We have a great crowd here today, and I know that we're live streaming this, and we're going to put it on YouTube. So, I want everybody at home to be able to hear how many people we have with us. So, you got to make some noise. Let's hear you.
I'm Alex Kantrowitz. I'm the host of Big Technology Podcast, and I'm thrilled to be here with Dr. Alan Baratz for a conversation about the cutting edge of quantum computing. Dr. Baratz, it's great to speak with you again.
Great to speak with you. You're making this sound so professional.
Got to get people into it. This is the way we enter.
Lot of news. Can you give us the highlights and what the implications are?
Yeah. So, first of all, not brand new news, but within the last couple of weeks we did announce that we have acquired Quantum Computing Inc., which brings revolutionary new gate model technology to D-Wave, and we believe accelerates us to the forefront of gate model computing alongside the fact that we're already the world leaders in annealing quantum computers, so making us the leading quantum computing company. We've also announced, as you just heard, that Florida Atlantic University has purchased a D-Wave Advantage system to be placed at their Boca Raton campus, just a little bit down the road, for use in workforce development, application development, new science, leveraging quantum computing here in Florida. We ann... What time is it?
We just announced that we have signed a new quantum computing as a service deal. It's a two-year, $10 million deal to work with a Fortune 100 company to basically build and deploy a collection of different quantum applications within their environment. This is the first large enterprise deal, I believe, ever for quantum computing, certainly for D-Wave. And it's something that I have been talking about for a while, that we were on the path to achieve this transition from small proofs of concept to large enterprise deals. And then, of course, we just announced that we are moving our corporate headquarters from Palo Alto, California, to right here in Palm Beach County, and we're really excited to be here.
Now, one bit of news that caught my attention is that you're announcing a partnership with Anduril, the defense technology company. All these different scenarios ran through my head of what that could be. Is it trying to find new types of weapons? Is it logistics? Is it simulations? What is that partnership going to...
So it's trying to help the US government and the Department of War solve their complex computational problems in support of national defense. So, you know, up until now the US government has been mostly focused on long-term research around quantum, but our annealing quantum computers are able to solve hard problems today, including hard national defense problems. So this is about working to really help address some of those hard problems leveraging quantum systems right now, today. And I think, you know, you heard from Dale and from Matthew that, you know, they were surprised at how capable our systems were, how much they are able to do right now, today, in addressing some of these challenging problems.
Now this is a moment where a lot of us are hearing, even those of us outside of the quantum industry, are hearing much more about quantum. Seems like every couple months there's a new announcement of a breakthrough or an application that seemed long away but is now possible. So talk a little bit about why quantum, why now, and why we're seeing this urgency around this technology at this moment.
Yeah. So first of all, I do think that we are at the point where there are hard problems that classical is not able to solve well enough. And these problems cut across a variety of different application areas. And in fact, you know, you saw one of the comments from Wakefield Research that 81% of executives think that classical is out of steam for solving the problems that are important to them. So there's an awareness of the fact that something needs to change in the compute environment to be able to solve these hard problems better and faster than they're being solved today. And quantum computing is the answer to that problem. I think the thing that has been less well understood, certainly not well recognized, is that quantum can address these problems right now, today, not three years, not five years, not ten years in the future, but right now, today. That's what our annealing quantum computers are capable of doing. So, as word is now getting out that quantum can solve your hard problems today, we're starting to see an acceleration in interest in actually leveraging that technology.
And give us some examples of what quantum computing can do that a classical computer could not.
Yeah. So, one of them... well, we need to divide the use cases into two different categories. I call them evolutionary use cases and revolutionary use cases. So you said what classical computers can't do. To me those are more revolutionary applications. There are applications where classical computers are solving the problems today, it's just they're not solving them fast enough or they're not solving them optimally. And so there's more business benefit, operational efficiency to be gained with better solutions. So our annealing quantum computers currently are primarily focused on those evolutionary applications, whether it's in the area of workforce scheduling, which is like what Alex Candella showed us, or in the area of manufacturing optimization, or protein folding. These are problems that are actually being solved today classically, just not well enough or fast enough, and our quantum computers can improve. Then there are applications that are beyond the reach of classical altogether. You can't even get near optimal solutions. You can't even get close. We demonstrated an example of that early last year when we showed that we could simulate properties of magnetic materials to aid in new materials design that could be done on our quantum computer in 20 minutes, but it would take nearly a million years on the fastest supercomputers in the world to perform those computations. So those are problems that, you know, can't even be addressed today. And there are others that fall into that category as well, some of the things I talked about before like global modeling, global design of drugs and so on.
Okay, let's go a level deeper on something you said, which is that this type of computing can be used for improved workforce scheduling. I think a critic might say, look, you can do pretty good workforce scheduling with classical computers today. Why do you need quantum to do this? So talk a little bit about what exactly quantum gets you that you would not get with a classical computer.
Yeah, I mean, let's just go back to the demo that Alex Candella showed, right? I mean, this is a problem of forward placement of emergency services personnel and vehicles. Now you might think that's a simple problem, right? Small number of, you know, service stations, small number of vehicles, small number of officers, but there's so many possible places they could be placed. There are interdependencies between the placements and, you know, servicing crimes or domestic disputes that it's a really hard problem. Leveraging our quantum computers, response time was cut in half, and that really does save lives. So this is a big, important deal.
All right, let's get into the technology. I mean, you've spoken before about the benefits of superconducting quantum computing, and I'd love to hear your perspective on the trade-offs between that and other approaches and where D-Wave's strategy fits.
Yeah. So, this is a big debate in the quantum industry. What's going to win? Is it superconducting from companies like D-Wave or IBM or Google or Rigetti? Or is it trapped ion from companies like IonQ or Quantinuum? Or is it neutral atom from QuEra or Pasqal? Or photonics from PsiQuantum or Xanadu? It's a huge debate that's going on right now. And the way the debate kind of unfolds, the superconducting proponents say, well, superconducting is a thousand times faster. It's just physics. And why would you ever want a quantum computer that's a thousand times slower? So, of course, superconducting is going to win. But then the trapped ion or the neutral atom proponents will say, yes, but our qubits are natural qubits — atoms, ions, photons — they have much higher fidelity, so it's going to be much easier to error correct. We'll be able to get to error-corrected gate model quantum computers much faster than superconducting. Maybe superconducting will never even get there. So that's kind of the way the debate plays out. But with the acquisition of Quantum Circuits, we just totally put that debate to rest. Because this dual-rail technology that Quantum Circuits has developed is absolutely revolutionary. It is transformational. We are talking about superconducting qubits. So it's the speed of superconducting, a thousand times faster than the other modalities, but it has the fidelity of trapped ions or neutral atoms, very high-quality qubits, making it much easier to error correct, much more efficient to error correct. So now, you know, in some sense, we've got the best of both worlds. Frankly, I don't know how the other modalities compete at this point because they don't have the speed that our qubits have. I also don't know how the other superconducting companies compete because they don't have the fidelity. Error correction is going to be much harder for them. This really does put D-Wave in a transformational leadership position.
You had the roadmap earlier up about how the dual-rail technology will continue to grow and eventually link together a bunch of qubits. So talk a little bit about what that enables at each stage, because I found that very interesting.
