Thank you.
Alan Dennis, thank you for being here.
All right. I thank you all for being here. Alan, I want to — I'll start with you. We had Pete Chadbot here yesterday from SC Quantum talking about his quantum computer. He wants to have one by 2029. I think you have one now. So I just want to help us understand the difference between, you know, these quantum computers that Google and others are building 10 years from now or whatever the number is, and what you're doing today.
Yeah. So there are two main architectural approaches to quantum computing. One is called annealing, the other is called gate. And I'm not going to get into how they differ, other than to say that annealing quantum computers are a much easier technology to develop. And as a result, we currently have annealing quantum computers that are in production. By that I mean we have customers in the aerospace industry, we have customers in the healthcare industry, we have customers in the telecommunications industry that are using our quantum computers today as part of their business operations to solve hard problems. Moreover, this is the only quantum computer in the world for which we've actually been able to solve a useful real-world problem that cannot be solved classically — true quantum supremacy.
The other approach, gate model, that's pretty much what everybody else in the industry is trying to develop. D-Wave is the only company that has annealing quantum computers, and those systems are many years away from commercial maturity. There are still some very hard technical problems that need to be solved in the areas of error correction, in the areas of scaling. So when you hear Pete talk about, you know, many years from now, or Google or IBM or IonQ, it's because that technology is still quite far away from commercial maturity.
Yeah. And you've made an acquisition on that. So you're doing both.
We do both. We're the only dual-platform quantum computing company. Our annealing systems are commercial today in production use. Our gate model systems, like everybody else in the industry, are still in the R&D phase. We still have some challenges that we need to address there.
Yeah. But Dennis, you're not in the quantum business.
Please do not ask me any quantum computing questions. It will be...
Okay, you can go. No, I'm just — so from where you sit, though, is this technology useful yet, or is it too early to even, you know, think about as a...
Well, I'm excited about it, and to be quite honest, we've just recently been having conversations about real-world applications and challenges that we're trying to solve. And so this is a learning journey for me as well, you know. And you think about AI and the transformation that that's making — quantum computing is now here, and there's different uses, different applications, hard problems. We're trying to solve operational problems every day. And how do we leverage these incredible technology capabilities? I mean, it's an exciting time to be alive. It's an exciting time to leverage technology in ways — I mean, we've already seen technology and how it's impacted the world. And I think we're like just getting started. I think we're — how can we be in the early innings of this? But that is where we are. And so, you know, we talk about operational matters of just making sure technicians get to where they need to in the right time, and identifying outages and issues. These are all real problems that, you know, we want to have conversations about.
Yeah. You know, Dennis, I've been hearing a lot in the halls around here about Claude Mythos, you know, the Anthropic model that's supposed to disrupt security.
Really interesting to see that be a big topic of conversation. Do you think — are you thinking about quantum as maybe a potential security solution in the network at all down the road? Obviously, maybe you're...
Yeah, you know, I started my career in cyber, and some of the elements of cyber from then still exist today, where, you know, there's the...
just the hygiene of patching systems and staying on top of patching, and being able to — you know, we're identifying issues every day, and how do we make sure that our teams have the capacity and the change management structure to be able to keep up with all of these updates that are happening. You know, it feels like non-stop. And so that's a great conversation: how do we leverage quantum now to be able to accelerate that? Because right now the biggest challenge is, hey, how do we keep up given the amount of vulnerabilities that we continuously see out in the wild? And one, we just have to have good hygiene, good program, good policies, education, and then how do we now leverage technology to make sure that we're staying ahead of it.
Do you, Alan, do you think that there's a possibility there? You can feel free to make your sales pitch.
Yeah. So, look, AI is great at some things. Quantum is great at some things. GPUs are great at some things. Nothing is great at everything. I think that AI's ability to kind of analyze things and draw conclusions based on what it sees is quite phenomenal. That's not the domain of quantum computers. Quantum computers are all about solving hard computational problems. So, you know, if you need to optimize a production schedule in a chemical plant like we're doing with BASF, that's quantum computing. If you need to predict supply, that's AI, right? So I think, you know, we need to understand that these technologies are each good at solving different classes of problems.
Yeah. And on the optimization front, is it a question of just faster optimization, or is it also a different result?
Yeah, it's faster and better in the sense that, you know, it's interesting — you know, most people will say production scheduling that's happening today, or, you know, manufacturing plant floor optimization, workforce scheduling, we're doing that today. But the interesting thing is these problems are what we call exponentially hard problems. What that means is that the cost of compute required to solve the problem optimally, to get the best possible solution, grows exponentially in the size of the problem. So after you get to even, you know, medium-sized problems, you're outside of the range where classical computers can actually provide the optimal solution. So companies are basically using heuristics. They're simplifying the problem. They're using heuristics to try to come up with what they hope are good enough solutions, and that's what's being used today. Quantum computing can come in and basically not only deliver the solution faster, but get you the optimal solution. So now you're getting better solutions faster.
Yeah. Dennis, I want to ask you about — just on an AI question here. There's this massive buildout happening on the infrastructure side with data centers and AI. Do you think we need something similar on the broadband side, whether that's, you know, fiber or something else?
Yeah, we've been investing heavily in the network, in fiber, in reliability, in availability. You know, when we talk to our customers, consumer and enterprise folks want more than ever quality, reliability, availability, and our ability to now use AI to be able to proactively identify when there's an issue, respond effectively, respond faster, and really ensure that we are making that network as hardened as possible is absolutely one of the things that we've been looking at. But then we're also looking at how does it evolve our product set? How does it evolve our go-to-market? How does it evolve the CPE that's sitting in the home? And now that we're at the edge in the house or in the business, what's the opportunity set there? And what are the needs that customers have? I think we're just in the beginning phases of what the applications are that we need to be able to support and unlock. And first and foremost, we need to make sure that we have the fastest network that it's able to handle whatever these applications are that are coming about. And so we're continuously monitoring and having these conversations with our customers to position the network appropriately.
Right. I mean, like, I think about the, you know, people at home using OpenClaw now and these agents, and they're sending information back and forth across the network. Does that require faster connections, or, you know, down the road in the future, do you think? Or are we already kind of there because we're doing 4K video and stuff?
Well, that's the interesting part. We, you know, we've got more video conferencing happening, more downloading, 4K video, and so it's more important than ever in terms of download speeds and upload speeds. You know, is AI today using a disproportionate amount of capacity in line with these types of applications? Not today, but I can tell you that every year the consumption grows by 10, 20, 30%, and that's been happening year after year after year. And I can only imagine that this introduction is going to continue that trend — it's not going to bring it down. You know, if I could imagine all the applications, I would be doing some other job. But I will make sure that our network is ready so that those that are creators, those that are, you know, got their hands on this thing, have the ability to unlock whatever magic that they're trying to create. That's our job, and that's what we're committed to.
Yeah. Alan, on the AI side, the data centers are causing all sorts of shortages now — not just silicon, but memory, and, you know, there's energy shortages. Do you think something like that is going to happen in quantum as we sort of ramp up the...
