D-Wave Quantum Inc.

Good morning everyone and welcome to BeReeve's second quarter of fiscal year 2025 earnings conference call. Today's conference call is being recorded. At this time, I would like to turn the call over to the Beth Nafis of Investor Relations. Please go ahead.

Thank you and good morning. With me today are Dr. Alan Barrett, our Chief Executive Officer, and John Marcovich, 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 reports. During today's call, management will provide certain information that will constitute non-GAAP financial measures under SEC rules, such as non-GAAP growth profit, non-GAAP growth margin, and the test of EBITDA loss and operating metrics such as bookings. Record affiliations to GAAP financial measures and certain additional information are also included in today's earnings release, which is available on the Investor Relations section of our company's website at .beereevequantium.com. I will now hand the call over to Alan.

Good morning everyone and thank you for joining us today.

I'm once again really excited to share our results for the second quarter of fiscal 2025. Building on the company's remarkable first quarter results, we continue to see accelerating momentum across the business. Let me now walk you through some key highlights, starting with technical achievements. In May 2025, we announced the general availability of V-Wave's Advantage II quantum computer, our most advanced and performing system. The Advantage II system is a powerful and energy efficient annealing quantum computer capable of solving computationally complex problems beyond the reach of classical computers. A smaller prototype of this system was used to demonstrate our quantum supremacy result on a real-world material simulation problem, a first for the industry. Featuring V-Wave's most advanced quantum processor to GAAP, the Advantage II system is commercial-grade and built to address real-world use cases in areas such as optimization, material simulation, and artificial intelligence. As previously shared, the Advantage II quantum processor has demonstrated impressive performance gains over the previous Advantage system, including double coherence time for faster time to solution, a 40% increase in energy scale for higher quality solutions, and increased cubic connectivity from 15 to 20 ways to enable solutions to larger problems. It's a significant engineering achievement that highlights our progress in scaling quantum technology to meet demand for growing computational processing power while maintaining energy efficiency. We're helping customers realize value from quantum computing right now, and the Advantage II system is an important truth-telling. We recently announced a new strategic development initiative focused on advanced cryogenic packaging, designed to advance and scale both state models and annealing quantum processor development. The initiative builds on V-Wave's technology leadership in cryogenic packaging and will expand our multi-ship packaging capabilities, equipment, and processes. By bolstering V-Wave's manufacturing efforts with -the-art technology, the company aims to accelerate its development efforts and support an aggressive product roadmap on the past 100,000 qubits. As part of this initiative, V-Wave is leveraging deep expertise and processes at the NASA Jet Propulsion Laboratory, JPL. Harnessing JPL's superconducting Bumpern process, we have demonstrated -to-end superconducting interconnects between shifts. Work that we expect will serve as an important foundation for scaling both our annealing and our gate model systems. We are continuing important development work that brings together quantum and AI to explore the synergies and benefits of these complementary technologies. Our aims to help organizations accelerate the use of annealing quantum computers in a growing set of AI applications. To that end, we recently introduced a collection of developer tools to advance quantum AI and machine learning innovation. First, we launched an open-source quantum AI toolkit that provides direct integration between V-Wave quantum computers and PyTorch, a production-based machine learning framework widely used to build and train these learning models. Second, we launched a new demonstration that illustrates how developers can use V-Wave quantum AI toolkit to generate simple images, reflecting what we believe is a pivotal step in the development of quantum AI capabilities. These tools are making it easier for customers like Japan's Daco and Triumph to build hybrid quantum classical machine learning applications. Customers are increasingly coming to our groups for how to integrate quantum into AI workflows, and we expect that this will remain a priority development area for us. Last quarter, we've accepted the purchase of an advanced system by the ULIC Supercomputing Center, an important milestone in our burgeoning on-premises business. Demand for purchasing a system has been high, and we've been in discussions with numerous organizations around the world interested in buying a V-Wave quantum computer. Recently, we announced a strategic relationship with Yansai University and Incheon Metropolitan City to accelerate the exploration, adoption, and usage of quantum computing in South Korea. Under the terms of the Memorandum of Understanding, the three organizations are working together to advance research and power development for quantum computing, to provide access to V-Wave quantum computing systems and services, and to collaborate on the development of new cases in biotechnology, material science, and other areas. In addition, the MOU supports our efforts toward the acquisition of a G-Wave advanced system on-site at the Yansai University International Campus in San-Gro, Yansu-gu, Incheon. Before training for commercial updates, I wanted to take a moment to remind everyone of the differences between a kneeling and gait model. As there still appears to be continued misinformation that we believe is confusing the market. A kneeling and gait models are different types of quantum computing approaches that solve different types of problems. According to peer-reviewed research, gait model quantum computers will not offer advantages for all problem types. Multiple research results have shown that a kneeling quantum computer outperforms and are expected to continue to outperform gait models on optimization problems. So gait models cannot universally solve all problems better than classical. It is also important to understand that a kneeling is not a niche solution. We believe that a kneeling quantum computing is well suited to a broad set of problems including AI machine learning, quantum simulation, and business optimization, which is ubiquitous in today's modern enterprise. Business optimization problems encompass things like workforce scheduling, production scheduling, resource allocation, vehicle routing, and so on. Together, these represent extensive use cases with far-reaching potential. To characterize a kneeling quantum computing as niche is misleading and ill-informed. Both kneeling and gait model quantum computers can solve a broad range of problems and each has its limitations with problems it cannot efficiently solve.

A kneeling

quantum computing is very good at solving optimization problems, which cannot be efficiently solved by gait models. Gait model quantum computers, once commercialized, are expected to be very good at quantum chemistry and 3D fluid dynamics, which cannot be efficiently solved by any other. And both systems, both systems can tackle linear algebra and factor gait, leading problems related to AI, machine learning, and cryptography. We believe that organizations will need both a kneeling and gait model systems in order to address their full problem sets. This is why D-Waze is building both types of quantum computers for our customers. Now I'll turn into commercial updates. In terms of D-Waze's customer portfolio, we've signed a number of new and renewing customer engagements for both commercial and research applications, including E.ONT, a European multinational electric utility company, GE Vernova, a global energy company, the National Quantum Computing Center, NQCC, the UK's National Lab for quantum computing, Nikon Corporation, a multinational corporation specializing in optics and precision technologies, NTT DataCorp, a multinational IT services and consulting company, NTT DoCoMo, Japan's leading mobile operator, Chug Corporation, a multinational electronics company, and the University of Oxford. We've also been working with a Fortune 500 error state and defense company, and in Q2 we completed a prioritization of 12 different use cases applicable to their business operations that the customer found challenging and unsolved using classical optimization techniques. Quantum optimization, powered by a new and quantum computing, can deliver value in terms of better and faster solutions. Based on the results of our initial exploratory work with this customer, we've now started building the proof of concept for the first of the use cases with a roadmap to expand to all of them and market them to additional error state companies. In addition, we recently built a quantum hybrid proof of technology with North Wales Police to optimize the deployment of patrol vehicles. The proof of technology solution was tested against historical data and exceeded the customer's expectations, needing target response time for more than 90% of incidents and using just 10 seconds of solve time. We're encouraged by these initial results and see them as important proof points of quantum hybrid potential for law enforcement related use cases. We're also seeing growing interest in the LEED Quantum Launchpad Program, which is a three-month trial that provides access to the UA's quantum computing systems, our LEED real-time quantum cloud service, and our team of quantum experts for project support. Since its introduction in January of 2025, the Launchpad Program has received more than 1,300 applications from business, government, and academic institutions. The program is serving as an important vehicle to attract and fast-track customers into proof of concept development and ultimately application deployment. So to summarize, we are continuing to make steady progress across our business. First, delivering on technical milestones, including the release of our sixth generation quantum computing. And advancing quantum AI development. Second, executing against our global market strategy, including increased discussions for on-premises systems with a variety of interested parties. And third, working closely with customers to develop hybrid quantum applications that are addressing critical organizational problems. With the strongest cash tradition in our company's history, we believe that we are very well-positioned to explore our NNA activity that will propel our business even further and faster while delivering value to customers and shareholders alike. With that, I'll hand it over to John to provide a review of our second quarter, fiscal year 2025 results. John?

Thank you, Alan, and thank you to everyone taking the time to participate in today's call. In my review of the second quarter and first half 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, and adjusted EBIT loss. As we believe, these measures improve investors' ability to evaluate our underlying operating performance. These measures are defined in the tables at the bottom of today's second quarter earnings press release with the non-GAAP financial measures. For the most part, adjusting for non-cash and non-retiring expenses. Revenue for the second quarter of fiscal 2025 totaled $3.1 million, an increase of about $900,000 or 42% from the second quarter of fiscal 2024 revenue of $2.2 million. The second quarter revenue includes $1 million in revenue associated with the Advantage II Cost and Processing Unit upgrade for the annealing system that was installed at the U.S. Supercomputing Center in the first quarter of this year. Revenue from the Advantage II upgrade is recognized using the percentage of completion method reflecting the timing of installation services that are closely integrated with the QPU or Corner Processing Unit hardware. We expect that this upgrade will be substantially complete by the end of this year. Looking for the second quarter totaled $1.3 million, an increase of approximately $600,000 or 92% from the second quarter of 2024 bookings of $700,000. As we have previously mentioned, we are encouraged by an expanding sales pipeline that includes a growing number of large enterprises and well-known logos with a market increase in the size of the average transaction size when compared to a year ago. Many of these companies are focused on having us build them proof of concepts versus just buying a small amount of QCAS or quantum computers as a service that translates to incrementally more complex transaction structures. This in combination with the challenges associated with dealing with substantially larger organizations with multi-step and sometimes very rigid procurement processes and documentation requirements has resulted in deals taking longer to be closed than what we originally anticipated. Over the last four quarters we have had over 100 revenue generating customers that includes customers in the commercial, government and research sectors in nearly 2,000 Forbes Global 2000 companies. JapGris profit for the second quarter was $2 million, an increase of approximately $600,000 or 42% from the second quarter of fiscal 2024 JapGris profit of approximately $1.4 million with the increase due primarily to the growth and revenue. Non-GapGris profit for the second quarter was $2.2 million, an increase of approximately $600,000 or 39% from the second quarter of fiscal 2024 Non-GapGris profit of approximately $1.6 million. The difference between Gap and Non-GapGris profit and gross margins is limited to non-cash stock case compensation and depreciation expenses that are excluded from the Non-GapGris profit and gross margin. GapGris margin for the second quarter was 63.8%, representing a slight improvement from the second quarter of fiscal 2024 GapGris margin of 63.6%. Non-GapGris margin for the second quarter was 71.8%, a slight decrease of .3% from the second quarter of fiscal 2024 Non-GapGris margin of 73.1%. Net loss for the second quarter was $167.3 million or 55 cents per share, an increase of $149.5 million or 45 cents per share from the second quarter of fiscal 2024 Net loss of $17.8 million or 10 cents a share. The increase in the Net loss was primarily due to $142 million in non-cash, non-operating charges related to the re-measurement of the company's warrant liability, as well as realized losses stemming from actual warrant exercises. In extracting the impact of the non-cash, non-operating warrant re-measurement and related charges from the Gap Net loss, the adjusted Net loss for the second quarter was $25.3 million or 8 cents per share, an increase of $5.3 million and a decrease of 4 cents per share from the fiscal 2024 second quarter adjusted Net loss of $20 million or 12 cents per share. Adjusted Net loss for the second quarter was $20 million, an increase of $6.1 million or 44% from the second quarter of fiscal 2024 adjusted Net loss of $13.9 million, with the increase due primarily to higher operating expenses that is reflective of our investments to support our future growth opportunity, partly offset by higher gross profit. I'll now address the performance for the first half of the year. The waived revenue for the six months ended June 30th was $18.1 million, an increase of $13.5 million or 289% from revenue of $4.6 million in the six months ended June 30th, 2024. Bookings for the first half of fiscal 2025 were $2.9 million, a decrease of approximately $400,000 or 13% from bookings of $3.3 million in the first half of fiscal 2024. Gap gross profit for the first six months of fiscal 2025 was $15.9 million, an increase of $12.9 million or 420% from gap gross profit of $3 million for the first six months of fiscal 2024, with the increase due primarily to the high margin system sale during the six months ended in June. Non-gap gross profit for the first six months of fiscal 2025 was $16.3 million, an increase of $12.8 million or 367% from the year earlier six months non-gap gross profit of $3.5 million. Gap gross margin for the first half of 2025 was 87.6%, an increase of 23% from the .6% gap gross margin in the first half of fiscal 2024, with the increase due again primarily to the high margin system sale during the first six months, for the six months ended in June. Non-gap gross margin for the first half of fiscal 2025 was 89.9%, an increase of .9% from 75% in the six months ended June 30, 2024. Net loss for the six months ended June 30, 2025 was 172.8 million or 59 cents per share, compared with a net loss of 35.1 million or 21 cents per share for the six months ended June 30, 2024. In adjusting the impact of the non-cash, non-operating warrant remunerant and related charges from the gap net loss, the adjusted net loss for the six months ended June 30 was 34.6 million or 12 cents per share, essentially flat when compared to the adjusted net loss of 34.6 million dollars or 21 cents per share for the six months ended June 30, 2024. Adjusting the net loss for the first half of fiscal 2025 was 26.1 million dollars, a decrease of approximately 700,000 dollars or 3% from the adjusted net loss of 26.8 million in the first half of 2024, with the improvement due primarily to higher gross profit partially offset by increased operating expenses. Moving on to the balance sheet and liquidity, as of June 30, DOA's consolidated cash position totaled a record 819.3 million dollars, representing over a 1900% increase from the fiscal 2024, second quarter consolidated cash balance of 40.9 million dollars, and a nearly 170% increase from the immediately prior fiscal 2025 first quarter consolidated cash balance of 304.3 million dollars. During the second quarter of fiscal 2025, we raised over 500 million dollars in equity, including 400 million dollars in gross proceeds from our fourth -the-market equity program, 99.3 million dollars in net proceeds from the exercise of warrants, and 37.8 million dollars in net proceeds from our equity line of credit with Lincoln Park Capital Fund that fulfilled the 150 million dollar commitment that was originally secured in June of 2022. Subsequently, to the end of the quarter, we received an additional 15 million dollars from the exercise of warrants. Lastly, during the quarter, we fully recovered the one million dollar investment plus accrued interest that we made in Zapata AI in February of 2024 through a convertible note instrument that we wrote off later that year when Zapata became insolvent. As a result of the magnitude of capital that we have recently raised, in addition to pursuing strategic acquisitions, we are accelerating a number of our key investment initiatives. In the area of research and development, your inducting and superconducting bump-bomb process is highlighted in Wednesday, our last Wednesday's press release, and as Alan mentioned earlier. This process will support our multi-chip processor program on our path towards a 100,000 qubit annealing system. This process will also support scalable cryogenic control of fluxonium-based gate model technology. We will also be upgrading our superconducting credit circuit board advanced packaging manufacturing operation and increasing the number and frequency of our wafer fabrication runs to support building advantage through prototypes, as well as continuous improvements to qubit coherence times for both our annealing and gate model architectures. In addition, we will be investing in a number of quantum AI research and development programs. In the area of sales and marketing, we will be expanding the size and geographical footprint of our professional services organization to support growing demand for quantum optimization customer engagements across both commercial and government sectors, including U.S. defense. And lastly, in the area of G&A, we will be making footer investments in our cybersecurity personnel and infrastructure. For the balance of this year, we expect these incremental investments will result in a quarterly non-GAAP OPEX that is approximately 15% higher than our second quarter actual non-GAAP OPEX. To conclude, as we have previously stated, we believe that U-Wave has the opportunity to be the first independent, publicly held quantum computing company to achieve sustained profitability and achieve this milestone with substantially less funding than required by any other independent, publicly held quantum computing company. Given that we are now fortunate enough to have 10 security analysts covering D-Wave, we will in the absence of time ask each analyst to commence the Q&A session with one question, and then we will go back through the queue for additional follow-on questions.

With that, we will now open up the call for questions.

Thank you, ladies and gentlemen. We will now begin the question and answer session. Should you have a question, please press the star followed by the number 1 on your touch-tone phone. You will hear a prompt that your home has been leased. Should you wish to decline from the polling process, please press the star followed by the number 2. If you are using a speakerphone, please lift the handset before pressing any keys. Please note that each person is limited to one question and are welcome to join the queue again. One moment, please, for our first question. Our first question comes from Craig Ellis of B. Riley Security. Please go ahead.

Yeah, thanks for taking the question, and congratulations on the results in the quarter and technical progress, guys. I wanted to start by following up on the point the company has made about M&A and understand the types of M&A that the company believes would make sense, either items that are more technical in nature, maybe helping to accelerate the gate model, side of the business, or things that might be more -to-market oriented, and then what size of M&A makes sense for the company and timely related about. What are we looking at

in terms of timing as we pursue that great angle? Thank you. Hi, Craig.

Thanks for the question. So we have not disclosed our strategy and plans for M&A, other than to say that, you know, with $800 million in the bank, it has now become a strategic priority for the company. That having been said, over the course of the last several months, we have been spending a fair amount of time developing a strategy and a plan, and, you know, it falls into a number of key areas, including some of those that you mentioned. But, you know, think about it as really accelerating our R&D and product development activities in a number of key areas, you know, which could be, you know, everything from

gate model to quantum AI. And anything on timing there, Alan, whether we're looking at something that could be 2025 versus 2025?

It's hard for me to predict, but what I would say is that, you know, our goal would be to, you know, start being able to announce acquisitions this year. However, you know, it takes two to ten, though, and so we'll just have to see how that plays

out. Good luck with the balance. I'll get back to you. Thank you.

Our next question comes from the Vivarolem suspension office. Let's go ahead.

Hey, good morning, everyone, and congrats on the continued progress here. So maybe she could speak to the cryogenic news and the importance of that towards your roadmap and what you think it will bring ultimately as you get that ramped up into the roadmap. Thank you.

Yep, David, thank you. This is really important to us. So we've talked in the past about, you know, how we have significant intellectual property and a real need in cryogenic control, and by that I mean the ability to, you know, control qubits and control our systems on shift rather than needing to do all the control from room temperature. And now as we are looking to leverage that into the gate model program, as well as expanding our annealing processes to much larger numbers of qubits, as we said, 100,000 qubits, we really need to be moving to a multi-chip solution. And, you know, when we start interconnecting chips together in the refrigerator, we need to make sure that that interconnect is also superconducting and that we can preserve the quantum properties, you know, like entanglement across those interconnects. And so, you know, this is key to both scaling our annealing systems as well as developing our gate model systems. And frankly, we made progress in the area much faster than we actually expected to. The non-chip propulsion laboratory had some capabilities that we thought looked interesting. We thought it would take a while to get to the point where we could actually kind of involve that into what we needed, but it actually moved a lot faster than we thought. And so now we're really starting to build a production capability around that technology to more rapidly drive the multi-chip annealing

processes as well as the gate model system. Thank you. Our

next question comes from Troy Denson of Fender Physical. Please go ahead.

Hey, gentlemen. I also wanted to also make a congrats on all the technical problems here. Maybe, you know, for you, Alan, I'd just love to hear more about Advantage 2 and I guess a few things kind of all coupled together. You know, is South Korea the planet? Is that going to be Advantage 2 or are there number systems you expect to install by the end of next year and maybe some of the technical improvements in the platform?

Okay, Troy. So first of all, Advantage 2 is a really important system for us in the sense that it was the first system on which we were able to demonstrate true quantum supremacy, specifically the ability to solve a useful real-world problem on a quantum computer that cannot be solved classically, full stop. It is what everybody in the quantum industry aspires to and we were the first to achieve it and we achieved it on the Advantage 2 system. I will tell you we tried to get this result on our earlier Advantage system and we were not able to. It took the increased capability of Advantage 2 to be able to perform that computation and specifically it required the additional interconnect to more efficiently map the problem into the quantum processor and it also took the longer coherence time and the increased energy scale to get the solutions faster and more accurately. So this is a significant advance over Advantage and we're really excited about it and it's also, I think, driving that increased customer interest that John talks about relative to much larger companies with much larger opportunities that are now engaged with us in a kind of sales cycle process. As far as the number of systems, this falls into two categories. One is our quantum cloud service and we have four production systems in our quantum cloud service today. We don't really need more than that in the cloud service for relatively year-term revenue growth. We likely will add a couple more systems down the road. But four is sufficient for now and obviously all four of those will be upgraded to Advantage 2. Currently one of them has been upgraded. Ultimately all of them will be upgraded. And then there's the on-premise systems and obviously EULIC is one of those and we are already in the process of doing that upgrade as John pointed out. And then as we sell more on-premise systems, those will be Advantage 2 processors. And we said that we've got a really good pipeline for sales of systems. We've got a second one that we're closing in on which is South Korea. We've got another one that's now starting to kind of emerge as a relatively near-term opportunity and then a pipeline of others. But in the past I've had said in the near-term, think more like one in a year than multiple a year. I still say that although I start to feel like maybe it could be a little bit more. But the number is still relatively small in the near-term. So that having been said, if you add up everything that I said, we're talking maybe six or seven Advantage 2 systems.

Perfect. Thanks for the detailed answer and good luck then

for it guys. Thank you.

Our next question comes from Richard Shannon of Craig Hallam. Please go ahead.

Hi, this is Tyler Anderson on for Richard Shannon. Thanks for taking my question guys. So could you elaborate on the developer tools that you released and noting that the problem that you demoed is a classical ML problem. Can users leverage higher pixel images for this? And then also for the sake of time in question, you mentioned control right after your bump bonding. Do you have or plan to have integrated control into your shiplets such that there isn't an external control mechanism?

So Tyler, I will answer your first question to be fair to everybody else because we did say only one question and then you can go ahead and get back into the queue. With respect to what we announced as far as the AI developer toolkit, which I believe is what you're referring to, essentially what we have done is we have introduced the ability to use PySource, which is an open source, Python based machine learning platform that's frankly in fairly wide use for training large language models. And we've introduced into that the ability to use a technology that we have to develop within D-Wave, which is called a discrete variational autoencoder. Now I'm not going to get into the technical details of what I mean by that. Other than to say what this does is allows you to take a data set and map it into a latent space, which is really what machine learning is all about. I think we map it into a machine learning model that can then be used to recreate the data and other things that look like that data set. But what's unique about this is that we're mapping it into a discrete latent space, not a continuous latent space. Machine learning today typically operates on continuous data, but when we're mapping it into a discrete latent space, seeing excellent results with a discrete latent space, but what's so important about that is that our quantum processes natively work with discrete data, not with continuous data. So what this does is it actually opens up the opportunity for the annealing quantum computer to be the vehicle for creating that discrete latent space or doing the learning, which we ultimately think could deliver better models faster and with lower energy consumption. But that having been said, I still want to point out that this is just the next step on our journey in the area of quantum AIs. And there are a number of other things we are working on today in the lab that takes us significantly further than what we've

announced so far that we're very excited about as well. Thank you, appreciate the answer. I'll go back to the cell.

Thanks. Our next question comes from Sergio De Silva of Frost Capital. Please go ahead.

Hi, Allen. Hi, John. I appreciate all the color, the smart quantum AI. Can you talk, Allen, about the next milestones or activities to watch in getting Jewish progress here?

In the area of quantum AI? Correct. I think the short answer to the question is

no, because we haven't yet announced anything beyond what we announced a few days ago. But just to kind of say a little bit, follow up a bit more on what I said a minute ago, you know, there are a number of modern approaches to AI and machine learning model training and inference. Variational autoencoder is one approach, but there are other important things like transformation model, sorry, transformer models and diffusion models. We're working with those as well. And we expect that over time we will be able to deliver a platform that could leverage

our quantum systems in support of all of those approaches. Thanks, Allen.

Our next question comes from Haish Kumar of Library Finder. Please go ahead.

Hey, guys. Congratulations on a lot of progress, advantage too, and other things that you're doing. Allen, I wanted to ask you about the toolkit information you provided in your press release. Is it possible that you could have libraries, kind of like how NVIDIA does, offer to its customers sort of hot finish models that they can, the customers can then take and sort of finish up and customize? Is that sort of the idea or is that even possible with the toolkit for demos reference that you mentioned in your press release and commentary? So,

it's absolutely possible. And in fact, the demo is one simple example of that. However, currently we are working with customers leveraging their data in the application areas that are important to them. You know, for example, Japan, Tobacco, and Triumph, the two that I mentioned a bit earlier, rather than trying to build these out ourselves. The extent to which, A, we take any of that and pull it back into our platform will depend a little bit on the customers and the extent to which we negotiated the ability to be able to do that. And then whether we choose to start pursuing any applications or application templates ourselves is not something that we've certainly not announced it. We've not talked about it. I think that would require us to bring domain expertise in key problem areas into the company. It's something we're thinking about. But honestly, at this point, I wouldn't say we're going to do it. I would just say we're thinking about

it. Understood. Thank you,

Alan. Our next question comes from Kingsley Green, Askanica Agility. First, go ahead.

Hi. Thanks for taking the question. So quantum annealing really has significant potential with both corporates and nation-states or agencies. I'm curious how the tenor in the U.S. government has shifted specifically with respect to quantum annealing in the past couple quarters and then just any thoughts on DARPA's quantum benchmarking initiatives and if there's an opportunity for annealing within that framework.

Oh my. You really

know how to push my buttons. Okay. Let's start with QBI. The DARPA QBI program is totally focused on gate model, and I think that is a huge mistake on the part of DARPA and the U.S. government. I think that by focusing on gate model, they are totally missing the fact that annealing is the most capable approach to quantum for many of the important problems that the government needs to address, whether it's in the area of defense for things like missile defense or troop resupply or in the area of transportation, for example, things like port logistics or we've done work in the area of wildfire fighting. I mean the truth of the matter is annealing represents, I think not only the best, but the only quantum approach that can address many of the government's hard computational problems. This is back to the fact that many of these are optimization problems which require annealing quantum. I think that's a huge mistake and I would encourage them to maybe not add annealing to the QBI program, but maybe create a second quantum program for non-gate model approaches to ensure that the U.S. government is kind of focused on all the approaches to quantum computing, not just one approach to quantum computing. Now with respect to progress more broadly in the U.S.

Well said. Appreciate the comments, Hank.

Thank you. Our next question is coming from Ruben Roy of FIFA. Let's go ahead.

Yes, thank you. And Alan, I don't need to push your buttons here, but I'm going to ask this question anyway. So, and I guess it's in the context of the M&A commentary that you made and also some of the comments that John made with respect to having conversations with larger customers and sort of getting feedback, I guess, from them. So with all of that in mind, I guess the simple question is, has your philosophy on the timing of when D-Wave might think about bringing a gate model to market changed? Has that accelerated for any reason or no? And if no, kind of, are customer conversations sort of driving you to think that the time frame that you guys were thinking about previously is probably the right time frame? Thank you.

Yeah, that's not pushing my buttons at all. That's just a great, well, they're all good questions and they're all good conversations to have, but, you know, I'm not annoyed about gate model and annoyed about D-Wave. So relative to our gate model program, look, we still believe that A, you will never, never see a commercially viable gate model quantum computer before we have error correction. And then you still need to scale to solve youthful real world problems. And as a result, we're still many years out because, you know, no matter what you hear, you know, from the industry, there are still very hard problems that need to be solved around error correction. It's not just a matter of engineering. And then there are still very hard problems that need to be solved in scaling. It's not just a matter of engineering. And so we do see that it's still a number of years before we will see a scaled error corrected gate model system that is commercially viable. So, you know, for us, though, the focus is on removing the risk. In other words, providing clearer line of sight to being able to deliver that by A, driving the R&D efforts needed and or possibly bringing in house really great things that are going on out there in the industry. And so it's less, I think, about accelerating the time frame and more about kind of being much more concrete on exactly what the roadmap is that will

get us there. I appreciate the detail. Thanks, Al. Our

next question is coming from Kevin Garza, a Fresno Black Securitas. Let's go ahead.

Yeah. Hey, Alan and John. Thanks for taking my question. I'm going to switch gears a little bit. And

you mentioned

you

signed renewing customer

engagement. And

can

you give us a sense of what your retention rate is? And the customers that you renew,

have they typically already had another application in mind that they want to use your quantum annealer for? Or does the team show them, you know, how else they can benefit from quantum and

that kind of renew engagement?

John, you want to talk about the retention rate and then I can provide color on kind of how we grow with our customers?

Sure. Our average retention rate going back over approximately like a four quarter period is in excess of 90 percent.

So we do have a very high retention rate. You know, we've talked a little bit about this in the past. You need to keep in mind that we have two different types of quantum computers to service customers. There are customers that you call do it yourself or they come in and buy some assets as developers team and start kind of exploring, doing research, trying to develop applications on their own. And these customers tend to just continue to renew quarter after quarter or year after year. But, you know, haven't been, you know, kind of growing or converting from experimentation to actual production applications. And so, you know, one of the things we are focused on is, you know, how to help them move faster into production. But not all of them are even kind of at the stage where it did make sense to do that. I mean, some of them are research organizations. It should never convert to production applications. And some of them are smaller organizations that really are just experimenting. So, rather, it's kind of really understanding who those do it yourself customers are and focusing on trying to engage them with, you know, kind of help to move forward. And in some sense, the quantum launchpad program was put in place in part specifically to do that, to move those customers off of just doing it yourself into the launchpad program where, you know, it comes with some support from our professional services team. The other class of customers is the customers that have engaged us through a professional services engagement. And, you know, those are the class of customers that, as John said, it's much larger customers that are engaging us now with much larger projects. For example, that aerospace company, I mean, a 4500 company, we engaged us on 12 different applications from the outset. We did the evaluation and are now working on the first of those applications with a plan to move through all of them and then take it to other aerospace companies. So, you know, our approach now really is to work with these larger companies to really kind of find a flagship customer in each industry or vertical area, work with them the way we did with this customer, and then as we're helping them progress through the applications, take that out to other customers in the

same industry and so on. Okay, that makes sense. I appreciate the color and I'll back in the queue.

Thank you. Our next question is coming from Craig Ellis of VRI with Security. Please go ahead.

Yeah, thanks for taking the follow-up question. I wanted to follow up on my first question to take it in a different direction. So, clearly there's a lot of business model flexibility you now have with a much higher cash balance. And one of the things you can do is organically invest a greater amount in R&D and marketing. What I'd like your help on is understanding how you're evaluating current intensity versus higher levels. And what we should expect is you evaluate where you can go with internal investment to accelerate your path to further commerciality, especially with this growing portion of Fortune 500 global,

2,000 customers in your pipeline. Thank you.

Yeah.

First of all, we had in the past said that we are investing in the market. We made it significant for us investment in the sales portion of -to-market sales and technical account management as we over doubled the size of that team in the first half of this year. And now, as John said, we're focused on building out the professional services team in support of that. But, you know, we're also taking it a definite time. So, you know, we made an investment and the pipeline looks good. We're making progress. It's taking a little bit longer to get these deals closed than we had expected because of the size of the customer and the complexity of the processes involved. But we're making good forward progress. And we want to see that we're getting a return on that -to-market investment. And then once that's invalidated, we'll continue to grow there. On the R&D side, we also are starting to make some additional investments in R&D. We talked about the advanced cryogenic packaging work. We talked a little bit about quantum AI. These are areas where we are starting to make some incremental investments. And, you know, beyond cryogenic packaging and its impact on both an alien aid, there will be incremental investments on the gate model side as well as we continue to kind of work through all the technical elements and R&D elements of that program. And John kind of gave you a metric to think about with respect to, you know, an increase in spend

throughout the remainder of this year. Got it. Thank you very much, Helen.

Thank you. We also have a follow-up question from Craig Shannon, from Richard Shannon of Craig Hallam. Please go ahead.

I think you've retaken my follow-up. So I had noticed that Triumph had mentioned using Advantage 2 in their upcoming research. Are you in talks with them for a fair little QQ? Is this someone who you have recently been talking to or you have mentioned that you have been talking to, Veltro? So Triumph

is actually working with our system today, and they have seen really good results leveraging our system to do basically generative AI around, you know, particle acceleration problems that they're dealing with. We've talked about them in the past. We've talked about the work that they're doing. I mentioned them a little earlier. So they are a customer. They are working with our system. They are working with our system in the area of generative AI. They have seen some really good results with that, and we're continuing to grow that relationship with them. As far as the system sale, I haven't really talked about who is in the pipeline and who we're engaged with, other than we have

now begun talking about Yonsei University in South Korea. Okay, thanks. Appreciate the call. Congrats. Thank you. Okay, should we... Go ahead.

Yes, thank you. As a reminder, if you wish to ask a question, please press star 1. If there are no further questions at this time, I would now like to turn the call back over to Alan Barrett for his closing remarks. Let's go ahead.

Thank you, operator. So, as I think you all know, at E-Wave our mission is to help customers realize the value of quantum computing right now. Our second quarter results show continued progress in service to that nation across R&D, go to market, customer application development, and more. Everything we build is designed to provide lasting value for our customers and shareholders, and the future looks very bright. So, thank you all for taking the time to join us today.

Ladies and gentlemen, this concludes today's conference call. Thank you for your participation. You may now disconnect.