IonQ, Inc. (NYSE:IONQ) Q4 2023 Earnings Call Transcript

IonQ, Inc. (NYSE:IONQ) Q4 2023 Earnings Call Transcript February 28, 2024

IonQ, Inc. isn’t one of the 30 most popular stocks among hedge funds at the end of the third quarter (see the details here).

Operator: Greetings and welcome to the IonQ Fourth Quarter and Full Year 2023 Earnings Call. [Operator Instructions] 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.

Jordan Shapiro: 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?

Peter Chapman: 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 pass 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 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 describe the behavior of everything via a strange world of small particles where entanglement and super physician 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 doubled 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 that we expect will deliver #AQ 64, we anticipate 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. And 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 to train 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 reasons for this is that human intelligence, the way our brain think and process 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 would suggest 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 now 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. And 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 the 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, unable to share that we’ve actually gone beyond that and have 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 considering 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 the 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 beam.

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 which demonstrates 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, 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 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 6x 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 would be 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. That speaks to an important trend that industry insiders are noticing. Each day that we continue to work on quantum, we make progress on 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 4 million times improvement, putting the algorithm in 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. And this is happening across a wide variety of application areas.

While yesterday it seemed years away, suddenly 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, it’s 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 pre-emptive steps to defend itself against impending quantum security effects. BCG has approximated the size of the quantum security market and 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 Intelligent 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 on 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, doctors 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 is seeing hardware, software and production improvements that bring us closer to near-term commercial advantage and is 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.

Thomas Kramer: 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 road map.

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 that 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.

Peter Chapman: 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 is NVIDIA, Cisco and OpenAI all in one. And with that, operator, I’d like to open the line for questions.

Operator: [Operator Instructions] The first question comes from Joe Moore from Morgan Stanley.

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Q&A Session

Joe Moore: I wonder if you could just — you talked about #AQ 64 next year kind of breaking beyond what can be done with classical simulation, like at what point will the broader world become aware of that? Because I feel like we still — we ask questions about quantum and we still get timeframe being several years away and I understand you think your technology gets us to quicker. But at what point can you demonstrate that capability where you might expect there to be quite a bit more kind of a pickup in investment in the quantum area?

Peter Chapman: 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 between 35 now 36 and going to 64, the number of GPUs that would be needed to simulate what is we’re doing. And so it’s kind of already that kind of proof point that says it’s increasingly becoming difficult to do what it is that we’re doing in a classical way. So now 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 have a bunch of things that we’re working on right now in terms of early work to build applications, so we’ll take advantage of our own hardware and increasingly talking with other quantum developers getting them ready for having that kind of computational power.

So it’s timing, as I kind of mentioned in today’s script, you need these 3 things to come together. And we think it’s roughly in that kind of 2 to 3x year period for all 3 pieces to come together where really, really starts to take off. It has, as I kind of said, the ChatGPT moment is when it really starts. Now, I think you’ll see Telltale signs along the way. And there’s potential for like, as I said today, the algorithmic improvements, somebody had a breakthrough. There’s potentials along the way to do more with less. And that seems to be the history of the industry as well. And it seems just like every other day, there’s somebody that comes out and announces they’ve managed to optimize the hell out of one particular algorithm and now need a lot less resources.

So we could have a surprise too. It’s kind of when we’re predicting the future, it’s kind of difficult to do.

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

Quinn Bolton: Congratulations on the strong finish to ’23 and nice outlook for ’24. I guess first, maybe for Thomas. Just talk about the bookings in ’20 — in the fourth quarter, how diversified where 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 what’s the split between hardware or system sales versus more QCS or development or professional service type contracts?

Peter Chapman: We did not have any hardware-related bookings in Q4. However, you can tell from 2 things that we are absolutely expecting to see that in ’24. Number one, it’s just a high bookings number which comes from the fact that our systems sell at a very high price. But very much worth it. And the other thing is that you can see from the range, like $70 million to $90 million is a wide range and that’s representative of the fact that our bookings are high. And 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.

Thomas Kramer: And just as a clarification, when we say hardware here, we’re going to assume we mean hardware sale 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 applications development. So I think what we’re trying to say here is we didn’t sell the system in the fourth quarter.

Peter Chapman: That’s correct. Ultimately, we do sell compute. And when we sell a system all at once, it just is an aggregation of block small compute at one time.

Thomas Kramer: Exactly.

Quinn Bolton: 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 ’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?

Thomas Kramer: We look forward to coming back to you with projections for ’25 on the Q4 call. But what we can tell you is that we are very happy with the investments that were made. We’re sitting now in the new executive briefing room in Seattle. And we are getting ready to make more sales, both domestically and internationally and we’re very pleased with how the funnel is looking.

Operator: The next question comes from David Williams from Benchmark Company.

David Williams: Peter, thanks for all the great color in your script there. I guess maybe can you talk about the hurdles that you see in front of you in terms of becoming more commercial. And maybe if you could dissect that a bit and talk about where you’re seeing from a government perspective but also what are you seeing from maybe nongovernmental entities? Are you — is that really beginning to pick up? And are you gaining interest there, specifically kind of related to the progress you’ve made on your quantum algorithmic qubits?

Peter Chapman: Yes. So, in terms of kind of top of funnel is one of our reasons we’re pretty happy at the moment is I’d say is international seems to be particularly strong, maybe even stronger than domestically in terms of government. And so that’s one area which is of strength. As we kind of mentioned in this, we’re hedging a little bit because we don’t know as to whether or not Congress will pass a budget build this year. So we have to see how that goes. But I would say kind of roughly at the moment, when I look at from kind of top of funnel is there’s roughly equal interest in commercial. And so there’s heavy interest in the enterprise as well.

David Williams: So I wanted to ask real quick about Jungsang and his departure from his current role. And I recognize the transitions that happened here. But just curious if you can provide maybe a little bit more color or maybe just 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.

Peter Chapman: That’s a great question. I’m sure that’s also — there’s always a lot of energy in these topics. So maybe I’ll give you a little bit longer answer which is when I started here 5 years ago, there was Chris, Jungsang and myself. That was it. We’re running on QuickBooks at the time. We had a bookkeeper and it was — in terms of management, it was a pretty light at the top. One of the questions, Chris and Jungsang were professors and still are today. And so 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. And we gave them — don’t quote me on it but about a little under, I think, 0.5% of the company in exchange for that.

And so at the very beginning, the question was how do we start the company and also keep this relationship, this business arrangement we have with universities going. And so Jungsang was going to take a sabbatical from Duke and come to IonQ to help. And Chris was going to — he moved from University of Maryland to Duke to run what now has become the Duke Quantum Center. And that was important to the company because the research that’s going on there is being captured by the company. We have an economic relationship with them. So we have an interest in making sure that that works. And then Jungsang, it was basically Jungsang and myself and I was the business and Jungsang was the tech person and then we started hiring the management team. We got, for instance, Dean to come in, in 2021 to come in as VP of Engineering.

At that point, Jungsang had that role. And then Jungsang left that role because Dean had taken over and Jungsang then went and became VP of R&D. And then we hired Pat last year and then he gave up that role. And then he went over to applications. He was our kind of go-to guy, if you will, for whatever the open role we had in the tech. And then we’ve gotten now to the point where we have a full management team. And the work that’s going over at the Duke Quantum Center is also quite demanding. And so it’s just — it’s kind of we’ve ran to a full course here where basically you saw, obviously, Chris and now Jungsang going back to Duke to run the thing and to be the professors and continue to teach and do all the things that they do. And at the same time, the company now has a complete management team.

And so we’re no longer in QuickBooks or none of those things. So, at some level, somewhat of the maturity of the company. Jungsang is still available, will still be qubitsing combining on next-generation designs and all the rest of those things with the team, that’s not going to stop. So I know it’s a juicy kind of tidbit for people to chew on but it’s just the 2 of them are professors. They — Jungsang taking a leave of absence from Duke to be able to come and join us and we appreciate the time that he was here to be able to do that. But as an example, for #AQ 35, that wasn’t really Jungsang, that was Dean and the rest of the team. The internal engineering group was the ones that kind of really responsible for that. So I don’t want to minimize what Jungsang’s participation because it’s been enormous over the years.

But at the same time, we’ve kind of — we’ve got a pretty good team now to be able. And we have in our management team, 3 PhDs. And the other side is that about 2/3 of our staff also have an academic — an advanced academic degrees. And we strongly have their DNA in the company because in the early days, many of the people that have been here for years now were originally students at either University of Maryland or Duke. And so that continues on as well. So anyway, there’s a long answer to probably what it should be a short question but there you go.

Operator: [Operator Instructions] The next question comes from Shadi Mitwalli from Craig-Hallum.

Shadi Mitwalli: 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 knowing to be somewhat slower than other qubit modalities. So how do you expect to be able to accomplish this? And is this with the same barium qubits your forthcoming systems will use?

Peter Chapman: I’ll tell you, we have Pat sitting here, who happens to be working on it. So I’m going to let him answer.

Pat Tang: Right. So the two research paths we’re taking. One is really optimizing the current gate schemes that we have which, as you know, relies upon motional mode in the high chain. But we also have another modality that we’re looking at as well using gates switch interact electromagnetically. So that would potentially give a real speed up to gate times. So you’re going to be hearing more of that in our forthcoming quarters about that particular research but that’s a very active research and I recognize the point that you made and this has been addressed as we speak right now. And we’re having very good collaborations with different entities to try to attack this issue at all angles but we’re making good progress on this and we’re going to hear more of that this in future quarters to come.

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

Peter Chapman: Once again, we’ll redirect to the techies in the room. So Pat, take it away.

Pat Tang: Yes. So photonic interconnect is really beyond #AQ 64. And I’m happy to report that you’ve probably seen the recent press release, we’re very happy about that progress. And we’re on track to finish the photonic interconnect this year. We actually have customers very interested in this technology. And it’s our method of being able to scale QPUs beyond #AQ 64. So this is a very important technology to us and making great progress on this. And you’re going to hear us — we stated this that we’re going to complete this this year and expect more to come from this year’s reports.

Peter Chapman: So just to add a little bit Julie, just to make sure people understood. So to hit #AQ 64, we don’t think that we need photonic interconnects to be able to make that to work. So — but it is an active area. And as we said, we expect by the end of the year to see the first demonstrations of that.

Operator: The next question comes from David Williams from Benchmark Company.

David Williams: I just want to ask real quickly. Are those the photonic interconnects, will those be kind of system agnostic in terms of — does it matter which hardware you’re working on as long as quantum or is it specific to the trapped ion or your IonQ systems?

Peter Chapman: So in principle, the architecture itself can be agnostic but we are using a bearing system, as you know. So the hardware that we’ve developed is specifically for the barium and requires a special set of lasers, special optics which are geared towards that particular wavelength. But to your point, in principle, the architecture can apply to different modalities.

Operator: The next question comes from Kevin Garrigan from WestPark Capital.

Kevin Garrigan: Congrats on the progress and I apologize if any of these questions have been answered, I joined a little late. So I was wondering if you can kind of give us a sense of the new customers that you start talking to, do they know what problems that they’re trying to solve? Or is there still a major teaching component where you have to kind of go through the process of helping them understand what they’re trying to do and kind of how quantum compute can help?

Peter Chapman: That’s a difficult conversation, so — or complex, I guess. Yes, there’s probably a full spectrum of those. We try not to do a lot of kind of education work and POC stuff. So — but I would say most of our customers tend to be a little more sophisticated in the overall quantum compute space range or whatever. So you see sometimes companies that have 20 or 30 customers from a wide range of things and they’re doing 100,000 engagements and those kinds of things. We don’t do those things. So it’s — I think what is the Thomas said, we don’t do the small deals. So it’s — no but having said that, sometimes we do get — there’s a customer that is early in their space. But generally, people have a pretty good idea of the problems that their businesses have and are coming to us to ask do you think that you can solve X,Y and Z.

And if you look at kind of everything we’ve reported in terms of work with customers, I mean, these are their pressing problems of the day, right? How do we build flying cars if the batteries themselves aren’t — can’t hold the charge long enough. I mean that’s a critical question to be able to enable that business. And so these are the kinds of critical things for these things. They’re not — people aren’t generally off doing kind of raw R&D. Hopefully that answers your question.

Kevin Garrigan: It does. Yes, that’s very helpful. And then just as a follow-up, I was just wondering if you can kind of talk a little bit about the competitive landscape. It seems like every week, every month, a new quantum computing company kind of pops up. So are you seeing any kind of increased competition in the market?

Peter Chapman: You’re 100% right. First is I see it as well. There seems to be a breakthrough every day in kind of what if you watch your news feed and so if you look at the cycle to go from a breakthrough in a university setting, all the way to a finished product, probably for almost every one of these qubit technologies, you’re looking at a $1 billion investment in multiple years. And so IonQ I think is not only the best funded but the fact that we’re building a manufacturing plant is just kind of way-way ahead of everyone else in this marketplace. And I have said it in the past and I have no problem saying it which is there might be in the future other qubit modalities which are better than IonQ. And so if you ask me 10 or 15 years, who might — which qubit technology might be the winner, it might not be ion traps.

But in terms of the next 5 years or so, we believe it will be us and we will have the advantage of a revenue stream and the ability to decide that sometime in the future, we want to look at other qubit modalities and other ways of doing things and will give us an advance into the future. So I don’t really — it doesn’t bother me that somebody is off doing work which is going to show up 15 or 20 years from now, that’s a different time period. So the short answer, no, we’re not worried about the competition at the current time.

Operator: 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.

Peter Chapman: Well, 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.