Greetings and welcome to the IonQ Fourth Quarter and Full Year 2023 Earnings Call. As a reminder, this conference is being recorded. I'd now like to turn the conference over to your host, Jordan Shapiro. Thank you and you may proceed.

Good afternoon, everyone, and welcome to IonQ's fourth quarter and full year 2023 earnings call. My name is Jordan Shapiro, and I'm the Vice President of Financial Planning and Analysis and Head of Investor Relations here at IonQ. I am pleased to be joined on today's call, here in Seattle, by Peter Chapman, IonQ's President and Chief Executive Officer; Thomas Kramer, our Chief Financial Officer; Dean Kassmann, our Vice President of Engineering, as well as Pat Tang, our Vice President of Research and Development. By now, everyone should have access to the company's fourth quarter and full year 2023 earnings press release issued this afternoon, which is available on the Investor Relations section of our website at investors.ionq.com. Please note that on today's call, management will refer to adjusted EBITDA which is a non-GAAP financial measure. While the company believes this non-GAAP financial measure provides useful information for investors, the presentation of this information is not intended to be considered in isolation or as a substitute for the financial information presented in accordance with GAAP. You are directed to our press release for a reconciliation of adjusted EBITDA to its closest comparable GAAP measure. During the call, we will discuss our business outlook and make forward-looking statements. These comments are based on our predictions and expectations as of today. Actual events or results could differ materially due to a number of risks and uncertainties, including those mentioned in our 10-K that we have filed with the SEC today. We undertake no obligation to revise any statements to reflect changes that occur after this call, except as required by law. Now I will turn it over to IonQ's CEO, Peter Chapman. Peter?

Thank you, Jordan, and a warm welcome to everyone on the call, including our two new board members. We are most proud to have attracted new directors of such caliber and stature. This past year, 2023 was a landmark period in IonQ's journey. It is with immense pride and enthusiasm that I announced we've yet again closed the year on a high note. IonQ had a strong fourth quarter, generating $6.1 million in revenue to bring our full year recognized revenue to just over $22 million, beating the upper end of our projected range. I am delighted to report that we have surpassed our annual bookings guidance, achieving $65.1 million in bookings for the year and greatly exceeding the bookings midpoint of $40 million we said at the beginning of 2023. This accomplishment has propelled us past our ambitious target of $100 million in cumulative bookings within our first 3 years of commercialization as announced 2 years ago. It's a testament to the exceptional performance of both our technical and commercial team. Thomas will walk you through the numbers in more depth. So today, I would like to try something slightly different for our earnings call. I hope to give you a sense of how much has evolved for quantum computing in the last 3 years since IonQ went public and why you should be paying close attention to IonQ now. Specifically, I will explain IonQ's potential in supporting the AI industry, provide insights on when we expect quantum computing to deliver a commercial advantage, and share how this contributes to our market opportunity in 2024 and beyond. Back in 1981, in his seminal lecture 'Simulating Physics with Computers', Richard Feynman said these memorable words: 'Nature isn't classical, dammit, and if you want to make a simulation of nature, you better make it quantum mechanical. And by golly, it's a wonderful problem because it doesn't look so easy.' Underlying his insight was the realization of three facts. Number one, the real world is neither digital nor analog but quantum. Our quantum reality deals heavily in probabilities, not just deterministic answers. The natural world is governed by quantum mechanics, which ultimately describes the behavior of everything through a strange world of small particles where entanglement and superposition rule. Quantum mechanics, quantum probability, and quantum statistics give us new and exciting tools to solve high-value problems. Feynman's second insight was that it was difficult for digital computers to simulate anything quantum. We can see that today in action. The GPU with 80 gigabytes of memory can simulate 32 qubits. However, every time you add a qubit to that simulation, it doubles the GPU memory required. As a result, to fully simulate 64 qubits, you would likely need 3.6 billion GPUs. We recently announced that using IonQ Forte, we hit our 2024 technical milestone of 35 algorithmic qubits or AQ, a full year early, placing us beyond what can be simulated on an 80-gigabyte GPU. And with our upcoming Tempo system, we expect to deliver AQ 64, anticipating that the market for classical machines running quantum simulation will no longer be able to keep up. Feynman's third insight is that there are a set of problems that consume compute resources at an exponential rate and which classical computing will likely never be able to solve, even with Moore's Law and the advent of both GPUs and CPUs. I will note that large language models underpinning generative AI are on this path. These models are starting to change the world, becoming the new foundation for our interaction with AI. While so many of us have spent time using ChatGPT, we might not all be aware of the enormous resources required to bring this technology to light and to operate it classically. IonQ customers have recently reported that training the latest LLMs takes 30,000 servers, each with 8 GPUs. It takes upwards of 3 months and $1 billion to train a single model. My intuition is that the main reason for this is that human intelligence, the way our brain thinks and processes the world around us, could be a quantum process and not a classical one. If that is the case, it would take enormous compute resources to try to replicate this quantum process with classical computers. These dramatic compute requirements explain why Sam Altman is now talking about the urgent need to increase the electrical output of the world, so he can power more classical data centers. This line of thinking suggests that the only way to build the next generation of AI is to fill our planet with data centers. What you're seeing is that our need for computational power is exceeding what is reasonable. Feynman made this realization back in 1981. This is why IonQ fully intends to pursue the artificial intelligence market. We expect to do this in several forms as our technology matures. In the near term, you'll hear examples of how we continue to invest in applications of quantum machine learning, such as predictive maintenance and computer vision. Next, we are actively exploring ways to use quantum to supercharge LLMs, which is a fertile area. Lastly, we are looking at new ways to build strong AI for what we think of as truly intelligent machines without LLMs. If we increasingly build our society around AI, quantum computing may be the only way, or one of the only ways, to power all that compute. Bloomberg projects the degenerative AI market to reach a market size of $1.3 trillion within the next 10 years. Replacing even a fraction of the resulting compute load would represent significant revenue for the quantum industry and a meaningful reduction in energy consumption for our planet. We need to augment today's computers with a different technology trend that will drive the next wave of innovation. Quantum computing is starting to demonstrate all the necessary pieces. In short, this is why something IonQ has the potential to be one of the world's most important technology companies. It's also why today's leading players, Google, Amazon, and Microsoft, among others, are all collaborating with IonQ on quantum computing. In a short 3 years, the question on most investors' minds has changed. It is no longer if quantum computing will change the world but exactly when it will. The answer lies where three trend lines intersect. The first trend represents progress in quantum computing hardware itself and the growth of computational power. The second trend represents progress in software development that reduces the computational power needed to run quantum applications. And the third trend is the reduction of cost and time to produce our quantum computer. This intersection is when we believe we will unlock the first commercial applications for quantum computing. Taking hardware progress first, when we announced last month that we had surged from AQ 29 to an impressive AQ 35, a full year ahead of expectations, we catapulted our computers from being able to consider about 500 million simultaneous possibilities to over 34 billion. Today, I am excited to share that we've actually gone beyond that and achieved AQ 36 on IonQ Forte. In a matter of weeks, we improved from AQ 35 to AQ 36, effectively doubling the computational space of our systems to simultaneously consider over 68 billion alternatives. This illustrates the exponential progress we're seeing in hardware performance. At AQ 64, we expect Tempo will have a computational space more than 500 million times that of Forte Enterprise and will do so with an even smaller footprint. Tempo will be built here in Seattle. In the future, our design goal is to fit our quantum computers into a single standard data center rack. Within that rack, we intend to network several quantum processors or QPUs together to allow access to thousands of physical qubits for error correction. Our goal is to increase the gate speeds by several orders of magnitude, allowing much larger quantum algorithms to run efficiently. Forte Enterprise and prior systems use a series of bulky mirrors and lenses to direct laser beams. Future IonQ systems will route light using photonic integrated circuits or PICs. This technology has several significant advantages, including that we expect the size and cost of our systems to shrink and for fidelity to improve as well. I am thrilled to announce today that we have our first PICs working in a lab setting, demonstrating that the engineering process is now possible at IonQ. Last week, we shared that we have officially demonstrated the first critical milestone for photonic interconnects at IonQ. We can now reliably entangle a qubit with photons to enable communication. Later this year, we expect to show that we can connect multiple qubits together across QPUs and that those connected qubits can be used for distributed quantum computation. We envision connecting the QPUs in our next-gen systems with photonic interconnects. So, our first trend line and our technical roadmap shows that quantum hardware will be ready for commercial applications in 2 to 3 years. If quantum hardware progress is accelerating at an impressive pace, then quantum algorithmic development is moving even faster. To spot these early signs of commercial advantage, you need to keep a close eye on developments not just here at IonQ but in the broader quantum industry as well. Let me provide you with a few examples. Thompson Machinery, a Caterpillar dealer serving parts of Tennessee and Mississippi, is working with IonQ on developing quantum AI models for predictive maintenance. Together, we tasked an IonQ quantum machine learning model with detecting potential failures in the company's fleet of bulldozers and compared it directly to a classical model. The quantum model was more likely to detect failures, did so with more precision, and promises to be economically significant. In a recent collaboration with Hyundai Motors on image classification, our quantum algorithm was 5 to 6 times more efficient than its classical equivalent and yielded the same accurate results. BCG recently estimated the market for quantum automotive solutions at upwards of $10 billion. Meanwhile, in a recent project that we will share more about with the forthcoming paper, the quantum machine learning algorithm for chemical manufacturing was up to 75% more efficient than its classical equivalent and demonstrated potential cost savings for users. According to BCG, quantum chemistry applications could have a market size of up to $50 billion. Quantum algorithms are beginning to show advantages over their classical counterparts. This speaks to an important trend that industry insiders are noticing. Each day that we continue to work on quantum, we make progress in making the algorithms more efficient. Just last month, the quantum algorithms company published research showing they could reduce a complex material simulation requiring 1.5 trillion gates down to requiring only 410,000. That's a factor of four million times improvement, putting the algorithm within the near-term range of quantum computers. Over the last several years, algorithmic work to find ways to do more with a smaller number of qubits is progressing at a much faster pace than the hardware itself. This is happening across a wide variety of application areas. While yesterday it seemed years away, suddenly, it is within reach due to the hard work of quantum developers. This means that even with more sophisticated IonQ hardware in the pipeline for 2 to 3 years from now, it is possible that software innovation will support commercial quantum applications even sooner. If you look at all the work we've done with customers over the last 3 years, a picture emerges. One of the particular strengths of quantum computing is machine learning. We said this years ago, and now the world has the data to back it up. As proof points, we have shown that quantum and ML models are more expressive and capture the signal better in the underlying data. We have shown that we can create equivalent or better quantum models than classical models using less data. We have shown an ability to dramatically reduce the number of iterations required to train those models using quantum. And we are now showing that quantum computers can work with sparse data where classical computing may have limits or just wouldn't work. The third critical trend is the increasing product maturity of quantum computers that is making them smaller, cheaper, faster to produce, and more reliable. With the help of U.S. Senator Maria Cantwell from the State of Washington, we recently inaugurated our Seattle manufacturing facility which will support these product roles. We are dialed in from that facility this afternoon. We are only a few feet away from the manufacturing floor, where our first Forte Enterprise systems are being assembled to fulfill rising customer demand. We're also announcing that we've already decided to increase our footprint in the Seattle facility by 50%, given how encouraged we are by the progress we're making and the demand we are anticipating. Speaking of that demand, last year, we announced our intention to capture two quantum markets: computing and networking. Compute hardware customers today, such as Quantum Basel, are looking to jump-start their local quantum economies with on-prem access to the latest cutting-edge systems. Networking customers like the U.S. Air Force Research Lab are interested in communication between quantum systems. Regarding quantum communication, we worried that a rapid advancement in quantum decryption, similar to the other algorithms we discuss tonight, would put the world at significant risk. The Internet is already under attack. You can no longer tell if a photo, video clip, or audio clip is real. Imagine a world where truth itself is under attack and nothing can be trusted. One of the reasons we're getting into networking is because we believe the world will soon need a quantum-safe network. Just last week, Apple, the world's largest consumer company, announced that it was taking preemptive steps to defend itself against impending quantum security effects. BCG has approximated the size of the quantum security market at upwards of $80 billion. We believe that between networking and computing, these solutions will need potentially millions of pieces of hardware. That's a sizable opportunity for quantum manufacturers. On the corporate front, it is my pleasure to announce two new members of the IonQ Board of Directors, who will help us accelerate our commercialization and capture these markets. Robert Cardillo is the former Deputy Director of the U.S. Defense Intelligence Agency and previously served as a National Intelligence Adviser to President Obama, driving the President's Daily U.S. intelligence briefing. With 40 years of intelligence experience, Robert will play an integral role in expanding IonQ's relationship with federal agencies, helping us to meet the unique needs of government customers. Bill Scannell is the President of Global Sales and Customer Operations at Dell, where he oversees an organization of nearly 24,000 sales team members delivering technology solutions to over 180 countries worldwide. Bill brings to IonQ decades of sales experience and will provide critical insights into our sales strategy, helping to strengthen our leadership in the quantum economy. IonQ's leadership is bolstered by our technical expertise, and we want to remind our investor audience that IonQ has a relationship with Duke University, where we have an agreement to exclusively capture royalty-free all intellectual property generated that pertains to trapped ion quantum computing. That agreement continues to contribute valuable IP to IonQ. Our co-founders, Drs. Chris Monroe and Jungsang Kim, are both professors at Duke, where they are the cornerstones of the Duke Quantum Center. At the end of this quarter, Jungsang will transition out of his post as our CTO at IonQ to turn more of his attention back to his academic duties at Duke. He will continue to advise IonQ on trapped ion quantum computing as a scientific adviser and serve as a resource for IonQ's most senior technical executives, including Dr. Dean Kassmann, our VP of Engineering; Dr. Pat Tang, our VP of Research and Development; and Dr. Dave Mehuys, our VP of Production Engineering. In summary, we had a fantastic quarter and full year 2023. Heading into 2024, IonQ is focused on supporting the AI industry, seeing hardware, software and production improvements that bring us closer to near-term commercial advantage, and ramping up to capture a sizable and growing pipeline across quantum compute, networking, and AI. With that, I would like to turn the call over to Thomas.

Thank you, Peter, and thank you to everyone joining us today. With no further ado, let's walk through this quarter's financial results in more detail. As Peter mentioned, we had an excellent quarter and year, recognizing $6.1 million in revenue. For the full year, we ended with $22 million in revenue, above the high end of our updated guidance range and up 98% year-over-year. We ended the year with $65.1 million in bookings, which was also above the high end of our updated guidance range for 2023 and up 65% year-over-year. Given that we are still at the beginning of our commercialization phase, I want to reiterate my comments from our last earnings call that we expect bookings to continue to be lumpy for quite some time. Moving down the income statement, for the fourth quarter of 2023, our total operating costs and expenses were $60.6 million, up 121% from $27.4 million in the prior year period. For the full year 2023, that number was $179.8 million, up 86% from $96.9 million in 2022. To break this down further, our research and development costs for the fourth quarter were $31.6 million, up 131% from $13.7 million in the prior year period. For the full year 2023, that number was $92.3 million, up 110% from $44 million in 2022. We call that we are investing heavily in R&D and are increasing our production of our systems to meet projected customer demand. Our sales and marketing costs in the fourth quarter were $7 million, up 189% from $2.4 million in the prior year period. For the full year 2023, that number was $18.3 million, up 118% from $8.4 million in the full year 2022. This increase was due to us growing our go-to-market function as we continue our investment in our commercialization efforts, and we expect that trend to continue as we further expand our sales initiatives. Our general and administrative costs in the fourth quarter were $15.3 million, up 69% from $9.1 million in the prior year period. For the full year 2023, that number was $50.7 million, up 41% from $36 million in the full year 2022. Stock-based compensation was $69.7 million for the full year 2023, up from $31.5 million in the full year 2022. All of this resulted in a net loss of $41.9 million in the fourth quarter compared to $18.6 million in the prior year period and a net loss of $157.8 million for the full year 2023 versus $48.5 million in 2022. It is important to note that these results include a non-cash gain of $7.6 million for the fourth quarter related to the fair value of warrant liabilities and $19.2 million in non-cash loss for the full year 2023. We saw an adjusted EBITDA loss for the fourth quarter of $20 million compared to a $13.3 million loss in the prior year period, and a loss of $77.7 million for the full year 2023 versus $48.7 million for 2022. Note that we projected an adjusted EBITDA loss for the year of $80.5 million and have announced $77.7 million in actuals, once again beating our expected plan. Turning now to our balance sheet. Cash, cash equivalents and investments as of December 31, 2023, were $455.9 million. We are confident in our cash position, which positions us well to continue executing against our technical roadmap. Looking forward to our full year 2024 outlook, we are introducing a first quarter revenue target of between $6.5 million and $7.5 million, and we are projecting revenue of between $37 million and $41 million for the full 2024 fiscal year. Additionally, we anticipate bookings of between $70 million and $90 million for 2024. We remain highly confident in our pipeline, but our bookings range acknowledges the unpredictability of U.S. government investment in quantum, given the uncertainty of the federal government's fiscal year 2024 budget process. Finally, we anticipate an adjusted EBITDA loss of $110.5 million for the full year 2024 at the midpoint of our revenue guidance. And with that, I would like to turn the call back over to Peter for some closing remarks.

Thank you, Thomas. 2023 was another fantastic year for IonQ. We exceeded expectations on both technical and financial performance, expanded our Board and executive team, brought our production facility online, increased its footprint to meet increasing demand, and set this stage for IonQ's continued growth. The quantum market is truly heating up, and we believe it is only a matter of time before we hit quantum's ChatGPT moment and catalyze the next wave of world-defining companies across quantum computing, networking, and AI. In other words, if you think about who IonQ wants to be in the coming years, it is NVIDIA, Cisco, and OpenAI all in one. And with that, operator, I'd like to open the line for questions.

The first question comes from Joe Moore from Morgan Stanley.

I wonder if you could elaborate on AQ 64 next year potentially exceeding the limits of classical simulation. When do you anticipate the general public will realize this? It seems we still encounter questions about quantum technology with timelines stretching several years into the future. I understand you believe your technology can accelerate this process. At what point can you showcase that capability and potentially stimulate greater investment in the quantum sector?

Joe, great question, and I think it is the kind of the number one question for investors. It's interesting, just looking at simulating our quantum systems alone. We happen to be at a place where going from AQ 35 now to AQ 36 and going to 64, the number of GPUs that would be needed to simulate what we're doing has increased significantly. So it's already a kind of proof point that says it's increasingly becoming difficult to do what it is that we're doing in a classical way. There's not a huge market for classical simulation of what we're doing. So it's a technical proof point but not a business one. But I do think that we will see within this time period when we get to 64, a number of different applications. We are currently working on early projects to build applications that will take advantage of our own hardware, and we are increasingly engaging with other quantum developers to prepare them for this level of computational power. Timing-wise, as I mentioned in today's script, you need these three things to come together. We think it's roughly in that kind of 2 to 3-year period for all three pieces to converge where we will really start to see major adoption. I liken it to what we refer to as the 'ChatGPT moment,' as that marks a period when things really take off. I believe there will be indicators along the way. There's potential for breakthroughs at any moment, and we've seen improvements from others in the field that allow for more efficient use of resources.

The next question comes from Quinn Bolton from Needham & Company.

Congratulations on the strong finish to '23 and nice outlook for '24. I guess first, maybe for Thomas. Just talk about the bookings in Q4. How diversified were those bookings? Were there any hardware components or systems in that fourth quarter number? And then maybe a similar question, looking into the $70 million to $90 million bookings guidance. Can you give us a sense of the split between hardware or system sales versus more QCS or development or professional service type contracts?

We did not have any hardware-related bookings in Q4. However, you can tell from two things that we are absolutely expecting to see that in '24. Number one, it's a high bookings number which comes from the fact that our systems sell at a very high price, but very much worth it. The other thing is that you can see from the range of $70 million to $90 million is a wide range, and it’s indicative of the fact that our bookings are high, so you could easily see a swing when something flips from one quarter to the other. We are not yet guiding to the difference between hardware and software and services, but you should expect that our hardware will outperform in terms of the bookings weight compared to the other categories.

Just as a clarification, when we say hardware here, we will assume we're referring to hardware sales of systems. Of course, there is hardware compute time in terms of actual time. So if you look at the fourth quarter, it would be a mixture of selling time on systems and application development, but we did not sell a system in the fourth quarter.

That's correct. Ultimately, we do sell compute, and when we sell a system all at once, it is just an aggregation of lots of small compute engagements at one time.

Exactly.

Got it. And then how much I'm not sure if I'll get you to answer this question, but I'll ask it. You're guiding to an EBITDA loss of $110 million, $110.5 million. As you look forward, obviously, I would expect probably if we look at '25 and beyond revenue continues to grow. My question is, do you think EBITDA loss peaks in 2024 and starts to come down in future years? Or is it too early to call what year EBITDA loss might take?

We look forward to coming back to you with projections for '25 on the Q4 call. What we can tell you is that we are very happy with the investments that were made. We're currently in our new executive briefing room in Seattle, preparing to make more sales both domestically and internationally, and we are very pleased with how the funnel is looking.

The next question comes from David Williams from Benchmark Company.

Peter, thank you for your insightful comments. Could you discuss the challenges you face in becoming more commercial? Can you break that down further and share your insights from a government perspective, as well as from nongovernmental entities? Is there an increase in interest there, particularly in relation to the advancements you've made with your quantum algorithmic qubits?

Yes. In terms of kind of the top of the funnel, one of our reasons we're pretty happy at the moment is international interest seems to be particularly strong, maybe even stronger than domestic, in terms of government collaboration. That's one area where we see strength. As we have mentioned, we are hedging a little bit because we don't know yet whether Congress will pass a budget bill this year, so we have to see how that unfolds. But roughly speaking, when I look at the top of the funnel, there's roughly equal interest between commercial and government opportunities. There is heavy interest in the enterprise as well.

I wanted to ask real quick about Jungsang and his departure from his current role. I recognize the transitions happening here, but just curious if you can provide maybe a little bit more color or the thought process going forward. I know that we've made it through a lot of the hurdles, but it seems like there’s still a lot of work to do, and just wondering if that’s going to impact the business going forward.

That's a great question. I’m sure there’s a lot of energy around topics like this. When I started here five years ago, there was Chris, Jungsang, and me. We were running on QuickBooks at the time, and management was quite light. At the beginning, Chris and Jungsang were professors and still are. We have this relationship with UMD and Duke, where we capture IP that they generate at their universities through this exclusive arrangement which is royalty-free to the company. At first, the question was how to start the company while keeping this relationship intact. Jungsang came to help at IonQ, taking a sabbatical from Duke. Chris moved to Duke to run what is now the Duke Quantum Center. We had a small focused team, and over the years, we built a complete management team capable of directing operations. Jungsang's move back to Duke now reflects the company’s maturity. He will still be involved, contributing insights as a scientific adviser, but we have a solid team in place to lead operations moving forward.

The next question comes from Shadi Mitwalli from Craig-Hallum.

This is Shadi Mitwalli on for Richard Shannon. Congrats on a solid year, guys. Maybe a question for Peter. In your prepared remarks, you mentioned the potential to increase the speed of qubits by many orders of magnitude. Ion traps are known to be somewhat slower than other qubit modalities. How do you expect to accomplish this? Is this with the same barium qubits your forthcoming systems will use?

I'll tell you we have Pat here, who is currently working on it. So I'm going to let him answer.

Right. The two research paths we're taking include optimizing the current gate schemes we have, which rely on motional modes in the ion chain. We also have another modality being examined that uses gate-switch interactions electromagnetically. This would potentially lead to real speed increases in gate times. We are making good progress here and aim to share more about this in forthcoming quarters.

And just one more follow-up. What milestones should we look for in terms of progress and timeframe for success in quantum networking between QPUs in your AQ 64 system?

Once again, we’ll redirect to the tech team here. Pat, please go ahead.

Yes. Photonic interconnects are really beyond AQ 64. I'm happy to report that we've made good progress here, and we are on track to complete the photonic interconnect project this year. We have customers very interested in this technology, as it is our method of scaling QPUs beyond AQ 64. This is a very important technology for us and we're making great strides.

To add to that, we don't think we will need photonic interconnects to achieve AQ 64 functionality. So while it is an active area of research, we expect to see our first demonstrations by the end of this year.

The next question comes from David Williams from Benchmark Company.

I just want to ask real quickly. Are those photonic interconnects going to be system agnostic in terms of the technologies they're working with? Or do they require your hardware specifically?

So in principle, the architecture itself can be agnostic. However, we are using a barium system, as you know. The hardware we developed is specifically for barium and this requires a special set of lasers and special optics geared toward that wavelength. So while the architecture can apply to different modalities, our current technology is tailored to our specific trapped ion setup.

The next question comes from Kevin Garrigan from WestPark Capital.

Congrats on the progress, and I apologize if any of these questions have been answered; I joined a little late. Can you give us a sense of the new customers you are starting to talk to—do they know what problems they're trying to solve? Or is there still a major teaching component where you have to help them understand what they're trying to do and how quantum computing can help?

That's a difficult conversation, or complex, I guess. Yes, there's probably a full spectrum of those inquiries. We try not to engage too much in educational work or POC discussions. Generally, our customers tend to be somewhat more sophisticated in the quantum compute space. You find other companies might have many customers doing numerous engagements, we don’t stray into small deals. That said, sometimes we do get customers early in their quantum journey, but overall, clients generally have a good understanding of the pressing problems they face and are coming to us with specific questions about whether we can resolve their issues.

That is very helpful. As a follow-up, can you talk a bit about the competitive landscape? It seems like nearly every week or month a new quantum computing company emerges. Are you seeing any increased competition in the market?

You're absolutely right; I see it too. There appears to be breakthroughs occurring constantly. If you follow these advancements from universities, the journey to a finished product typically requires significant investment and years of development—often around $1 billion for most qubit technologies. IonQ, I believe, is not only the best funded, but our focus on building a manufacturing plant truly places us ahead of the competition. I’ve stated before and have no qualms about saying it: there may be other qubit modalities that outperform IonQ in the future. However, in the next 5 years, we believe we have the edge, coupled with a revenue-generating model that enables us to explore other approaches down the road. Currently, the competition does not concern us.

Ladies and gentlemen, we have reached the end of the question-and-answer session. I'd now like to hand over the call to Peter Chapman for closing remarks. Thank you, sir.

I want to thank everyone for joining our call today and, of course, thank our team for all their hard work and our shareholders for their support. We look forward to speaking with you soon and updating the entire financial community on our next earnings call. Thank you, everyone.