IonQ, Inc. (NYSE:IONQ) Q4 2023 Earnings Conference Call February 28, 2024 4:30 PM ET
Company Participants
Jordan Shapiro - Vice President, FP&A, Head of Investor Relations
Peter Chapman - President & Chief Executive Officer
Thomas Kramer - Chief Financial Officer
Pat Tang - Vice President of R&D
Conference Call Participants
Joe Moore - Morgan Stanley
Quinn Bolton - Needham
David Williams - Benchmark Company
Operator
Good evening, and welcome to the IonQ Fourth Quarter and Full Year 2023 Earnings Call. At this time, all participants are in listen-only mode. A question-and-answer session will follow the formal presentation. [Operator Instructions] As a reminder, this conference is being recorded.
I'd now like to turn the conference over to your host Jordan Shapiro.
Jordan Shapiro
Thank you, Jimmy Chris [ph]. 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 & 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. We 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 close 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 meeting 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 three years of commercialization, as announced two 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.
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 three years since IonQ went public and why you should be paying close attention to IonQ now. Specifically, I will explain I accused 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 Fineman [ph] 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 basically, it's a wonderful problem, because it doesn't look so easy.
Underlying it’s insight was the realization of three facts. Number one, the real world is neither digital nor analog. But our quantum reality deals have Boolean probabilities, not just deterministic answers. The natural world is governed by quantum mechanics, which ultimately describe the behavior of everything. Yeah as strange world of small particles, where entanglement and superposition rule. Quantum mechanics quantum probability in quantum statistics gives us new and exciting tools to solve high value problem. Fineman 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 cubits. However, every time you add a cubit to that simulation, you double the GPU memory required. As a result, to fully simulate 64 cubits, you would likely need 3.6 billion GPUs.
We recently announced that using IonQ forte; we hit our 2024 Technical milestone of 35 algorithmic cubits, 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 H 264. We anticipate that the market for classical machines running quantum simulations will no longer be able to keep up by Simon'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 LLM takes 30,000 servers, each with eight GPUs. It takes upwards of three 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 brains think and process, the world around us, wouldn't 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 which suggests that the only way to build the next generation of AI is to fill our planet with data.
So what you're seeing is that our need for computational power is exceeding what is now reasonable. Fineman 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're actively exploring ways to use quantum to supercharge LLM, which is a fertile area. Lastly, we're looking at new ways to build strong AI, or what we think of as truly intelligent machines without LLM. 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 generative AI market to reach a market size of $1.3 trillion within the next 10 years. Replacing even a fraction of the resulting compute loop 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 trends that will drive the next wave of innovation in quantum computing is starting to demonstrate all the necessary pieces. In short, this is why something I MQ As 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 IBM to on quantum computing. In a short three 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 in 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 costs and time to produce a quantum computer. This intersection is one 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. The full year Head 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. In a matter of weeks, we improve from AQ 35 to 8 to 36, effectively doubling the computational space of our systems to simultaneously considering over 68 billion [ph] 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 a 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 cubit use together to allow access to 1000s of physical cubits with 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 [ph]. 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 picks working in a lab setting, which demonstrates that the engineering process is now possible at HQ. Last week, we shared that we've officially demonstrated the first critical milestone for photonic interconnects that aim to we can now reliably entangle a cubit with photons to enable communication. Later this year, we expect to show that we can connect multiple cubits together across cubit [ph] use, and that those connected cubits can be used for distributed quantum computation. We envision connecting the cubit use 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 two to three 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 HQ, 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 IQ quantum machine learning model with detecting potential failures in the company's fleet of bulldozers and compare to 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 five to six times more efficient than its classical equivalent and yielded the same accurate results. ECG recently estimated the market for quantum automotive solutions at upwards of 10 billion. Meanwhile, and a recent project that we will share more about with a forthcoming paper in quantum machine learning algorithm for chemical manufacturing, would be up to 75% more efficient than as classical equivalent and demonstrated potential cost savings for users. According to BCG, quantum chemistry applications would have a market size of up to 50 billion quantum algorithms are beginning to show advantages over their classical counterparts. That's the sort of important trends 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 the can reduce a complex materials 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 cubits is progressing at a much faster pace than the hardware itself. And this is happening across a wide variety of application areas. What yesterday seemed two 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 two to three 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 three years, a clearer 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 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 and 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 and 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 US Senator, Maria Cantwell [ph] from the State of Washington, we recently inaugurated our Seattle manufacturing facility, which will support these products. We're dialed in from that facility this afternoon. We are only a few feet away from the manufacturing floor where our first 14 enterprise systems are being assembled to fulfill rising customer demand. We're also announcing that we've already decided to increase our footprint in this 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.
Computer hardware customers today, such as quantum basil, are looking to jumpstart their local quantum economies was on-prem access to the latest cutting edge system. Networking customers like the US Air Force Research Lab, are interested in communication between quantum systems. Regarding quantum communication, we worry that a rapid advancement in quantum decryption similar to the other algorithms we discussed 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. DCG 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 [ph] is the Former Deputy Director of the US Defense Intelligence Agency, and previously served as a national intelligence adviser to President Obama, driving the President's daily US intelligence briefing with 40 years of intelligence experience, Robert will play an integral role in expanding ion queues relationship with federal agencies, helping us to meet the unique needs of government customers. Bill's Cannel [ph] is the President of Global Sales & 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.
I think US 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 trap AI on quantum computing; that agreement continues to contribute valuable IP buying to our co-founders, Christ 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 AI on 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 May, who's 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 sizeable and growing pipeline across quantum computer networking in 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 into our year, recognizing $6.1 million in revenue. For the full year, we ended up with $22 million in revenue above the high end of our updated guidance range, and 98% year-over-year. We ended the year with $65.1 million in bookings, which was also about the high end of our updated guidance range for 2023 and up to 65% year-over-year. Given that we are still at the beginning of our commercialization phase, I want to reiterate my comment from our last earnings call that we expect bookings to continue to be lumpy for quite some time.
Moving down the income state for the fourth quarter of 2023; our total operating costs and expenses are $60.6 million 121% from $27.4 million in the prior period. For the full year 2023 that number was $179.8 million 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 131% from $13.7 million in the prior period for the full year 2023; that number was $92.3 million 110% or $44 million in 2022. We call that we are investing heavily in R&D, and our increasing production of our systems to meet projected customer demand.
Our sales and marketing costs in the fourth quarter were $7 million of 189% from $2.4 million in the prior 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 administrative costs in the fourth quarter were $15.3 million, up to 69% from $9.1 million in the prior period. For the full year 2023 that number was $50.7 million 41% from $36 million dollars 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 for $1.9 million in the fourth quarter, compared to $18.6 million in the prior period, and the net loss of $157.8 million for the full year 2023 versus $48.5 million in 2022. It's 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 a 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 20 to 33 versus $48.7 million for 2022. Note that we projected an adjusted EBITDA 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 equivalents and investments as of December 31 2023 of $455.9 million, we are confident in our cash position which positions us well to continue executing Ganser [ph] technical roadmap. Looking forward to a 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 US 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 the 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 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 Oh Open the line for questions.
Question-and-Answer Session
Operator
Thank you. [Operator Instructions] First question comes from Joe Moore from Morgan Stanley.
Joe Moore
I wonder if you could just you talked about a 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 understand you think your technology gets us there quicker. But you know, at what point can you demonstrate that capability, where you might expect there to be quite a bit more kind of a pickup and investment in the quantum area?
Peter Chapman
Joe, great question. And I think it is the kind of the number one question for, for investors. You know, it's interesting, just looking at simulating our quantum systems alone, we happen to be at a place where, you know, going between 35 Now 36 and going to 64, the number of GPUs that would be needed to simulate what would it is we're doing. And so, you know, it's kind of already that kind of proof points 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 even not a huge market for, you know, classical simulation of what we're doing. So it's a technical proof point but not a business one. But I do think that, you know, we will see within this this time period, when we get to 60, for 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 that will take advantage of our own hardware, and increasingly, talking with other quantum of developers, you know, getting them ready for having that kind of computational power.
So it's timing, as I kind of mentioned, today's script, you know, you need these three things to come together. And, you know, we think it's roughly in that kind of two to three time, your period, for all three pieces to come together, were really, really starts to take off and has, as I kind of said, the ChatGPT moment is when it really starts now. You know, I think you'll see tell-tale signs along the way. And there's, you know, potentials for like, as I said, today, the algorithmic improvements, somebody had a breakthrough. You know, there's potentials along the way to do more with less. And that seems to be the history of the industry as well. And, you know, 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, you know, we could have a surprise, too. That's kind of, you know, when we're predicting the future, it's kind of difficult to do.
Joe Moore
Understood. Thank you very much.
Operator
The next question comes from Quinn Bolton from Needham & Company. Please proceed with your questions.
Quinn Bolton
And just first maybe for Thomas, just as talking about the bookings. In the fourth quarter, you know, how diversified were those bookings? Were there any hardware components or systems in that fourth quarter number? And then maybe a similar question, looking to the $70 million to $90 million bookings guidance? Can you give us a sense, what's the split between hardware system sales versus more to gas or development or professional service type contracts?
Jordan Shapiro
Thanks, Quinn. Excellent questions. And we did not have any hardware related hardware related bookings in Q4. However, you can tell from two things that we are absolutely expecting to see that in 24 Number one, the it's just a high bookings number which comes from the fact that our assistants sell at a very high price, but very much worth it. And the other thing is that you can see from the range; something 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 that you should expect that our hardware would out, perform in terms of the bookings weight, compared to the other categories.
Peter Chapman
And we're -- 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, 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 it, we didn't sell a system and in the fourth quarter,
Jordan Shapiro
That's correct. Ultimately, we do so compute. And when we sell a system all at once, it just is an aggregation of lots more compute at one time.
Quinn Bolton
Got it. Okay. And, I'm not sure if I'll get you to answer this question of the landscape, your guiding say, even to a lawsuit of $110 million, $107.5 million, you know, you look forward, obviously, I'm going to expect, you know, probably 2025 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 peak,
Jordan Shapiro
We look forward to coming back to you with projection for 2025 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
Thank you. The next question comes from David Williams from Benchmark Company. You may proceed with your questions, David.
David Williams
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 non-governmental entities? Are you is that really beginning to pick up? And are you are you gaining interest? They're specifically kind of related to the progress you've made on your quantum algorithm and cubit?
Peter Chapman
So in terms of -- kind of top of funnels, one of our reasons we're, you know, pretty happy at the moment, is, I'd say is international seems to be particularly strong, maybe even stronger than, you know, domestically in terms of, of government. And so, so that's one area, which is of strength. As we kind of mentioned in in this were, you know, hedging a little bit, because, you know, we don't know as to whether or not Congress will pass a budget bill this year. So, you know, 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, you know, there's heavy, there's heavy interest in the enterprise as well.
Operator
David, does that complete all of your questions or do you have any further questions? Yeah,
David Williams
My apologies. I was -- unfortunately, hit mute. So I wanted to ask real quick about Jungsang [ph] and his departure from his current role. And I recognize the transitions that happened here, but we're just curious, we provide maybe a little bit more color or maybe it's 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? Thank you.
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, you know, when I started here, five years ago, there was Chris during saying and myself, that was it. You know, 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 you know, Chris, and John saying, we're 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 you know, 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, you know, start the company, and, and also keep this, this relationship, this business, you know, arrangement we have with universities going. And so, John sang was going to take a sabbatical from Duke, and come to IonQ to help. And Chris was going to move from University of Maryland to Duke to run what now is become the Duke quantum center. And that was important to the company, because the, you know, the research that's going on there is, you know, being captured by the company, we have an economic relationship with him. So we have an interest in making sure that that works. And then John sang, it was basically John saying, and myself, and I was the business and John sang was the tech person. And then we started hiring the management team, we got, we got, for instance, Dean to come in, in 2021, to come in as VP of engineering.
At that point, Jungsang [ph] had that role. And then, you know, John sang left that role, because Dean had taken over, and Jung then went and became VP of R&D. And then we hired Pat last year, and then he gave up that role. And then we went over to applications, you know, he was, 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, we've gotten now to the point where we have a full management team. And, you know, 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, John saying, going back to Duke to run the thing, and to be the professor's and continue to teach and, you know, do all the things that they do.
And at the same time, the company, you know, now has a complete management team. And so we're no longer in QuickBooks or, you know, none of those things. So it's in some level, somewhat of the maturity of the company, John saying, and, you know, is, is still available will still be, you know, convincing on next generation designs and all the rest of those things with the team. You know, that's, that's not going to, that's not going to stop. So I knew it's a juicy kind of titbit for people to chew on. But, you know, it's just, the, the two of them are professors, they, you know, trunk saying, I've taken a leave of absence from Duke to be able to come in and join us, and we appreciate the time that he was here to be able to do that. But you know, as an example, for AQ 35, you know, that wasn't, that wasn't really junk thing that was Dean and the rest of the team. You know, the, the internal engineering group was the ones that kind of really responsible for that.
So, you know, I don't want to minimize what junk things 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, you know, we have in our management team, three PhDs. And the other side is that about two thirds of our staff also have an academic, you know, 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, Maryland, or two. And so, you know, we, that continues on as well. So anyways, there's a long answer to probably what it should be a short question, but there you go.
David Williams
Thanks so much for that color; certainly appreciate it. And I look forward to seeing your continued success. Thank you.
Operator
[Operator Instructions] The next question comes from Chatty [ph] from Craig Hallum. Please proceed with your questions.
Unidentified Analyst
Hey, this is Chatty [ph] on for Richard Shannon. Thanks for taking my question and congrats on the solid year, guys. Maybe a question for Pete. I hear in your prepared remarks, you mentioned the potential to increase the speed of cubits, by many orders of magnitude. Ion traps are known to be somewhat slower than other cubit modalities. So how do you expect to be able to accomplish this? And is this with the same Varium [ph] cubits? Your forthcoming systems we'll use?
Peter Chapman
I'll tell you what; we have Pat sitting here, who happens to be working on it. So I'm going to let him answer.
Pat Tang
So the two research paths we're taking. One is really optimizing the current gates schemes that we have, which as you know, relies upon motional Mosinee ion chain. But we also have another modality that we're looking at as well, using guides which interact electromagnetically. So that would potentially give a real speed up to okay times. So you're going to be hearing more that in our forthcoming courses about that particular research. But that's a very active research. And we 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 going to hear more about self-esteem, future quarters.
Unidentified Analyst
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 GPUs and your AQ 64 system?
Peter Chapman
Once again, we'll redirect to the to the techies in the room. So, Pat can take.
Pat Tang
So photonic interconnect [ph] 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 queues beyond H 264. So this is a very important term, I want you to us, we're making great progress on this. And you're going to hear us, we, you know, we stated this, that we go and complete this this year, and expect more to come from this year's reports.
Peter Chapman
So just to add a little bit to there 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.
Unidentified Analyst
Thank you for all that. And that's all for me.
Operator
Next question comes from David Williams from Benchmark Company. Please proceed with your questions, David.
David Williams
Thanks for the follow-up. I just want to ask real quickly, are those -- the photonic interconnects; will those be kind of system agnostic in terms of the does it matter which hardware you're working on as long as it's Quantum? Or is it specific to the trapped ions are your IonQ systems?
Pat Tang
So in principle, the architecture itself and agnostic, but we are using a barrel system, as you know, so the hardware that we've developed is specifically for the barrier money prize, 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.
David Williams
Right, perfect. Thanks so much.
Operator
The next question comes from [indiscernible]. Please proceed with your questions, Kevin.
Unidentified Analyst
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, you know, the new customers that 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 you know, what they're trying to do and kind of how quantum computing can help.
Peter Chapman
That's a difficult conversation. So are complex, I guess. Yeah, there's probably a full spectrum of those. We try not to do a lot of kind of education work and POC stuff. You know, so, but I would say most of our customers at tend to be a little more sophisticated on in the overall Quantum Computer Space range or whatever. So you see sometimes, you know, companies that have 20 or 30 customers from a wide range of things, and they're doing 100k engagements and those kinds of things. We don't do those things. So it's, I think, what is the Thomas, who said, we don't do the small deals. So if I'm no fun now, having said that, sometimes we do get there's, you know, a customer that, you know, is early in their space. But generally, people have a pretty good idea of the problems that their businesses have.
And you are coming to us to ask, do you think that you can solve XY 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? You know, how do we build flying cars if the batteries themselves aren't -- can't hold the charge long enough? I mean, that's a that's a critical question to be able to enable that business. And so, 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.
So hopefully, we got to your question?
David Williams
Yes, no, 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? You know, 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
In that, you're 100%, right. I see it as well, too, there's a, 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, you know, probably for almost every one of these cubit technologies, you're looking at $1 billion investment and multiple years. And so, you know, IonQ, I think is, is not always the best funded, but the fact that we're building manufacturing plants, is just kind of way, 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 cubit modalities, which are better than IonQ.
And so if you asked me 10 or 15 years, you know, who might which cubit technology might be the winner, it, it might not be ion traps. But in terms of the next five years or so we believe it will be up. And we will have the advantage of a revenue stream, and the ability to decide sometime in the future. We want to look at other human modalities and other ways of doing things and will give us an adventure and in, you know, advance into the future. So I don't really, you know, it doesn't bother me that, you know, 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 -- you know, no, we're not worried about competition at the current time.
David Williams
Yes, got it. Okay. Perfect. Thank you.
Operator
Thank you, 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.
Peter Chapman
Well, I want to thank everyone for joining our call today. And of course, I thank our team for all their hard work and our shareholders for their support. We look forward to speaking with you soon enough. It's updating the entire financial community on our next earnings call. Thank you, everyone.
Operator
Thank you very much. This concludes today's conference. You may disconnect your lines at this time. And thank you very much for your participation.