Filed by D-Wave Quantum Inc.

Pursuant to Rule 425 under the Securities Act of 1933

and deemed filed pursuant to Rule 14a-6

under the Securities Exchange Act of 1934

Form S-4 File No. 333-263573

Subject Company: DPCM Capital, Inc.

(Commission File No. 001-39638)

ICR Webinar – 7/18/22

Kevin Hunt: ... everyone to ICR SPAC webinar series. My name is Kevin Hunt and I am a managing director in the ICR tech investor relations group. We are very excited to have D-Wave with us today. D-Wave is a truly disruptive technology company, a pioneer in the development of quantum computing, and the only company that is today delivering commercial class quantum computing. On our call today, we have D-Wave’s CEO, Alan Baratz. Alan has a long history in commercializing innovative technology that he brings to D-Wave and the quantum industry. Our format today will be a fireside chat Q&A session. We encourage audience members to submit questions to the chat function of the webinar, and we will do our best to get to as many questions as possible. Monitoring today’s session, we are pleased to have David Williams of Benchmark, who covers the semiconductor space in addition to all the major pure quantum play companies, the broadest coverage of quantum on Wall Street. David, thank you for joining us today and I’ll now turn things over to you to get the discussion going.

David Williams: Kevin, thanks so much. Certainly appreciate it and glad to be here today. Alan, as always, it’s great to talk with you and I love the platform at D-Wave and I think you guys have done a very good job on the commercialization front. And I guess with that, can we start maybe with a little deeper of your background, because I actually think it’s quite fascinating, but just a little bit of your background maybe and then we’ll go into a company overview?

Alan Baratz: Thanks, David. Happy to do that. And thank you for taking the time to be here today and have this conversation. So as Kevin and David said, my name is Alan Baratz and I am the CEO at D-Wave. I joined the company about five years ago, originally to run R&D. And I took over as the CEO of the company a little over two years ago. And over the course of the last few years, we’ve made an enormous amount of progress at D-Wave. And I’m happy to have the opportunity as we go through the discussion today to tell you about that.

If we go a little further into my background, I was the first president of Javasoft at Sun Microsystems. So I was responsible for bringing that technology to market, growing the revenue, building the developer ecosystem. A lot of the things that I did there are similar to what I’m doing now at D-Wave, as we’re creating a new industry for quantum and building a new ecosystem here. I’ve also been a senior executive at a number of other large companies. I was responsible for all products at Avaya. I was responsible for all software at Cisco. I’ve been a private company CEO three times prior to D-Wave. I sold all three of those companies. The last one I sold to Cisco, which was how I ended up there. And I’ve been a venture investor. I was a managing director at Warburg Pincus and I opened their first Bay Area office. So I’ve had an opportunity to see the tech industry from the big company side, from the small company side and from the venture investing side.

Educationally, I have a PhD from MIT in theory of computation. So while I’m not a quantum physicist, I’m pretty good at holding my own at our spectacular R&D team.

David Williams: Yeah. You do a very good job of simplifying things as well, I think, especially with the background there and I can appreciate that in your ability. So thanks for the overview and much appreciated. I guess, as you kind of think about D-Wave and where you’re positioned today, how do you think the market develops over time specific to maybe what you’re doing and maybe the annealing approach versus some of the gate models? But maybe just a little bit about how you’re seeing that market develop.

Alan Baratz: Yeah. So thanks for that question, David, because there’s a really important point that needs to be made here. And that is that there are two primary approaches to quantum computing. There’s annealing quantum computing and there’s gate model quantum computing. And what we now know is that different applications will run better on each of those architectures. So there are certain applications like optimization that will deliver a significant speed up on a annealing quantum computers, but not on gate model systems. And there are other applications like quantum chemistry or computational fluid dynamics, where you can get a significant speed up on gate model quantum computers, but not on annealing quantum computers. And so what that means is that you will always need both annealing and gate in order to be able to address or deliver speed ups across all application sets.

Now, currently, there is only one company in the world that provides annealing quantum computers, and that’s D-Wave. We’re the only company in the world that provides annealing quantum computers. And as a result, we’re the only company in the world that can address the applications that are well suited to annealing. That’s optimization applications, things like employee scheduling, or autonomous vehicle routing, or anti- money laundering. These are frankly, most of the important computationally hard problems that businesses need to solve. And only annealing can address them. And as a result, only D-Wave can address them. That means there’s a very important portion of the market that’s available to D-Wave only.

On the gate model side, there are many players and many technological approaches that are being pursued by these players. And I think the jury is still out with respect to which technologies, which architectures and which players will be the winner or the significant providers in the gate model space. Of course, now D-Wave is one of those players as well, because in addition to our annealing quantum computers, we are now also building gate model systems, which means we’re the only company in the world that’s pursuing both annealing and gate. And as a result, we’ll end up being the only company in the world that can address the full market for quantum.

And let me make one last point, and that is, with our annealing quantum computers, we are commercial today. So with respect to the kind of evolution of the quantum marketplace, annealing and its support of optimization problems, that’s commercial today. We have over two dozen, global 2000 customers working on real business applications to benefit their business operations. In fact, just today, we announced an important partnership with MasterCard to address a number of their important application areas. However, with gate model systems, we’re at least seven years away from being able to support real business applications at commercial scale.

So you always need annealing for optimization problems. You will always need gate for quantum chemistry, computational fluid dynamics. Annealing is commercial today. D-Wave is the only company in the world that does that. We are at least seven years away from commercialization of gate model systems. D-Wave will be one of the players in that space.

David Williams: Very good. And maybe walk us through why that is. Why is the annealing better for optimization? Why is gate model better for other questions? I think that’s very interesting, just in that approach and those application areas. So if you could help us understand that.

Alan Baratz: Sure. So let’s start with annealing. Annealing quantum computers do only one thing. They solve only one problem. That problem is finding the lowest point in a multidimensional landscape and they use quantum mechanical effects like superposition and entanglement and tunneling to be able to find that low point very quickly, much faster than classical computers can solve that task. But what’s very interesting about that particular problem, finding the low point in a multidimensional landscape, that is a very hard optimization problem. In fact, it’s one of the hardest.

And what that means is that any optimization problem, the kinds of problems that I mentioned a few minutes ago can be easily mapped into that problem, namely reformulated as that problem. So whatever optimization you have, you can easily reformulate it as that low point in a multidimensional landscape problem. And then the annealing kneeling quantum computer can solve it and it can use quantum mechanical effects to solve it faster than it can be solved classically. So that’s what makes annealing quantum computers very good at solving optimization problems. Moreover, because programming an annealing quantum computer is simply reformulating your problem, it’s fairly easy to program annealing quantum computers.

And finally, annealing systems are much less sensitive to errors than gate model systems. And that’s why we have commercial quantum computers today that are able to deliver good, if not optimal solutions to hard optimization problems today, without the need for full error correction. Gate model systems are quite different. You program a gate model system more like you program a classical computer, where you need to specify the sequence of instructions needed to solve that problem. However, those instructions are very complex, linear algebra and quantum physics gates. And as a result, there’s a very steep learning curve associated with programming a gate model system.

Moreover, gate model systems are very sensitive to noise and errors. In fact, without error correction, it’s likely that you will not be able to solve any real world problems at commercial scale. And that’s why I say that we’re seven years away from commercial gate model systems, because there are many hard fundamental technology problems that still need to get addressed, particularly in the realm of scaling and error correction before a gate model system will actually be able to do anything useful.

David Williams: Okay. Very helpful. And I also think it’s interesting that you have a 5,000 qubit system today deployed. Your 7,000 qubit system is in early development state or in early prototype sampling, but that’s a big difference between what we see in the gate model system. How are you able to get to five to 7,000 qubits versus some of the gate model systems?

Alan Baratz: Yeah. So first of all, annealing is an easier technology to scale. The qubits are not quite as sensitive as gate model qubits. The required coherence times are not quite as long as for gate model systems. And so they’re easier systems to scale.

Moreover, at D-Wave, we’ve been working on these systems for over 10 years. Our 5,000 qubit processors are our fifth generation system. And we’ve had to solve a number of hard fundamental research problems and address a number of very challenging engineering problems in order to get to this point. For example, we’re the only company in the world that has control of the qubits on the same chip as the qubits.

Now, this is required for a variety of different reasons, but it’s very challenging because you worry about interference between the control electronics and the kind of sensitive quantum nature of the qubits, but we’ve been able to solve that problem. We’ve been able to manage the crosstalks so that the control electronics does not undermine the quantum characteristics and capabilities of the qubits. So in addition to the fact that annealing is an easier technology to scale, we’ve also solved many hard fundamental problems to get to the point where we have a 5,000 qubit processor.

And by the way, look, as I said, it’s taken us over 10 years to get to this point. Gate model systems in that sense are still in their infancy, right? The earliest of the companies really trying to pursue a gate model system didn’t even start till about four or five years ago, right? So even if the technology was the same as annealing, I’d expect they have another five years ahead of them, but gate is more challenging. That’s why I say seven or more years.

David Williams: Okay. And you use the superconducting modality as well. So I think that’s more mature and more well understood versus photonics or some of the others. Can you talk maybe a little bit about superconducting specifically, and that’s your annealing approach, but also your gate model system is developed on superconducting as well?

Alan Baratz: Absolutely. So yes, we do use superconducting technology. We are strong believers in superconducting, not just for annealing, but also for gate model systems. And let me tell you why I say that. There are lots of pros and cons associated with superconducting versus trapped ions versus photonics versus NV centers. And there are many different technologies that are being investigated right now for gate. But the reason why we believe in superconducting is we are always very practical. We’re always looking at the commercial applications and what’s required to support a real world commercial application.

So let’s take the application that most interests and excites everybody on gate model systems, and that is Shor’s algorithm for breaking RSA, for basically factoring large semi prime numbers. Well, there’s a lot of research that’s been done on what will be required in a gate model system in order to solve that problem. So what we now know is if you want to factor a 2,000 bit semi-prime, which is currently state of the art for RSA, if you use superconducting technology, it’ll take about 20 million qubits and about eight hours to factor that number.

Now let’s just think about this for a minute. 20 million qubits. The largest gate model systems we have today are 50 to a hundred qubits. So even if you double every couple of years, we’re 20 years away from that. Okay? But nonetheless, superconducting, about 20 million qubits and about eight hours to factor that number.

If you want to do that same thing on an ion trap system, it’ll take about a billion qubits and about a third of a year, on the order of a hundred days, to factor that number. Photonic systems, it’ll take also about a billion qubits and a full year to factor the number. So why is this?

Well, the reason is that if we take for a minute superconducting versus ion trap, what you don’t often hear about is the gate speeds. The time it takes to process a gate or process an instruction on the gate model system. With super conducting technology, gates run in about 20 nanoseconds. In ion trap systems, it takes about 500 microseconds. So the gates are a thousand to 10,000 times slower on ion trap systems than on superconducting systems. So that right off the bat explains the difference in eight hours to factor the number versus a hundred days to factor the number.

But there’s more to it than that, because while you’ll hear ion trap and photonic people say, “Yeah, but we have more perfect qubits. Ions are more perfect, and so you don’t have to work as hard to do error correction.” It’s true. They are better. Better, well, let’s say more perfect qubits. But they’re not a thousand to 10,000 times better. Right? And that’s the reason why, when you factor in all of the elements required to get to a commercial gate model system, we absolutely believe that superconducting is the best path to pursue.

And we’ve got a lot of experience with superconducting and a lot of fundamental technologies that we have developed for our kneeling superconducting computers that we believe will be directly applicable to gate model that our competitors haven’t even started working on yet. And we think that’s going to allow us to move a bit more quickly even in the gate model space.

David Williams: Okay. And jumping around a bit here, and I’ve several additional questions on the technology, but want to make sure we get to everything, at least the more important aspects, but your revenue mix is a lot different, I think, than most of your peers’, in that about two thirds of the revenue is driven by your actual commercial business class customers.

Can you talk a little bit about that? How you’ve been able to achieve that, but then also the launch platform and the different mechanisms you have to help really drive that forward longer term?

Alan Baratz: Sure. First of all, that’s absolutely correct. In 2021, about two thirds of our cloud service, our quantum compute as a service revenue came from commercial customers. So while everybody else in the quantum industry talks about government research grants as revenue, and they talk about national labs and academic institutions as customers, we have over two dozen global 2000 companies that are our customers. So we talk about MasterCard, where we just announced a strategic relationship today, or Johnson & Johnson or GlaxoSmithKline, or Bank of Canada, or DBVA or Volkswagen or DENSO.

These are all customers, and these customers are all working with us on real business applications. Everything from employee scheduling to eCommerce, grocery delivery to bin packing for improving shipping logistics, to loyalty programs for offering programs to customers that are most likely to say yes to participate in these programs. These are all real world business applications. They all happen to be optimization applications that we are working on with our customers.

And the reason why we are at this point is first of all because we have a quantum computer that can support it. Right? I mean, we’re the only company in the world that has a quantum computer that today is able to support business applications at commercial scale. And we do that through our Leap quantum cloud service.

So in fact, we own our own cloud service. It’s called Leap. We think there are very important reasons why you should own your own cloud service, which we can talk about in a few minutes, if you’re interested in going down that path. But our customers access our quantum computers and our hybrid solvers, because we are also strong believers in hybrid. Bringing classical compute together with quantum compute is the best way to solve these hard problems.

So we have a commercial quantum computer today. We have a commercial quantum cloud service. Our quantum cloud service includes hybrid solvers for bringing together quantum and classical. These are all reasons why we are able to support business customers and business applications. And so these are all things that have allowed us to get to this point.

Now, how do we engage with our customers? You asked a minute ago about the model. We have what we call our launch program, our D-Wave launch program, which is a four phase engagement model for working with our customers. In the first phase, we basically help our customers to evaluate their applications, to understand which applications can most benefit from our quantum computers. We typically will charge $50,000 for a two month engagement to do the application evaluation.

Second is a proof of concept phase. We will actually build a proof of concept of one of those applications for our customers. Now we will typically charge about $350,000 for a five month engagement to build out the proof of concept. Our third phase is a pilot deployment where we help our customer bring their application up in their environment on a small scale as a pilot or a test deployment. Once again, we’ll charge about $350,000 for a five month engagement.

And then once we are through all of that, the customer can move the application into full production. This is where they are using the application to help improve their business operations. We’ll generally charge between $500,000 per year and a million dollars per year per application, where the price we charge depends on the size, the complexity and the frequency with which the application needs to access the quantum computer.

Now, in addition to that launch program, we also have go to market partners that will help us to engage customers. And in some cases they’ll do some of the heavy lifting with respect to helping the customers build out their applications. So these are basically go to market partners, channel partners, professional services companies that can kind of extend the reach for D-Wave.

David Williams: Okay, great overview there. Certainly appreciate it. And I want to remind everyone in the chat room that if you have a question, feel free to enter that over to the side and we will get to those questions, but feel free to do that. I know there’s a lot of questions we’re not going to cover. So feel free, please, to ask those questions and we’ll get to those.

And Alan, I wanted to also mention, which I think is really interesting, but I had an opportunity to get onto the leap system and run through, really try to investigate, and there’s a tremendous amount of information there. But can you talk about the importance there, and that physically, anyone can go and run quantum computing algorithms on your system, and that’s the simplicity that you’ve made it? Which I think is a very important aspect of this.

Alan Baratz: Yeah. Yeah, thanks for asking about that. Absolutely anybody can go sign up for a Leap account. If you go to our website dwavesys.com and click on Leap, takes about 30 seconds and you get basically unlimited access to all of the resources in the Leap account, with the exception of the quantum computer and the hybrid solvers.

So you get unlimited access to all the learning materials. You get unlimited access to all the documentation. You get unlimited access to our integrated developer environment. We have a full integrated developer environment in Leap, so you can build your applications right there. You get unlimited access to our support section. The only thing where we limit access is when you actually go to run an application, either through the hybrid solvers or the quantum computer. You get a minute of free time for actually running your application on the hybrid solvers or the quantum computer. But a minute of free time is actually quite a bit of free time for the quantum computer.

You can run between 400 and 4000 jobs on the quantum computer within that minute of free time. Moreover, if you’re willing to open source the work you’re doing on Leap, then you can renew that minute every month. So you can get a minute of free time per month.

So anybody can get a Leap account that will give you unlimited access to all of the really strong educational learning training materials inside of Leap, the ability to build applications, and then that minute of free time on the quantum computer and the hybrid solvers. Now, obviously if you need more time or if you want to do work that’s proprietary to your company, then you buy access to the Leap cloud service. You can do it either through the launch program that I described a few minutes ago, or if you want to do it all yourself, you can just buy time on the system, as much as you need to build and run your applications. Now I’d also just like to take a minute to talk about why I think Leap is so important to D-Wave. Most of the other companies in the quantum space, at least the quantum computing companies, those building quantum systems, are relying on others for the cloud service. They’re either relying on AWS with their Braket service, or they’re relying on Azure with Azure Quantum or Google.

And so basically they kind of let those companies go out and do the customer acquisition and provide the tools and give their customers access to the backend quantum computers. So in that sense, our competitors don’t really always even know who their customers are. They don’t always know what their customers are doing with their quantum computers, whether they’re being successful or having problems.

Well, with us, we think it’s really important that we have the ability to manage that customer journey, to engage with our customers, to understand what they’re doing, what’s working, what’s not working. To learn from their use of the system so that we can improve and we can provide them feedback. And that’s why we think it’s so important to have our own quantum cloud service.

Now, you can access our quantum computers through AWS Braket as well. However, when customers really want to start digging in and doing more than just some research experimentation, they’ll typically come directly to D-Wave to get access directly from us on our Leap system so that we can help them to be successful.

David Williams: Okay. And can you talk a little bit, I know that others have talked about the cloud access and you mentioned it a little bit there, but maybe speak to the importance of having your own cloud and what the relevance of that is with your customer specifically?

Alan Baratz: Yeah. So as I said, this is really all about, A, making sure that your customers are successful with the use of your products, and B, learning from their experience so that you can always improve.

Commercial is very important to us. Right? We’re all about commercial. Look, we have a multi-part strategy where we like to say that our strategy is to build the business and advance the science and technology through a virtuous cycle. Right? And we’re always as focused on the business and the customers and their use cases and making them successful as we are on advancing the technology and the science, and those two go hand in hand.

With your own cloud service, that’s the only way you have the ability to get that direct access, to influence their journey, to help them be as successful as they can be, as well as to learn from them. So that’s why we are loath to cede ownership of the customer over to a third party.

David Williams: Nvidia’s had some efforts recently in creating classical quantum computing platform to help accelerate those development efforts. I think it lends at least validation to the quantum efforts. But, how do you view this? And is that a benefit? Is it a challenger? How do you see what NVIDIA’s working towards versus-

Alan Baratz: So, look. I don’t want to comment on NVIDIA’s work, other than to say that from everything I’ve seen, this is hybrid for gate model systems. In other words, it’s leveraging the NVIDIA processors as the classical part of a quantum classical hybrid solver, where the quantum part is gate model. We have also developed hybrid solvers. We launched our first hybrid solver a couple of years ago. We call that our binary quadratic model solver. Basically, it provided support for problems with binary variables, variables that could take on the value zero or one. Then we launched our discrete quadratic model solver for problems that had variables that could take on discrete values. For example, one of the colors from the set, red, green, yellow, blue. And then very recently, we launched our constrained quadratic model solver with continuous variable support. And what’s really important about the constrained quadratic model solver is that A, it allows us to support both integer and continuous variables.

This is the first time that continuous variables can be supported on a quantum computer. And so we can support mixed integer programming problems, which is really what many data scientists and data analysts use to solve their hard computational problems. Second, when we launch the constraint quadratic model solver, we raised the level of abstraction for those data scientists and data analysts. So, now programming the quantum computer can be done in the language they understand, basically specifying the constraints and the objective function in a symbolic language. So, hybrid is very important to us. And we use NVIDIA GPUs, frankly for the classical part of our hybrid solvers. It’s just that the quantum part is our annealing quantum computer rather than gate model systems.

David Williams: Yeah. Very helpful. Thanks for the color. And then maybe from an economics perspective, if you think about what the economic benefit is to your customers in quantum computing, what are they achieving? And maybe if you can kind of give us, kind of size it up, maybe a magnitude of what they’re hoping to achieve.

Alan Baratz: Yeah. So look, at the end of the day, it’s all about solving their computationally challenging problems better and faster than they can solve them today to able to improve their business operations. So, the interesting thing is that the optimization problems that most businesses need to solve today, and in fact, as I’ve already said, most of the important hard problems that businesses need to solve are optimization problems, these problems are so hard that today, classical compute will not solve them optimally. And so what businesses typically do is they come up with heuristics to try to get good enough solutions, or what they think are good enough solutions. So, the problems are so challenging that you can’t solve them optimally classically, so you use heuristics to get what you think are good enough solutions. However, with quantum computing, in many cases, we can get the same solution that they’re getting classically faster, or better solutions, in fact, in many cases, optimal solutions. And what this does is it allows them to improve their business operations.

So, think for a minute about bin packing for shipping logistics, right? So, you’ve got boxes that need to be packed into containers for shipping. And they’re different size boxes, and you want to pack them so you can get as many boxes as possible into each container. This is a very hard optimization problem. And in fact, the heuristics that are being used today are okay, but they’re not great. In fact, if you go to our leap cloud service, we actually have a demo of this, where you can pick a number of containers, pick a number of boxes, pick random sizes for those boxes, and then try to solve it classically using what most customers use today versus quantum. And you’ll see that when you try to solve it classically, there are many fewer boxes that can go into containers than when you solve it using our quantum hybrid solutions. So, denser packing, fewer containers, improve shipping logistics, lower cost, right? And this story plays out over and over again for different customers in different industries, with different applications.

David Williams: And you’ve kind of talked about, Save-On-Foods and the work that you’ve done there. They’ve kind of worked through that first in production, and now they’ve come back for a second one. But as you kind of think about the benefits that they’re able to achieve with that, are you seeing others that understand those economics, that understand the benefits, and that those are compelling enough to help move them into the quantum cloud?

Alan Baratz: So, yes, but the only caveat is it’s still early days. I mean, keep in mind, we did not have a quantum computer that could support business applications at commercial scale until we launched our 5,000 qubit system at the beginning of last year. At that time, we also introduced our D-Wave Launch program, that four phase engagement model that I described to you, where in fact, even if you add up the timeframes, two months for evaluation, five months for proof of concept, five months for pilot deployment, it’s a year to get to the point where you’re ready to move into production. So, we’re just now at the point, a year after introducing the launch program, where we’re starting to see things move into production. I think, over the course of the next year, as more applications move into production, as more applications become referenceable, the value proposition will become more and more clear across the board. Look, we just today announced our partnership with MasterCard, pursuing not one application, but several different applications that are important, really important, hard problems that MasterCard needs to solve.

David Williams: Very good. And what I really find interesting is that there is such a complete ecosystem that you’ve developed from beginning to end in terms of using the D-Wave platform. But I guess as you kind of look through your different solvers and your different applications, your software packages, will there be opportunities at some point, do you think, to monetize those specific versus just really driving and helping bring customers into the ecosystem?

Alan Baratz: So, I’m not sure I fully understand the question, but we are vertically integrated today on our annealing platform. We kind of have to be, because we’re the only company in the world that does a kneeling, right? So, we do the quantum computers, we do the software development tools, we do the hybrid solvers for annealing, we do the quantum cloud service. So, kind of breaking that apart would be hard, because if we pulled out the hybrid solvers that are designed to use classical with annealing, but it’s not targeting our annealing quantum computer, whose quantum computer is going to target? Because nobody else does annealing, right? We’re the only company in the world that does it. So, I think in the annealing arena, we are vertically integrated by necessity, but it’s also been really important for us, because quantum is early enough in its lifetime that you really do need to build all of the pieces together so that you can kind of carefully think through the trade offs with respect to what functionality should be done where.

So, the fact that we’re the only ones that do annealing and we had to build the full stack, I actually view as a good thing, right? That’s worked out extremely well for us, and we’ve got a very powerful stack. Now, by the way, sometimes I get asked, “Well, Alan, if annealing is so powerful and solve such important problems, aren’t you worried about other companies kind of jumping into the annealing space?” And the answer to that question is, well, yes, I think it will happen. Worried? No. The reason why I’m not worried is because we’ve got over a 10 year head start on annealing, and we’re not standing still. We continue to enhance our annealing quantum computers on an ongoing basis, always increasing the number of qubits, increasing the connectivity, reducing the noise to continually solve larger and more complex problems faster. Moreover, we own all the key intellectual property for all our products. We have over 200 US granted patents, and over a hundred in process worldwide.

In fact, in 2021, we are in the top five for quantum patents alongside IBM, Google, Intel, and Northrop Grumman. So, in addition to that very significant head start we have on annealing, we have a pretty significant patent moat in the annealing space. So, I think annealing is ours for quite some time to come. Now, gate model, lots of players, and we’ll be one of them, but I actually think that all the work that we’ve done in the annealing space is going to benefit our gate model program and allow us to move fairly quickly there as well.

David Williams: Okay. And we didn’t get a chance to touch on that yet, but I wanted to turn it back over to Kevin for a few minutes and run through some of the customer questions that we’ve received here. So, I’ll let you do that. And then if there’s some time available at the end, maybe we can come back.

Alan Baratz: Okay. Sounds good.

Kevin Hunt: Yeah. Thank you, David. Yeah, we do have a handful of questions from the audience. The first one I think builds off some comments you’ve already made, really, I guess say in the R&D area and how much leverage you get from your annealing program to develop your gate model system.

Alan Baratz: Yep. So, first of all, I do want to say that having the, annealing program, and now adding the gate model program, gives us a very important first mover advantage in the marketplace, right? Because we’re out there in the market to date commercial with our annealing quantum computers, building customers and customer loyalty. And as we bring out more advanced annealing systems that can support larger applications, it’s an upsell. As we bring out our gate model system, it’s an upsell. So for us, it’s all about upsell. For everybody else, it’s about customer acquisition. So, that first move of advantage, I think, is very important. As far as the technology benefits in going from annealing to gate, there are a number of very hard research questions we’ve had to answer and engineering problems we’ve had to solve in building our annealing quantum computers.

So, right at the very beginning, qubits, right? So, we do use superconducting technology, but everybody in the gate model space is using what’s called transmon qubits. These are voltage controlled qubits. Our annealing quantum computers we’re built using flux qubits. They’re controlled by magnetic flux and current. There are a number of really important advantages to flux based qubits. For example, with transmon qubits, you need microwave control lines. These are very costly and very difficult to manage. With flux based qubits, you can control them with much slower control lines, less costly, easier to manage. So, our gate model qubits, they won’t be identical to our annealing qubits, but they will be flux qubits. They will be controlled by magnetic flux, so we’ll get all the benefits of the flux based qubits in the gate model program. And we kind of have a lot of IP built around that technology.

Second, we fabricate our qubits using a multilayer fabrication process. Pretty much everybody else fabricates qubits directly on the platinum on the wafer. We have multi-layer qubit fabrication. This is what allows us to get the density that we have today. That’s why we have 5,000 qubits when everybody else has about 50 or a hundred qubits. This is very challenging, because being able to fabricate multi-layer qubits, and at the same time, manage the noise and keep high coherence time, very challenging part of what we’ve had to do with our annealing program. Next, we do have control on the same chip as the qubits. Again, very challenging, because you need to ensure that the crosstalks between controlling qubits are managed, and we’ve been able to do that. And the reason why control on the same chip as the qubits is so important is, first of all, when you are fabricating 5,000 qubits on a chip, the operation, the parameters, the operating parameters for each qubit is highly sensitive to the fabrication process, and even small variations in the fabrication process across the chip can cause the qubits to perform slightly differently from one another.

However, in order to have a quantum computer, those qubits all need to perform identically. And so what that means is that you need to design and build qubits where you can read parameters and tune those parameters to homogenize the qubits. We’ve got a lot of intellectual property around how to do this, but you need the control on the chip to be able to aid in that process, to be able to help read out those parameters, and then set the tuning elements to homogenize. The other reason why control on the same chip is so important is because that gives us addressing and pipelining.

That’s why we are able to control a 5,000 qubit processor with only 200 I/O lines, whereas everybody else has one I/O line per processor. These are technologies that we’ve had to develop for our annealing quantum computer that are going to be required for gate model systems.

Our competitors haven’t even started working on this yet, and we’ve got these technologies in hand. That’s some of the reason why I think we’re going to be able to move a bit more quickly on the gate model side.

Kevin Hunt: A quick follow up to that really as it pertains to software development tools. Is there leverage between annealing and gate there as well?

Alan Baratz: That’s a really interesting question that currently, honestly, I don’t know the answer to, in the following sense. What I do know is that we will be working hard to ensure that our tool suite, the name of our tool suite is Ocean, which currently targets our annealing quantum computers and annealing hybrid solvers, we will be extending Ocean to support gate model systems as well.

We’ll be providing a more unified programming environment for whether you’re targeting annealing or gate model on the backend. The question that I’m occasionally asked is, “Do you see any applications where there’s value to using an annealing and gate model system together to solve that problem?”

That’s a really interesting question. We know that there are problems that require annealing, and we know that there are problems that require gate. We don’t yet know if there are problems that can benefit from both working together. That’s the sense in which I say we don’t yet know the answer to that question.

Kevin Hunt: Then you had mentioned a bit earlier about your commercial customers. We got a question about how many customers have made it from entering the program to actually going into a production environment. Then a follow up to that is what your contracts look like.

Are they multiyear deals? Any color you can provide there.

Alan Baratz: First of all, as I said a few minutes ago, we’re still in the early stages of the launch program. We didn’t even introduce that till we got our 5,000 qubit system at the beginning of last year. We’re only a little over a year into the launch program.

Yes, the first of the customers that entered the launch program are moving into production now. It’s small, but it’s a very important starting point for us. What I can tell you is that when we built our five-year financial model that, I think, you can find in our investor presentation, we assumed that of every 10 customers that went into phase one in the launch program, only two of them made it through to production.

However, since we introduced the launch program a little over a year ago, we have not actually lost anybody through the program yet. We’re actually tracking ahead on churn, if you like. We’re feeling quite good about where we are. Although admittedly, we’re more at the beginning of the process.

Now, we also have customers that have just bought quantum compute as a service, not bought into the launch program. They wanted it do it yourself. In that case, we have some customers that are large multiyear customers and some customers that are smaller, shorter timeframe customers.

We do have some significant multiyear agreements, as well as some that are shorter timeframe, smaller scale agreements.

Kevin Hunt: Another question related to that, do you have any commercial customers interested in buying a system outright rather than doing the QCaaS model?

Alan Baratz: We occasionally get asked if a customer can purchase a system. The first thing we do is explain to them why the QCaaS model is so much better for them, first of all. It allows them to buy in just what they need without having to lay out a lot of cash to get a lot of capacity that they may not need for a while.

Secondly, we always ensure that our quantum cloud service has our latest and greatest technology, whether it is the latest quantum computer.

In fact, we just put an experimental prototype version of our Advantage2 system, our next generation system, into our cloud that our customers can start experimenting with prior to availability of the full blown product version. As well as our latest and greatest hybrid solvers.

Our Leap cloud service always has the latest and greatest technology as soon as it’s available. Finally, we always have backup systems for high availability, high reliability. If you buy your own system, you don’t necessarily have the backups.

If you buy your own system, you’re not necessarily going to be able to deploy the next generation technology right away, whether it’s hybrid or quantum. There’s a significant upfront cost associated with that.

Now, occasionally a customer will come to us with a really good reason to buy a system. For example, it’s a government agency that has three letters, and they want to run classified applications on a system in a secure environment.

In that case, we would entertain selling a system. There has to be a unique reason to do it. Our primary business model is quantum compute as a service.

Kevin Hunt: The next one comes an area of competition, a bit of a, I think, repeat of what you’ve already said. The specific question is who are your two biggest competitors, and how are you differentiated? I’ll let you say however you want on [inaudible].

Alan Baratz: Our marketing organization continually tells me not to mention our competitors. Although, on the flip side I love to do it. Here’s what I will tell you today, we have no competitors in the annealing space. Well, no quantum competitors in the annealing space.

We’re the only company in the world that does annealing quantum computing. When we go talk to a customer about leveraging our annealing systems and our hybrid solvers for solving their optimization problems, our competition is classical, what they are doing today on classical with heuristics.

It’s really all about just educating them, not just the benefits, but the value that quantum can bring them in solving those hard problems and improving their business operations. In the gate model space, there are lots of competitors.

Everybody and their brother is trying to figure out how to get a piece of the action in quantum, whether it’s building quantum computers, or software development tools, or applications. There’s a lot of activity in the gate model space.

We have thrown our hat into that ring as well. We think we’re quite unique in that we bring some very important hardware and software technology to that space, that none of our competitors have that’s going to allow us to move more quickly.

We feel quite good about our position in annealing. That first-mover advantage relative to building the customer base and delivering valuable commercial applications, and then growing from there to support both annealing and gate in the future.

Kevin Hunt: One last one which I’ll throw in here. We’re running up on time here soon. Since this is the SPAC series, can you maybe comment quickly on why D-Wave chose the SPAC route? Then you also have a very unique bonus structure related to the deal. If you could maybe just comment on that.

Alan Baratz: Why SPAC, is easy. We thought the time was right to basically access the public markets for fundraising, cash into the company. We thought that the SPAC path was the path that would allow us to do that most quickly.

Moreover, going down the SPAC path, we had the opportunity to partner with a team of individuals that are very smart, and we believe will be very helpful to us as we build the business going forward. These are the folks from DPCM. The CEO is Emil Michael, who is the number two at Uber, who has become a great partner and a great supporter and very helpful to the company, even as we’ve gone through the de-SPAC process up to this point in time.

Basically, access to the public markets, and access to a team of partners that can be helpful to us as we build the business. We do have a unique bonus structure that we announced when we announced the SPAC transaction.

Basically, when we announced the SPAC transaction back in February, we recognized that we were in a very challenging market environment, and that it was unlikely that that environment was going to get better before it got worse. I think that’s played out.

It’s continued to get a bit worse as time has gone on. We care a lot about our stockholders. We want them to feel good about investing in D-Wave and continuing to be investors in D-Wave as we go through the de-SPAC process. What we wanted to do was to make it economically attractive to them to stick with us.

We announced that we would be providing five million bonus shares. These would be allocated on a pro rata basis to the SPAC stockholders that do not redeem.

What this means is that if nobody, sorry, if nobody redeems, in other words all the money stays in trust and comes to the company, that those five million shares would be allocated on a pro rata basis to all the investors in the SPAC and it would lower their cost basis to about roughly $8.50.

I don’t remember the exact number, but it is in our filing. Obviously as redemptions go up, that five million bonus shares is allocated to fewer participants, because some are redeeming and some are staying in, and so their cost basis starts to go down. It bottoms out at around $6.88 a share, I believe. Again, the exact numbers are in the filing.

This is really lowering the cost basis for the public company stockholders in DPCM to basically give them an incentive to stick with the company.

Kevin Hunt: Great. Thanks Alan. I guess we’re getting almost out of time. I’ll turn it to David if he has any final questions, or, Alan, if you have any final comments you want to make, I guess.

David Williams: No. That’s it for me. I just want to say, Alan, thank you so much for being with us today. I’ve really enjoyed the conversation, as always. With that, I’ll turn it over to you for any closing remarks.

Alan Baratz: Thanks David. Thanks Kevin. I’ve really enjoyed the conversation, as well. Thanks for the opportunity to be here today. Look, I think there are just two things that I’d like to reinforce. First, D-Wave is the only quantum computing company that is commercial today.

Second, the reason why we are commercial today is because of our annealing program, which is required for optimization problems, which represents a significant portion of the total addressable market for quantum, up to a quarter of it. That quarter of the TAM for quantum is accessible to us exclusively, because it requires annealing, and we’re the only ones that have annealing.

Of course, once we introduce our gate model systems, we’ll be the only company in the world that can address the full market for quantum, because we’ll be the only company that will have both annealing and gate systems. Otherwise, I thank everybody for their time.

Kevin Hunt: Thank you.

David Williams: Thank you all.

Important Information About the Proposed Transaction between D-Wave Systems Inc. (“D-Wave”) and DPCM Capital, Inc (“DPCM Capital”) and Where to Find It:

A full description of the terms of the transaction between D-Wave and DPCM Capital is provided in a registration statement on Form S-4, as amended, filed with the Securities and Exchange Commission (the “SEC”) by D-Wave Quantum Inc. that includes a prospectus with respect to the combined company’s securities, to be issued in connection with the transaction and a proxy statement with respect to the stockholder meeting of DPCM Capital to vote on the transaction. D-Wave Quantum Inc. and DPCM Capital urge investors, stockholders, and other interested persons to read the proxy statement/ prospectus, as well as other documents filed with the SEC, because these documents contain important information about D-Wave Quantum Inc., DPCM Capital, D-Wave, and the transaction. DPCM Capital commenced mailing the definitive proxy statement/prospectus to its stockholders on or about July 13, 2022 in connection with the transaction. Stockholders also may obtain a copy of the registration statement on Form S-4, as amended—including the proxy statement/prospectus and other documents filed with the SEC without charge—by directing a request to: D-Wave Quantum Inc., 3033 Beta Avenue, Burnaby, BC V5G 4M9 Canada, or via email at shareholdercomm@dwavesys.com and DPCM Capital, 382 NE 191 Street, #24148, Miami, Florida 33179, or via email at mward@hstrategies.com. The definitive proxy statement/prospectus included in the registration statement, can also be obtained, without charge, at the SEC’s website (www.sec.gov).

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