Good day, everyone, and welcome to the D-Wave Q4 2023 Earnings Call. At this time, all participants are in a listen-only mode. Later, you will have the opportunity to ask questions during the question-and-answer session. [Operator Instructions] Please note, today's call will be recorded, and I'll be standing by if you should need any assistance. It is now my pleasure to turn the conference over to Kevin Hunt, Investor Relations. Please go ahead.

Thank you, and good morning. With me today are Dr. Alan Baratz, our Chief Executive Officer, and John Markovich, our Chief Financial Officer. Before we begin, I would like to remind everyone that this call may contain forward-looking statements and should be considered in conjunction with cautionary statements contained in our earnings release and the company's most recent periodic SEC report. During today's call, management will provide certain information that will constitute non-GAAP financial and operational measures under SEC rules, such as non-GAAP gross profit, non-GAAP operating expenses, adjusted EBITDA, and bookings. Reconciliations to GAAP financial measures and certain additional information are also included in today's earnings release, which is available in the Investor Relations section of our company website at www.dwavequantum.com. I'll now hand over the call to Alan.

Thanks, Kevin. Good morning, everyone, and thank you all for taking the time to join us today. D-Wave's momentum is undeniable. We're seeing traction and progress across every part of our business, substantive product advancements, ground-breaking scientific results, new strategic partnerships, additions to the executive leadership team, and impressive commercial traction. We're single handedly leading the transition from an academic endeavor exploring quantum's potential to enterprise-scale adoption and deployment, solving our world's toughest problems. Based on our strategic decision to bring to market a different type of quantum technology, annealing quantum computing, now proven to be able to solve important real world problems that cannot be solved classically, we hold a first-mover advantage that no other company in the world can claim. While the rest of the industry is focused on building gate model systems that won't solve real world problems for many years, we're in the market now, helping customers derive ROI from quantum solutions today. Let's face it, the world's toughest problems are only getting tougher, and customers can't wait another five-plus years for solutions. This isn't about future potential. This is about quantum-powered solutions that drive better business outcomes now. And D-Wave is the only company doing it today. Our market leadership position is evident. We were the first to launch commercial quantum systems, the first to have quantum applications running in production for commercial customers, and now, the first to achieve a demonstration of quantum supremacy on real world problems. No other quantum computing company comes close at this time. So, let me walk you through a few key highlights of recent developments at D-Wave. First, we believe that D-Wave is the first in the world to demonstrate quantum supremacy on real world problems. This ground-breaking work was achieved using our latest generation Advantage2 quantum computer.…

Thank you, Alan, and thank you to everybody taking the time to participate in today's call. In my review of the fourth quarter and fiscal year results, I will be providing non-GAAP operating metrics, including bookings, as well as non-GAAP financial metrics, including non-GAAP gross profit, non-GAAP gross margins, non-GAAP operating expenses and adjusted EBITDA, as we believe these metrics improve investors' ability to evaluate our underlying operating performance. These measures are defined in the tables at the bottom of today's fourth quarter earnings press release with the non-GAAP financial metrics for the most part adjusting for non-cash and non-recurring expenses. Revenue in the fourth quarter of fiscal 2023 totaled $2.9 million, an increase of approximately $500,000, or 21%, from the fourth quarter fiscal 2022 revenue of $2.4 million and up 13% sequentially over the immediately preceding fiscal 2023 third quarter revenue of $2.6 million, representing the third consecutive quarter of sequential quarter-to-quarter growth in revenue. Due to the timing associated with our professional services revenue, we believe that our bookings performance may at times be a better indicator of our business momentum than quarterly revenue. We define bookings as orders received from our customers that are expected to generate revenue in the future. We present the operational metric of bookings because it reflects customers' demand for our products and services and to assist investors in analyzing our performance in future periods. Bookings for the fourth quarter totaled $3.1 million, an increase of approximately $800,000, or 34%, when compared with the fourth quarter of 2022 bookings of $2.4 million, and an increase of approximately $200,000, or 8%, from the immediately preceding fiscal 2023 third quarter bookings of $2.9 million. The $3.1 million of fourth quarter bookings represents D-Wave's seventh consecutive quarter of year-over-year growth in quarterly bookings, as Alan highlighted…

[Operator Instructions] Our first question comes from Suji Desilva with ROTH MKM. Please go ahead.

Good morning, John. So, couple of financial questions first perhaps. John, the QCaaS contracts signed to date, what's the typical term length for those? And, are those recognized linearly or is there sort of an elbow as usage goes up?

I've missed the second part of your question, Suji. Are they...

Whether they're recognized linearly or whether the revenue goes up with usage over time?

Typically, it's ratably straight line over the term of the contract, and we have contracts that range from several months to several years in duration.

Okay. And sticking on the financials, the commercial customer count in '23 was 78. Is the expectation that, that customer count grows in '24, or is it more than expectation to monetize revenue from this base? What's more of the focus in '24 relatively?

Our focus is on both, Suji. Expanding revenue opportunities within the existing base, as well as expanding the number of commercial accounts.

Okay. And then maybe you can provide data on the number of PoCs in process. And maybe just maybe tying to that, how professional services revenue is a lead indicator of the QCaaS revenue, if that's also the case?

Okay. I'll address your second part of your question first. So, over the last two quarters, Q3 and Q4, we had record levels of professional services. And this is a leading indicator of the potential pipeline for the production applications because within that we have the PoCs. With respect to the number of PoCs, we haven't disclosed that specific number on a quarterly basis.

Okay. That helps. Thanks. And then last question really on the applications. You have two in production and two more coming. Do you expect to add additional apps in the next 12 to 18 months? Or are you going to emphasize some of these initial apps for revenue in the next 12 to 18 months?

Alan, do you want to address that?

Yeah, I'll take that. So, Suji, as we discussed, I believe, in the last earnings call, as well as at our Analyst Day conference, our focus for the foreseeable future is on a specific set of use cases revolving around resource allocation and resource scheduling, primarily in the areas of manufacturing, logistics and supply chain. And so that really will be our focus for the foreseeable future. That having been said, there are actually quite a few different specific applications that fall into those broad areas. And so in fact, you can expect to see us talking about a variety of different applications across those key industries going forward.

Okay. All right. Thanks, Alan. Thanks, John.

Thank you. Our next question comes from David Williams with Benchmark. Please go ahead.

Hey. Excuse me. Good morning, gentlemen. Thanks for letting me ask the question here. First I wanted to ask, maybe Alan, can you speak a bit to the magnitude of the impact on the demonstration of the quantum supremacy? Obviously, there's going to be some skepticism, I think, from peers and maybe the investment community in general. But is there something you would say that maybe helps us get comfortable in that -- those findings, and just maybe any color there would be helpful, I think.

Yeah. So, first of all, David, let me just reiterate that we have submitted this paper for peer review. And as a result, we need to be a little bit careful with what we say about it. But the paper is on the archive and anybody can go look at it. In addition, we are able to talk a little bit about it in social media, in various meetings with customers and occasionally in conferences, if they're primarily technically oriented conferences. What I can say is that since we started talking about it in social media and at conferences, 90%-plus of the feedback has been positive. So, yeah, I mean, there are a couple of folks that are typical D-Wave quantum annealing, un-enthusiasts, shall we say, who have made some comments. But as I said, the vast majority of the feedback that we've gotten has been very, very positive, including from some very well-respected academics as well as government officials. So, we're actually quite pleased with the feedback, but really excited about the result.

Great. Thanks for the color, and congrats on that demonstration. I guess secondly is we're seeing -- it feels like a real acceleration in your business in terms of just the momentum that you're gaining and moving programs into production. But I guess maybe can you talk about what's accelerating that? What you're hearing from customers? And then maybe secondly just how you're -- what you're hearing from customers in relation to your peers, what they're finding? I'm sure that most are at least in the discovery mode and using multiple type vendors today. And just kind of curious what your feedback would be how your performance compares with your peers and what you're hearing from your customers. Thank you.

Yeah. So, I don't really want to talk about what our peers or competitors are doing, but I would highly encourage you to go ask them, which commercial customers they have, what real world applications they are working on, are these at scale or kind of experiments into whether the quantum system can actually do anything or not, and whether they've got any applications in production or not. So, I encourage you to go ask them that question. For us, as I commented a bit earlier and as John reinforced, the model is to start with professional services engagements to help build out proofs of concept that allow our customers to understand how our quantum systems can deliver value to their business operations and with a positive ROI. And then, once they understand that and are bought into it to help them transition those proofs of concept into production applications and then deploy them in production, at which point, we put in place a production agreement that is primarily quantum compute as a service agreement. So, it starts with a professional services agreement and then it transitions to a production application deployment quantum compute as a service agreement. And so, the work that needs to be done to effect the transition from proof of concept to quantum compute as a service is complete the PoC, help them benchmark it, help them understand the value and the ROI, help them understand how to move it into production and then support them in the work to actually move it into production. I will tell you that we expected at the beginning of last year that this process would move a bit faster than it actually has moved. So, while we were really pleased to see the transition to production starting in Q4. And we see that, we have the ability to move many more applications into production through the course of this year. It has taken us longer than we expected. But a big focus for us right now is how to shorten that timeline. And at Analyst Day, we talked a little bit about this when we described our verticalization strategy and the fact that we believe by focusing on specific use cases in specific verticals, we will learn with our customers how to, A, validate the value more quickly and, b, help them move into production more quickly.

Great. Thanks so much for the color there. Certainly appreciate it. And just one last one, just wanted to tell congratulations to Trevor on his promotion there. Thanks.

I will pass that on to him. Thank you.

Thank you.

Our next question will come from Harsh Kumar with Piper Sandler. Please go ahead.

Hey, Alan, John, huge congratulations. If I can use the term, seems like the dream is coming true. I wanted to ask about a specific application that you had in your press release that you mentioned in your commentaries. I think I'm pronouncing this correct, Zapata AI. AI is obviously all the rage, me being a semiconductor analyst, see it. You talked about reduced time for training. I was -- for particularly for machine learning, which is a huge application. I was hoping maybe you could just expand on that a little bit and talk about how you're helping there and what you're doing there.

Yeah. Som first of all, Harsh, you may or may not recall that at Analyst Day, we showed a graph of how we expect various use cases to become enabled with various iterations of our technology or enhancements or improvements of our technology. And we actually had AI and machine learning out a couple of years from now. Now that chart was put together before we really started digging in with Zapata AI to look at what it would take to do machine learning and generative AI model training using a quantum computer to help generate samples rather than doing it all classically. And what we found was that with our Advantage2 quantum computer, and so we are working with Zapata on the 1,000 qubit Advantage2 system, we are actually able to do it quite well today. Now, it's a little bit early to be definitive on this, but what I can tell you is that, the early results are demonstrating that we are able to do a better job of training models, more accurate, more rapidly, and here's a really important point, with lower power consumption. And so, we're very excited about that. This is not a research experiment. We put this relationship in place with Zapata to bring a product to market together. And so, there is a period of time of a few months upfront to build out the product and validate that it achieves the goals that we set for ourselves and then to get it in the market. And that is progressing really well. So, we're quite excited because it really accelerates our move into generative AI by a couple of years. But moreover, I actually think it accelerates quantum and AI by a number of years.

Fantastic. And then, I think at your Analyst Day, I think you had shown a obviously, the 1,000 qubit system, but I think you were talking about one that was the next generation, the 1,200 qubit system, I believe, from my memory here. Is that in production? Is that helping out for some of the applications, or do you expect quite a bit of dramatic breakthrough as you move into your newer system?

So, the Advantage2 1,000 qubit system is now in our Leap cloud service and it is accessible to all customers. So, they can either run on the 5,000 qubit advantage processor or the new 1,200-plus qubit Advantage2 Processor. And many of our customers are starting to run on the Advantage2 Processor, because it is a more powerful system even with 1200 qubits.

Great. Thanks. That was all I had. Thank you. Congratulations, guys.

Thank you.

Thank you.

Thank you. Our next question comes from Richard Shannon with Craig-Hallum. Please go ahead.

Well, hi, guys. Thanks for taking my question. [indiscernible] noise here driving down the freeway. I did want to follow-up on the topic of AI here that Harsh just brought up and maybe a couple other permutations on this topic. First of all, you're talking about improvements in training. Just to be clear, are we talking about training of really large language models or smaller ones or a range? Kind of give us a sense of what you have experience with? And then I guess the follow-on here is, Alan, I think you talked about accelerating the timeframe for quantum and AI to intersect here. I mean, when are you expecting to see production revenues or at least some amount of revenues coming from these kinds of applications? Thanks.

Yes. So, the starting point for the work with Zapata is really in the life sciences area and identification of new molecules in a variety of different life sciences areas. But that's really just the initial target. But that having been said, really what that means is that the initial model building and training is not large language model, but more in the area of kind of molecular data, if you like. And in some sense, I think that from there, we'll likely launch into other corporate applications. There's nothing that we can see right now that would prevent using this technology for training large language models as well, But the initial go-to-market focus is on corporate machine learning and generative AI. As far as accelerating the timeline, look, how do I want to say this, there's been experimental work done on investigating how quantum systems might be applied to improving machine learning. But this has all been basic research and experimental investigation. And in fact, if we put D-Wave aside for a minute and we talk about using quantum computers to generate better samples, because they're generating them from a quantum distribution rather than a classical distribution, on the current non-D-Wave gate model systems, it can take days to weeks to generate the samples that GPUs can create in seconds. So, it's always been thought of as very early days in research experimentation. However, with our system, leveraging the Advantage2 processor and frankly, the basic work that we did on the supremacy efforts, we are now able to generate those samples in seconds as well. And that's really what's allowing us to make this commercial today. And with Zapata, we expect to have products to market in a timeframe measured in months, not years.

Okay. Very interesting. Thanks for that detail, Alan. My last question here is maybe kind of following up on a prior question as well and it's really a topic you brought up and discussed at the analyst event a few months ago. And recognize that this is probably too short of a timeframe to expect any change, but always interested in seeing some improvement in the sales cycle. I know that's a big focus for you. Since the analyst event, have you seen any kind of green shoots or experiences that have helped you or even started to see any real world progress in terms of shortening sales cycles either at the beginning or the end of the process to getting to production revenues?

Yeah. So, two things. First of all, and I think I might have mentioned this even at the Analyst Day meeting, but our sales cycles, over the course of the last few years, has shortened. When we started down this path a couple of years ago, we were looking at 12-plus month sales cycles to kind of get the initial engagement in place with the customer, I think the professional services proof of concept engagement. We're now able to do that fairly regularly on a four to six months' timeframe. The verticalization strategy, which we only just initiated at the beginning of this year, we think we'll shorten that a bit further, but we really think it will shorten the back end, which is the transition from proof of concept to production. But it's still a little early because we did only launch that at the beginning of this year. That having been said, we have started demand gen and lead gen against the verticalization strategy and we're already seeing really good results from that with a number of large Global 2000 companies that had not previously been customers expressing interest in what we're doing.

Okay. That sounds like we could see as an expansion of the customer funnel here in terms of the customer count that you're giving us in the not too distant future. Is that a fair expectation, Alan?

I think so.

Okay. Excellent. Last quick question here, just on the financial guidance for the year, the EBIT loss here, you haven't given us any thought process either on revenues or the OpEx and related items to help us kind of put those together here. Anyway you kind of help us think about what kind of revenue growth you're expecting for this year? You've been fairly tight on OpEx here. I don't know if you're expecting to open the funnel up at all as you trying to drive faster growth. But just any general expectations you can help us in your thought process for the year that would be great. That's all for me.

John, do you want to take that?

Richard, I can give you some guidance on the operating expenses. So, the area that we will invest in this year in OpEx is go-to-market. And we're focused on a relatively significant increase in go-to-market investment from last year. And we anticipate that our year-over-year G&A will actually be down between 2024 and 2023, principally due to a lot of the non-recurring costs associated with the going public process last year and R&D being relatively flat to slightly up on a year-over-year basis. Does that answer your question, Richard?

Perfect. Thank you, guys.

You're welcome.

This only answers part of the OpEx question. I mean, the essence of the question is really about revenue growth. I'm assuming since you didn't put it in the press release, you're probably not prepared to talk about that. So, if you have any thoughts there, that's kind of what I was looking for, John.

You're correct. We have not provided revenue guidance.

Okay. That's all for me, guys. Thank you.

Thank you. Our next question comes from Quinn Bolton with Needham & Company. Please go ahead.

Hey, guys. I wanted to follow-up on the AI question as well since it's obviously, I think, very topical for most investors. Alan, you'd mentioned that the quantum computers and a quantum sampling of data can provide better results. I guess I was wondering or hoping you could expand on that a little bit more. I mean, I think for classical training, obviously, you've historically started with the data set that you use to train the model. So, I'm just trying to figure out how does quantum sampling and quantum production of data samples, how does that sort of apply versus, I guess, maybe historical training when you start with the initial set of data that you initially used to train the model? And then I've got a couple of follow-ups. Thanks.

Yeah. So, Quinn, there's probably a longer discussion here that we'd be more than happy to have with you. But the idea is the following. When you train a model, what you're trying to do is create a computational engine that basically is able to generate data with the same distribution as the distribution of the input dataset. So, you're really trying to build a computational engine that matches a distribution. However, there are only so many degrees of freedom in classical distributions, but quantum distributions have more degrees of freedom. So, if you could build the model against a classical distribution with -- sorry, against a quantum distribution with more degrees of freedom, potentially, you can get a better fitting model, because you have those additional degrees of freedom to match against. And that's what the quantum distribution gives you, and that's why we say better or more accurate models.

Got it. Makes sense. Thank you. And then, John, obviously, you're not sort of giving bookings guidance beyond the first quarter, a pretty nice step up in bookings in Q1. Wondering if you might be prepared to comment. Do you expect that bookings growth to sort of continue to grow sequentially through the year? I know it can be lumpy. So, just trying to sort of think about what sort of shape you expect the bookings through 2024? Thank you.

I can speak to the year, Quinn. Certainly, we're expecting an increase on a year-over-year basis. But based upon the composition and the types of contracts that we're negotiating, that could vary from quarter to quarter.

Perfect. Thank you very much.

Thank you. Our next question comes from Kevin Garrigan with WestPark Capital. Please go ahead.

Yeah. Hey, Alan and John, thanks for taking my question. You had recently announced a partnership with NEC Australia and entering the Australian market. I know the U.S., Europe and China are really trying to develop quantum computing technology, but any other geographies that are really looking to develop quantum and that you guys are really looking to expand into?

Yeah. So, we are already in Japan, North America and Europe. And, frankly, our business is quite strong in both Europe and in Japan. And so, from an Asia Pacific perspective, Australia is the next logical place for us to go. I will tell you, we have Leap access in India, but we don't really have a kind of full-court press currently on trying to sell commercially in India. And there are a couple of areas in that region that we will likely never or at least not for the foreseeable future enter China is the primary example of that, simply because of the geopolitical issues associated with that and the fact that Quantum is a sensitive technology for the U.S. and Canadian governments.

Okay. Perfect. Thanks, Alan. And then just as a quick follow-up, just kind of wondering if you could comment on the competitive landscape, more kind of new companies. Every week, you see a new quantum computing company that kind of pops up with the next big quantum technology. So, are you seeing any increased competition in the quantum annealing market?

No, not in the annealing market. And as we said in the past, it will be hard for anybody to compete with D-Wave in the annealing space. A, we've got a 15-plus year head start and we're not standing still as witnessed by the recent availability of our 1200 qubit Advantage2 processor. And B, we've got a huge patent mode with over 200 U.S. granted patents, over 500 worldwide patents. So, we don't expect to see much competition in the annealing space, which is great for us because there's an important class of applications, business optimization that really only annealing can address from a quantum perspective, and that pretty much makes that market ours.

Yeah. That makes a ton of sense. Okay, awesome. Thanks, Alan. Thanks, guys.

Thanks.

Thank you. Our last question will come from Craig Ellis with B. Riley Securities. Please go ahead.

Yeah, thanks for sneaking me in guys, and congratulations on all the progress in the quarter, things like Zapata and AI, and appreciate all the financial transparency. Alan, I wanted to go back to one of the comments you made in your prepared remarks. The point that Advantage2 has 100,000 problems already submitted. So that seems like just a remarkably high number, which would seem to be very positive for how customers would want to engage in that technology. The question is, as those problems have come in, have you been able to analyze those by end market, existing new customers, any other parameters that give us a better sense for how that problem set is distributed across existing or potential new customers or verticals?

Yeah. Unfortunately, not really for the following reason, and this is actually an important characteristic of our system. When a problem gets submitted to the system, because of how you program our system, we can't really tell what the application is that kind of underlies that submission. Just the way the computer gets programmed and the data that ends up getting submitted, it almost kind of inherently obfuscates. And this is actually important because it's an important privacy and security element of how our system works. So, no, when our customers submit problems, we don't know what exactly they're doing. But we have relationships with all those customers, and to the extent that we engage with them on a regular basis, we do try to understand exactly how they're using our systems. I will say that the Advantage2 processor is brand new. It's only been in Leap for a month. And so most of what's going on in that system right now is evaluating it, so that they can see how much better it is than the previous generation system.

Any historic data with prior systems on what the conversion rate is between problem submission, proof of concept work, et cetera, to give us an estimate of what the final might look like after this?

Yeah. Because of the fact that when a new generation system comes out, we always put it into our cloud service. And whenever we put something in our cloud service, it's available to all our customers instantly. Most customers just immediately transition to the new system. So, occasionally, if there's something that's up and running, they'll leave it on the previous generation system. But when it comes to new work, almost immediately transitions to the new system.

Yeah. Got it. That's helpful. Appreciate that. And then the second question was more for John and I wanted to take a swing at following up on one of Quinn's points on bookings for calendar '24. So, if we look at the first quarter, we've annualized I think around $17.2 million, so up 50% year-on-year. And I'm not looking for guidance, John, because I know the company isn't providing that. But what I was hoping you could do is just frame, as we look at the year, what would be some of the factors that would drive higher bookings levels, maybe early conversion on Advantage 2, new successes with streamlined go-to-market strategy, et cetera? And are there things we should be mindful of that would be challenges to year-on-year growth, whether there was something unusual that happened last year, et cetera? Thank you.

I think one of the areas that we're looking at with respect to the bookings momentum Craig is our focus on the verticals and the implementation of that go-to-market program as well as the timing and the magnitude of the applications transitioning into production.

Got it. And then lastly, there seems to be a growing Forbes Global 2000 quotient to the customer base. I think we're about 33% now with the 78% you had last year. Bigger picture, Alan, how does that evolve over time? Are we thinking that that moves up significantly as we go through '24 and '25, or what would the pacing for that customer conversion be at that level?

So, I think I mentioned a few minutes ago that as we've launched the new verticalization at least in the logistics arena, we've already seen very strong interest from companies in that vertical, many of them Global 2000 companies or Fortune 500 companies. So, we're starting to build a really nice pipeline now with companies at that scale that are not currently customers. But obviously, that's just the very beginning of the process with pipeline building and now we have to go get deals closed.

All right. Well, congratulations on a strong start to the year. Thank you.

Thank you.

Thank you. At this time, I would like to turn the call back to Alan Baratz for any additional or closing remarks.

Okay. So, first of all, I apologize to all of you for running over today. We'll try to do a better job of meeting management next time around. But for those of you that stayed with us, thank you. Listen, I couldn't be more excited by the progress we're making. It isn't easy to build an entirely new category, but we're doing it and we're leading the way. Our hardware and software are delivering highly performant production scale and commercial grade solutions. Businesses are using our technologies in production to fuel daily operations and reap the tangible benefits quantum can bring. We're showing the world through our research how quantum can outperform classical, full stop. D-Wave is out in front, blazing the trail for commercialization of quantum. It's an incredible time for the company, and thank you all for taking the time to join us.

This does conclude D-Wave's Q4 2023 earnings call. You may disconnect your line at this time, and have a wonderful day.