage listeners to check it out.

Artigue  

And we're using these systems today and have been for some time. Kristin, to what extent do you think this collaboration between EY and IBM can push the progress of sustainability research using these systems now that we have them when we're using them every day?

Gilkes  

Well, look at EY and IBM; we have some of the same core values as institutions. And we're solving some of the client's hardest problems to build a better working world, right? I had mentioned that earlier. And so the EY Quantum Lab's ability to execute these quantum models against the largest quantum computer on the planet, it's just a start to the benefits of our collaboration.

Artigue  

To give any listener an idea of scale, when we announced, it overloaded our inbox with requests from EY people to get training and how they get access. Curiosity drives innovation, and the curiosity around this is overwhelming. Every EY executive that I've had the pleasure of bringing over to our Quantum Centre has just been floored; you just sit down for a moment and take it in. It's truly amazing stuff. But before we wrap up, Kristin, Richard, can you give us some next steps? How should those interested in sustainability think about how quantum computing could fit into their research?

Padbury  

So as we've been discussing, the good news is that the barrier to exploring quantum computing today is very low from individuals to organizations. Obviously, these systems are not going to be sitting on your desktop anytime soon. But we do have these systems available on the cloud and plenty of educational resources to help anyone understand the technology. And as for organizations specifically interested in sustainability, the first step is to map the problems they're trying to solve to what a quantum computer can achieve. And this is where scientists at IBM and EY come in. So we work to match quantum expertise with domain experts to begin research and case studies. And hopefully, in the not-too-distant future, we'll be producing applications that deliver a quantum advantage.

Gilkes  

Yes, well said, Richard. The inclusivity and the availability of quantum it is here. So I'd like to just remind the audience, though, that you don't have to be a quantum scientist like Richard or me to get involved in quantum. The hybrid nature of the space is that we need to attract creative journalists, we need the digital ethicist, we need teachers, we need program managers, the computer software engineers to build all the middleware and the APIs to connect the data output, translate it to insight for everyday people. So we'll need a whole host of skill sets to facilitate this diverse and responsible growth of quantum technology.

Artigue 

Very well said; I mean, maybe people don't know. But the vast majority of computer programmers on this planet are not computer scientists. They are not doctors in microprocessors and assembler code and all of this stuff. Their programmers are writing code in the same languages that we use to access these quantum machines. You mentioned Python earlier. It's the language that you use to get to the systems. So mastery of a science of a very complex method to get into the systems isn't necessary, which is a brilliant approach to providing access to these computers. Look, Kristin and Richard, this was a fantastic conversation, and thank you for sharing your insights on quantum.

Before we go, a quick note from our attorneys. The views of third parties set out in this podcast are not necessarily the views of the global EY organization or its member firms. Moreover, they should be seen in the context of the time in which they were made. I'm Brad Artigue. I hope you enjoyed the show and you'll join us again soon for the next edition of the EY Think Ecosystem podcast.

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