Okay, we'll go ahead and get started. Good morning, everyone. My name is Quinn Bolton. I am the semiconductor and quantum computing analyst for Needham & Company. Thank you for joining us here on the first day of Needham's 27th Annual Growth Conference. It's my pleasure to host this fireside chat with Rigetti Computing. Rigetti became the second publicly traded quantum computing company in March of 2022. The company is a pioneer in full-stack quantum computing and is a leading supplier of superconducting quantum processors and computers that leverage its semiconductor design expertise and vertically integrated manufacturing capabilities. Joining me from the company is Dr. Subodh Kulkarni, President and CEO. Subodh, thank you for joining us. Thanks, Quinn. Now, before I get to my questions, the company has asked me to read the safe harbor language. Certain statements in this fireside chat may be considered forward-looking statements within the meaning of the federal securities laws. Forward-looking statements generally relate to future events and can be identified by terminology such as may, should, could, might, plan, possible, expect, believe, anticipate, or the negatives of these terms or variations of them or similar terminology and are subject to risks and uncertainties, factors that may cause actual results to differ materially from current expectations or set forth in Rigetti's annual report on Form 10-K for the year ended December 31st, 2023, quarterly reports on Form 10-Q, and other documents filed by the company from time to time with the SEC. We urge you to review these risk factors and cautionary statements contained in the filings. Thank you for bearing with me for that. Subodh, maybe just since the quantum sector has certainly caught the attention of many investors over the last three to four months, we may have some folks that are newer to the company. Can you give us a quick overview of Rigetti, what differentiates Rigetti from other quantum computing hardware vendors? Thank you for having me, Quinn, and glad you had to do the safe harbor statement and not me. Rigetti is a public company based in Berkeley, California. We are about 140 employees. We call ourselves a full-stack quantum computing company. That means we do everything from designing the chip to building a chip. Our fab is in Fremont, California, and all the layers of the stack, the control systems, the dilution, refrigeration, the firmware, software, and so on. What is unique about Rigetti? We are about 140 employees right now. What is unique about Rigetti is we started about 10 years ago, founded by Dr. Chad Rigetti. I've evolved over the time period, so we were one of the early entrants. What we have designed today is an open modular stack. So unlike some other companies, like big tech companies like IBM and Google, who play in this space, who deal with a quantum computer, like a mainframe computer, where it's all integrated, we have intentionally left our stack open and modular so we can slide in components that may be more creative coming from outside than what we can do internally. We can do everything internally, but when, for instance, NVIDIA comes up with a CUDA- Q, a quantum version of CUDA, we could easily integrate that into our stack. Whereas if you do it in a mainframe approach, it's difficult. Same with error correction companies like Riverlane and so on. Right now we are developing, making quantum computers. They're already there. We have sold a few, and we'll get into that. They work. They are not vaporware anymore. We continuously get those questions. Is it real? Is it happening? It's already happening in that sense. We are developing, making quantum computers. Customers are using them. All for research purposes. We are clearly still in the R&D mode right now. Perfect. The company has chosen the superconducting qubit modality for its quantum computers. Can you talk about the advantages of superconducting qubits versus the other modalities, ion trap, neutral ion, photonic? And are there any disadvantages today for superconducting? So certainly. So within quantum computing, before we get into superconducting, there are two different approaches. One is annealing or entropy-based approach, which is not quite computing per se, but it is quantum effects. We don't deal with that. We are more in the gate-based computing approaches, which is the much larger general-purpose computing market. Within the gate-based computing approaches, there are several modalities, as you pointed out. Most of the attention right now is on superconducting, which is where we are, but trapped ion gets a lot of attention, pure atoms, photonics, spin, and a few other modalities like that. We obviously belong to the superconducting camp. We believe that's the camp that's most likely to win. Along with us, you have IBM, Google, Amazon, the government of China, and a few other companies investing in superconducting modality. The big advantages of superconducting modality are scalability and gate speed. Scalability because we are essentially dealing with semiconductor chip-like technology. And just like semiconductor chips, once you have the fundamental architecture defined and the transistors, in our case, qubits, working properly, you can scale up fairly easily using all the known tricks in the semiconductor industry. Lithography, deposition etching, all the standard stuff we have done for the last 50 years in the semiconductor industry are leverageable here. So we feel we have a huge advantage in terms of scalability and going up in qubit count in the superconducting side. Equally important is gate speed. That's the clock speed. That's the speed at which your computing happens. We are fundamentally dealing with electron speed, just like CPUs and GPUs today with CMOS technology. So our gate speeds are in tens of nanoseconds. Like right now, our gate speed is about 50 nanoseconds. That's typically four orders of magnitude, so 10,000 times faster than trapped ion or pure atom-type modalities. So those are the big strengths we have: scalability and gate speed. On the flip side, historically, superconducting camp's biggest challenge was fidelity because we deal with engineered devices. So we used to get more errors than typically trapped ion or pure atoms where they are dealing with pure ions or pure atoms. But as you can see recently from Google's Willow announcement or our own press release at the end of December, we are basically caught up. So if anything, Google's Willow, our Ankaa- 3, is ahead of companies like IonQ's fidelity right now. IonQ is at 99.4% fidelity. We are at 99.5% fidelity. Google is at 99.7% fidelity. So the historic disadvantage with superconducting, we believe we have more than caught up and actually ahead in some cases. But certainly, our advantages in terms of scalability and gate speed continue to be the case. So we feel very strongly that of all the different modalities, superconducting has the most likely chances to win. And look no further, right? Why would a company like Amazon and the government of China invest in superconducting if they didn't think this was a winning modality? They could have chosen any different modalities to invest in. The fact that they choose to invest in superconducting and not trapped ion or pure atoms or spin, that should tell you something right there. Right, right. You sort of touched on it a little bit earlier, but just Rigetti's approach to hardware sales is a little different than some of your competitors in that you'll oftentimes sell just the quantum processor chip, the QPU, rather than the complete system with the dilution refrigerator. Can you talk about sort of why you pursued that strategy in terms of processor sales, not necessarily entire systems? Those are all good questions. Fundamentally, our view about quantum computing is a little different than some of our peer companies. We believe quantum computing is going to exist in the ecosystem of hybrid computing. So we'll always be in parallel with CPUs and GPUs. We will never be in an isolated situation. And we'll always interface with CPUs and GPUs, just like the CPUs and GPUs interface with each other right now. Secondly, I mean, you asked about sales. We still view sales as a bit further out than where we are, and that's why we have talked about it before. And I keep saying we are very much in tech dev mode right now, and sales don't matter at this point. What's far more important is the technology milestones, the fidelity milestones, the qubit count, the gate speed. Those are far more important than the few. All the sales that we have reported to date, most of it anyway, have been government contracts. And I believe that's the same case for our peer companies as well. So anytime we talk about sales and one contract that suddenly spikes up the sales, I don't think those really matter in the big long term here. It's the technology milestones that are important. That's why we don't like to talk too much about sales at this point. Long term, of course, that becomes important. So getting to your point, we believe quantum computing in the hybrid computing ecosystem has to evolve. There has to be an ecosystem that comes along. It cannot be just one company trying to dominate the whole system. We opted to, and because of our open modular stack, we opted to allow our customers and the government, national labs, the academy researchers, or even corporations. As of today, I don't believe any corporation has bought a quantum computer yet. It's mostly been government labs. But they are experts in different areas. One of our customers, for example, is Fermilab in Chicago. Fermilab is one of the inventors of cryogenic systems in the world. They obviously understand dilution refrigerator technology probably more than anyone else around this planet. It kind of is a little idiotic for us to try to sell them a dilution refrigerator technology. What we told them is that you keep your dilution refrigerator technology. We'll give you the QPU portion that you can interface with your dilution refrigerator technology. We opened up our stack. We are modular. So if a customer wants the full stack from us, we are happy to give the full stack. But if they just want a QPU portion, we are happy to do that. In some cases, like Air Force Research Laboratory, they have expertise and they want to design their own chips. And we will allow them to do that. So they actually give us a design for the chip, and we will build a chip in our fab and give it back to them. So we are open to working with creative arrangements with our customers, and we want to keep it that way at this stage in the game because we are still in R&D. Once it becomes a commercial business, then the discussion should evolve to what is the right business model long term. Got it, got it. The quantum computing industry has certainly caught the eye of investors over the last three to four months. What do you think some of the most important developments at the industry level have been over that period of time? And specifically, you mentioned Google's Willow and their 105-qubit processor. Can you share sort of your thoughts as to the importance of this announcement and how it might affect Rigetti? Well, I believe several announcements happened in the last few months that led to the significant increase in investor interest in the quantum computing sector. It probably started with the government of China announcing that they have started breaking AES encryption with quantum computing. Then, of course, there was a Trump victory that led to more interest in small caps and emerging technologies. Then Amazon made an announcement that they are increasing their investment in quantum computing. And then, of course, Google's Willow announcement was the big one. To us, I mean, we had a couple of important press releases along the way. Just before Google's Willow announcement, we announced that we have accomplished real-time error correction code with very low latency with Riverlane in the U.K. Although our announcements don't get as much notice as Google's Willow announcement, but that's a very important technical milestone that we demonstrated. And then after Google's Willow announcement, we announced our 84-qubit chip at 99.5% that has been deployed already on AWS and Azure now. So many factors have led up to the run-up in stocks of pure-play companies like us. Without a doubt, the biggest of them probably was the Google Willow announcement. What Google did is twofold things. Although the attention goes on the Willow chip, and as you said, it's 105-qubit, 99.7%, awesome accomplishment. But equally, if not more important, is the concept of using surface error correction code. And what they showed in that paper is that as you increase the length of the surface error correction code, in other words, as you increase the qubit count, your errors actually come down. And that's counterintuitive because normally as you add qubits, your errors go up. So Google's demonstration was a very powerful demonstration that once you start deploying surface codes, you can actually bring it down. Now, surface codes have not been invented by Google. They have been around. But as far as we know, it was the first deployment at that scale where Google demonstrated something like that. Now, obviously, we have been working with Riverlane and will continue to do so. So expect us to be doing surface codes and similar demonstrations in the next few months here. But that was a very important announcement that led to the interest. I guess with Willow and the surface codes, I mean, isn't that the whole concept of quantum error correction? Absolutely. As you deploy it, the logical, the fidelity of the logical qubit should be much higher. Correct. or error rate much lower than the underlying physical qubits. But it was all on paper. Now it's all real. The last question sort of at a high level, excuse me, was hoping to get your comments in response to comments made last week by Jensen that it could take 15-30 years before we have commercially available quantum computers. And I guess Zuckerberg made some comments either over the weekend. A couple of days ago. Yesterday as well, which I think sort of implied the same sort of it may be a while before we get a usable quantum computer. How do you respond to those comments? I mean, it's tough to respond to vague words like useful, right? What does useful mean? Somebody may find something useful today, may not find it useful even five years from now. That kind of, so I hate to get into those subjective vague words, particularly going tête-à-tête with someone like Jensen or Mark Zuckerberg, whose microphone is a lot bigger than any one of us here in the room here. So rather than get into that, I prefer to stay with the technical milestones, which we know. And so we can talk fidelity. We can talk qubit count. We can talk gate speed and other metrics. I know what our roadmap is. I have a good feel for what IBM, Google's roadmap, and some other companies' roadmaps are. What I can say is that in a couple of years, we are already at 84-qubit, 99.5%, 50-nanosecond gate speed. I mentioned that. In a couple of years, I'm pretty sure we'll be at a few hundred qubits at 99.7%-99.8% fidelity, maybe 30-40 nanosecond gate speed. We think that will be good enough to start demonstrating what we call narrow quantum advantage, which is demonstrating superiority with the quantum computing over classical computing for some select applications. Another couple of years later, so maybe three to five years from now, when we start approaching 1,000-qubit at 99.8% with surface code that we just talked about earlier, we think we will be able to demonstrate quantum advantage, QA, over quantum computing superiority over classical computing for most practical applications. And then that's the time when we think commercial customers will start showing interest in quantum computing in their data centers, whether quantum computing as a service or on-premise quantum computing. So somewhere four to five years from now is our view and commercial interest. Now, if you want to define usefulness as that, that's what I would pick as the number about four to five years from now. But academic researchers are using our quantum computers today and our peers' companies' quantum computers, and they are finding value in that. So hopefully that answers your question. Yeah, no, that's great. You sort of mentioned the Ankaa system, so maybe we'll skip over that. But looking to 2025, you mentioned technical milestones, probably the key that investors should be looking for. Maybe talk about your '25 roadmap. You've recently shifted your roadmap now to focus on tiling QPUs together. And so walk us through why tiling and what you hope to accomplish this year. So very important question, and that's really where we are starting to differentiate ourselves from our peer companies like IBM and Google in the superconducting camp. Our view is that to reach thousands and tens of thousands of qubits, we will need to tile chips together, just like the CMOS industry. And the reason is simply the same reason why CMOS industry does chiplets right now. If you look at the most advanced nodes, three nanometer, five nanometer nodes, so take your latest iPhone or latest gadget, chances are very high that you are using chiplet right now. And the reason that happens is because fundamentally it's very relatively easy to get a high yield, smaller size chip than a larger size chip, just because uniformities and everything is difficult to control on a larger area than a smaller area. And we find the same in the quantum world. So our nine qubit chip, if you will, is a six millimeter by six millimeter chip. Our 84 qubit Ankaa chip is one centimeter by 1.5 centimeter. So we find that our yield on the nine qubit chip is far higher than our 84 qubit chip for the same reasons why CMOS industry. So our view is that this is going to continue. I mean, CMOS industry has tried for decades to try to get a single chip to a high yield. There is a reason why they ended up with a chiplet format, and we see the same way. So why try to reinvent the wheel when the CMOS industry has already paved the path here? So we are jumping onto the chiplet approach. We have already demonstrated that you can tile two chips without losing any performance. We did that once with 20 qubit chips. We did that one another time with nine qubit chips at very high fidelity. That gives us the confidence that it's time to embark on a tiling approach with four nine qubits. That's the intermediate milestone we want to demonstrate middle of this year. So even though qubit count will go down, so we'll go from 8 36, but instead of a single monolithic chip, now we'll have four nine qubit chips. And it's important to demonstrate that. And we want to get fidelity up to 99.5% for a generic gate, 99.7% with an fSim gate. So we'll bump up the fidelity from where we are today, but more importantly, we'll demonstrate four chiplets, if you will. Assuming that we succeed with that, then we'll try to continue that. And we think that's the right way to go to several thousand and several hundred thousand qubits. IBM has said something similar in their disclosures that they are thinking about a chiplet approach, but as of today, we haven't seen anything, and we haven't heard anything from Google about that or any other companies, so we believe we are the first ones to embark on this milestone. Okay, got it. In August, you released a paper introducing a new chip fabrication process called Alternating Bias Assisted Annealing, ABAA, which allows you to sort of tune the frequency of the qubits. Talk about the advantages of that new process and sort of how that helps you increase the fidelity of your qubits. Fundamentally, when we build a qubit, I mean, essentially in physics words, it's called a Josephson junction. It's a sandwich structure of aluminum, aluminum oxide, and aluminum. We are sending a microwave pulse to one aluminum. It shoots a pair of electron and hole to the other side of the aluminum. In the insulating aluminum oxide layer is when all these quantum effects are being observed. That's what we are using to do the computation. That's the simple layman's description of what's going on in a fairly complex quantum physics world. This microwave frequency is that we send to the qubit to get it initiated in the quantum state. In the ideal world, we would get a perfect frequency for every qubit, but we don't because there's fabrication methods. There's all kinds of things. We get a frequency spread of qubits. The tighter the frequency spread, the better control we have, the better fidelity, the better everything, so we try to tighten up the frequency spread. Historically, we and others like IBM, what we have done is we did laser annealing approaches, so what we do is once we build a qubit, we actually go around the qubit with a high-powered laser, and that heats up the perimeter of the qubit, and then that heat permeates towards the center of the qubit, so you're essentially using the heat of the laser to adjust the morphology, if you will, of the aluminum-aluminum oxide interfaces, and that change of interface enables us to get a tightening of the frequency distribution, which also means the irregularities in the interface is the root cause of the frequency spread of the qubit. That's been done for a few years now. It's not that it's a bad approach. It's been working, and that's how we and IBM and Google have managed to get the systems to where they are right now. What we didn't like about the laser annealing approach is it's slow because it's an individual qubit going around laser. It's not a scalable process. You can do it for 100, maybe even 500 qubits, but imagine doing a 100,000 qubit chip or chiplets and going around each qubit one at a time, all the alignment issues, the cost, the pain index associated with it. It's just not a manufacturable process, so we have been experimenting with many approaches. And one of the approaches that seems to work really well is this ABAA. We call it Alternating Bias Assisted Annealing. Essentially, it's DC pulses, plus minus DC pulses through the entire surface area of the qubit. So essentially, once the chip is built, we are probing the chip to test it for all the room temperature properties. So there's already a probe sitting on top of every qubit. We are using the same probe to derive DC pulses, plus and minus through the qubit. So it's literally part of the qubit manufacturing processes. But we found that with the right sequence of DC pulsing, you can alter the morphology, if anything, better than the laser annealing approach. And it makes sense because we are sending the DC flux right through the surface area of the qubit instead of from a perimeter heating. So basically, a flux through the entire area of qubit is far superior than perimeter heating controlled morphological adjustment. And we find frequency spreading to be remarkably better. So our frequency spreading is significantly better, almost 10x better than what we were getting with the laser annealing approach. So certainly, it's a key part of our go-forward process is the ABAA annealing. And of course, there's a lot of IP that surrounds it. Was that sort of used the ABAA to get to the 99.5? Absolutely. Yeah, okay. But in all fairness, we could have gotten 99.5% or better without ABAA. Case in point, Google Willow. I don't believe Google Willow is using ABAA. I believe they are using something like laser annealing, and they obviously managed to get it to 99.7%. But I would dare say that to get to 10,000-qubit chiplet or chip, we will need an ABAA-like manufacturable process. Got it. Okay. So as you scale the qubits, it becomes more and more important. Much more important. Got it. Okay. You had mentioned that the quantum error correction work you've done with Riverlane. Maybe spend a minute what you're able to show in your work with Riverlane. So first, I mean, we did our own error correction. We continue to do it. But as I mentioned earlier, because of our open modular stack, if a company X comes up with a creative solution and is willing to partner with us, we will do that. And Riverlane is a good example. Riverlane is a small company in Cambridge, UK, about the same size as we are, 140-150 people, very creative. They do fantastic work in error correction. So when we saw what they were doing, we partnered. We started incorporating their error correction code in our stack. And a couple of months ago now, we published some papers with them and demonstrated real-time error correction with very, very low latency, which is a very powerful demonstration. So normally, error corrections are done in the background. So you generate errors, you do it offline, and then you bring back the results. But this time, literally, you're doing real-time. So as you are running the computing and as you're going down the depth of the circuit, as you discover the errors, you fix them on the fly, which is very important in the practical computing world. So if you're just doing an experiment, it's fine. You can do offline. But if you want to do real computing, you need real-time error correction. So that was a very important demonstration, and the latency was extremely small. I mean, all of this is in the papers. The next challenge we have, obviously, is to do what Google Willow did, which is surface error correction code and demonstrate that you can reduce the errors with longer surface error correction code. No reason it won't happen. We just have to demonstrate it with Riverlane now. To demonstrate this surface code, do you need to get to 100 plus qubits, sort of like Willow did? Or, I mean, I guess if it depends on the length of the surface. Exactly. So it literally comes down to the diagonal, right? So right now, if you take our Ankaa chip, it's a 12 by 7. So the longest diagonal we can find is like five or something like that. So we can do surface code even with the existing chip. But at 99.5%, at 99.0% for the standard Clifford Gate, we don't think it's good enough to try that. So we want to get to this 4 by 9, 36. You can't hire a physical qubit. And then. Finality before you can. So I believe Google had to get to 99.7% before they could demonstrate Surface Code. And I'm pretty sure we have to do the same that Google did. Maybe shifting to sort of some of the contracts or work you're doing with your Novera QPU, you've sold that to Horizon Quantum Computing, to Fermilab, and the Air Force Research Laboratory. You also sold a 24-qubit QPU to the UK's National Quantum Computing Center, NQCC. Can you talk a little bit about what those government agencies are researching with your QPUs? So from what we can see, and they are very open with us, most of the work that they are doing right now with the QPUs we have sold them is research applications. So they are doing fundamental quantum physics experiments, pulsing, tuning, retuning, algorithm development. So really understanding the physics of the device and how they can learn and improve on that kind of stuff. Some of the conclusions that they come up with, we try to incorporate them. So things that they learn as they go along, and they feed it back to us, and we try to incorporate that in our next generation technology. But so far, it's been all research applications. They are not really trying it on any commercial kind of applications yet. Okay. And now that you're in those government labs, what's your outlook for potential sales of additional either Novera 9-qubit QPUs or higher-qubit devices in the future? So certainly, there are two big DOE labs we deal with the most. One is Fermilab. The other is Oak Ridge National Lab. We deal with others too, but to a lesser extent. Their funding comes from the National Quantum Initiative, the original NQI Act that was signed in 2018 that expired about August of 2024. The NQI reauthorization bill is being tossed about between House and Senate as we speak. We expect that to get signed in the next few weeks once the new administration is in place. That's a $2.7 billion over five-year spending by the DOE, essentially. That's more than quintupling of the original NQI bill. Certainly, assuming that gets signed, and no reason to believe, there seems to be bipartisan support right now. So it's one of the first things that's going to go through, we believe. Assuming it gets signed and then appropriations take some months or so, typically, we certainly expect Fermilab, Oak Ridge National Lab, and other DOE labs to be big beneficiaries of that funding. We hope we get some. Right. And we are talking to them about it. So they are showing interest in the next generation and the latest technology, right? So right now, the nine-qubit Novera sitting in Fermilab does not have ABAA annealing, does not have our latest and best designs. So they are obviously interested in getting Ankaa and 84-qubit, the latest and best. So we certainly hope Fermilab, Oak Ridge National Lab, and other labs get the funding, and that permeates back to us. Air Force Research Laboratory runs on a different cadence. They are part of the DOD, obviously, and that comes differently than the DOE initiative. So that's not part of the NQI. No, that's not part of the NQI. Okay. Are there plans to increase funding on the DOD side? There are. They've been pretty active, it looks like. Yeah. DOD has its own cadence of what bills are going through and everything. Intentionally, the DOD bills are more opaque. It's very hard to see the line items in DOD bills for good reasons, right? They don't want our adversaries to know what's each line item in our DOD bill. So they're intentionally left in an opaque manner. But there are many, many line items in the current DOD bill that's likely to get passed. That's the $925 billion bill. That's the all-encompassing Pentagon bill and everything. But there are many line items in that bill that relate to quantum computing. So we certainly expect Air Force Research Lab and other, like Naval Research Lab and others, to get money from that. There's a little overlap too. There are some parts of that bill that come back to DOE. It's a little confusing sometimes. And then there are organizations like NASA and NSF and other organizations that get it from both sources. So it gets a little complicated. But overall, we are pretty optimistic that the U.S. government's investment in quantum computing is going to be substantially higher this year than it was last year. And going forward, it looks like our government is committed to continue at that high level. How about other governments around the world? Obviously, adversaries, probably not an opportunity, but allied investment in quantum computing. What are you seeing from some of the European or Southeast Asian governments? So certainly, I mean, not quite Europe, but UK is practically Europe, right? So we have a very close relationship with NQCC in the UK. That's their National Quantum Computing Center. They chose our quantum computer as their flagship quantum computer. We are really proud of that. They have a different parliamentary process, how they manage the bills. And obviously, there was a change of government in the UK. So long story short, the UK government seems committed to quantum computing. They seem to be planning an increase in funding, but not the quintupling of DOE budget that we are considering over here. So expect UK government annual spend right now is in the neighborhood of $200-$250 million. We expect that to get bumped up this year, but not that significantly. But we certainly will be part of it. EU gets a little more complicated. There's an EU bill that covers the entire EU, but then each country is doing its own thing. So then you have to go country by country. So small countries like Finland and Sweden and even Denmark, they are each having their own quantum initiative program. Of course, the larger countries, France, Germany, and so on. Frankly, we struggle with EU the most because there's a nationalistic element there. So even though they know pretty well that we are technically way ahead of their local domestic companies, they are almost choosing their - they want to support their domestic companies over somebody in California. So we struggle the most with EU governments right now. Asian countries are a little different, right? Each country has its own different plan. There's Australia. There's obviously Taiwan, Korea. Countries like India are jumping into it, and a few other countries like that, Israel, of course. There we definitely see some opportunities going forward. The Middle East is jumping into it in a big way. We are seeing a lot of initiatives right now, both in Saudi Arabia and Abu Dhabi and other countries. We have to be a little careful. I mean, certainly we cannot talk to an adversarial country like China or Russia. But there are some countries where things start becoming a little gray, right? Because they have some separate agreements with countries like China that we have to be careful about. We don't want to get caught in some kind of a geopolitical turf battle here. We are careful that just about any foreign government we talk to, we make sure DOE and DOD is fully aware and supportive of what we do. We don't want to get crosswise with those organizations. Yeah. No, it makes sense. Maybe just a couple of financial questions. How should investors think about your level of OpEx and cash burn sort of going forward? I think OpEx has been running about $15 million a quarter. EBITDA loss has sort of been $11-$12 million a quarter. Do you anticipate a step up in those levels as you come into 2025, or do you expect to hold those levels fairly flat? So you're right. Right now, our burn rate, if you will, is about $60 million a year. We have roughly $225 million cash, no debt. So we have three, four years at least of runway. Plus, obviously, it depends on government funding, right? Like this DOD has a big initiative for this quantum benchmarking program, $300 million over seven years. So we hope that our existing cash is good enough to take us to break-even position, frankly, for three, four years from now. We certainly expect OpEx to increase, partly inflation, partly some hiring that we need to do. But we don't expect a dramatic shift in the OpEx structure. So count on inflation plus some additional OpEx increase. Revenue hopefully starting to trend higher, especially when we get the rate. Certainly, exactly. And NQI reauthorization is a big trigger point. The DOD big one is a DARPA initiative. That's a $300 million over seven-year project. We are obviously competing and fighting for that. If we get a big chunk of that, that will obviously be a huge help to get us faster to break-even situation. And obviously, we'll continue to work with other governments and other agencies in the U.S. government. What are your highest priorities for this year? Fidelity, fidelity, fidelity. I have said that for two years, and I'll continue to say that. Right now, we are at 99.5% for fSim gate, 99.0% for iSWAP gate. We want to reduce the error rates by 2x before the end of this year, so we want to get the fSim to 99.7%, iSWAP or CZ to 99.5%. While we do that, we have taken the additional burden of tiling. Tiling, right. We want to obviously take care of that. Those are the big ones. We want to obviously take care of that. These are not in our control, but assuming NQI reauthorization is appropriated, we obviously want to tap into it and increase our government contracts. So sales, we hope the sales will increase based on NQI reauthorization and other DOD and other initiatives. But frankly, that's not the focus. I know you don't like me to say that, but sales is not what I focus most of my time on. It's fidelity, tiling. It's still a technology development company. We need to perfect the technology before worrying about sales and sales growth right now. With that, let me open up to questions. Yeah, I'm curious. The DC pulsing that you used to change the frequency of the qubits, is that a one-time thing that you use to then measure, okay, we now have narrowed the frequency target, or do you have to do it every time you run the chip? No, no, no. That would be impossible. So no, we do it once. Then we package the chip. But we are noticing some drifts over time. So we are thinking about what we may have to do as an intermediate thing. But it looks like it's holding reasonably steady over a few months at least. Other questions? Yeah. Can you talk to perhaps what the new banks are doing? Because they're normally the first adopters of any new technology. So some of the investment banks, do you have any sort of relationship with them? From a quantum computing usage standpoint? So we do quite a, for a small company, we do quite a bit of application development in the financial industry. So we have fairly good working relationships with Moody's, HSBC, Standard Chartered. And you can just do a Google search on us and those names, and you'll see the kind of applications we do. Many of them are in papers already. So with Moody's, for instance, we have been working with them for a couple of years now on trying to improve prediction of economic recessions using quantum computing. And they're showing some interesting potential results there. With HSBC, we are working with them to see if we can improve the detection of fraudulent transactions, partly driven by HSBC got fined something like GBP 2.5 billion about six, seven years ago because of one fraudulent transaction that they missed. So they are trying to see if a quantum computer can pick those signatures better than a classical computer. With Standard Chartered, it's something along those lines. But we are working with those three. We have also a good relationship with ADIA in Abu Dhabi, not quite a classic financial company, but still close to it. So we are doing time series modeling and seeing whether quantum computing can do a better job of predicting time series data. So we have a few areas where we are working with financial companies from an application standpoint. Certainly, we don't have the bandwidth that an IBM does. I mean, IBM has a relationship with Goldman Sachs and J.P. Morgan and a few other large banks. So we monitor what they are doing, and if there's something to learn, we'll learn from those things. But a lot of work is going on collectively with the financial community right now. Okay. Well, I think we're at the end of time. So both, thank you very much for joining us at the Needham Growth Conference. Thank you, Quinn.