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spk00: Ladies and gentlemen, thank you for standing by and welcome to the GSI Technologies fourth quarter and fiscal 2022 results conference call. At this time, all participants are in a listen-only mode. Later, we will conduct a question and answer session. At that time, we will provide instructions for those interested in entering the queue for the Q&A. Before we begin today's call, the company has requested that I read the following Safe Harbor Statement. The matters discussed in the conference call may include forward-looking statements regarding future events and the future of performance of GSI technology that involve risks and uncertainties that could cause actual results to differ materially from those anticipated. These risks and uncertainties are described in the company's form 10-K filed with the Securities and Exchange Commission. Additionally, I have also been asked to advise you that this call is being recorded today May 5th, 2022, at the request of GSI Technology. Hosting the call today is Li-Lin Xu, the company's chairman, president, and chief executive officer. With him are Douglas Shirley, chief financial officer, and Didier Lassaire, vice president of sales. I would now like to turn the conference over to Mr. Xu. Please go ahead, sir.
spk02: Good afternoon, and thank you for joining us to review our physical fourth quarter. and the full year 2022 financial results. Our fourth quarter revenue grew year-over-year by 14%, and for the full fiscal year 2022, revenue increased by 20%. The growth in the quarter was due to new projects, expanded business in all categories, and the price increase effective in December 2021. Gross margin improved in the fourth quarter by 840 basis points year over year, reflecting a more attractive mix of higher margin product sales and our ability to manage supply chain challenges and increase the cost. As a result, we narrowed our operating loss year over year by 19%. We ended the year with $44 million cash, cash equivalents, and the short-term investments. Our biggest use of cash remains R&D. The R&D budget and ongoing software development are two large funding projects. One is a software project, the upcoming launch of version 2 of the Gemini 1 compiler stack. The second is a major hardware project representing the most significant portion of the R&D budget, the design of Gemini 2. that we intended to complete by calendar year end. We will incur a one-time mass charge when we table. Other than that, our R&D budget will remain at the current runway for the foreseeable future due to ongoing need for software development and our commitment to continuously advancing the hardware platform. We are on track to release version two of the compiler stack in July. which will be entirely Python-enabled for coded algorithms, applications, and the library. This is exciting because our team will be armed with the tools to increase our Gemini One customer engagement across the various markets we are pursuing. GSR has a highly talented software team that has achieved impressive outcomes in several competitions. This team is a valuable resource as the software is a crucial component to produce success in this market, and one of the reasons we commit a significant portion of our R&D budget to it. The GSI software team has been especially effective and efficient in their work on several high-profile contests, which resulted in a first-place win in two challenges. We took one of the top spots in bidding scale approximate year's labor search challenge and proved our technology could perform on par with category leaders in AI. In addition to the great PR, the biggest benefit of this contest is how they raise GSI's profile in key market sectors, such as with the US and the Israeli military and defense agencies, and other government agencies, and the organizations related to defense and security. Recently, we announced our first-place win in the Mosaic Challenge for the Human and Object Attacking category. GSI loads software and algorithms that could most successfully, as judged by speed and accuracy, automatically detect, classify, and track humans. and differentiate between males and females, plus identify objects of interest such as weapons like a rifle, pistol, or knife that the person might be carrying. Our software was the fastest and the most accurate in performing at various distances and under diverse lighting conditions using images from real-time HD video source from the moving drone. This capability has many applications in the large global security market. The MOSAIC challenge gave GS a high-profile exposure to the leading agencies in the Israeli and American military and defense organizations, including the U.S. Department of Defense and the new agency, the Irregular Warfare Technical Support Directory. Using our contacts from the military and defense SM business, We are working aggressively to pursue the additional opportunities that the Mosaic Challenge win may offer. In fiscal year 2022, we also had the wins in other challenges. GSI was among the bidding scale of POSIMILIA's labor search challenge leader. We proved that APU technology and software could perform on par with the prominent industry leaders in AI. In addition to the industry exposure, participating in this contest also teaches a lot about what we need to work on and how we can improve our performance. Our first place win in the MAFE challenge resulted in several variable benefits to GSI. First was our POC with ELTA, which is funding a SAR image processing acceleration system on APU technology. Second is the inclusive perpetual license of the fast SAR algorithm that ELTA will allow GSI to sell as a SAR system product containing this algorithm. We plan to go after the entire SAR market with this product. The third benefit is ELTA is intended to deploy this system in volume, assuming that the POC is successful. In fiscal year 2022, We increase the customer engagement for the APU and make contacts into new market segments. We are in the early stage of working with the numerous POCs and expect to further our engagement with the second version of our compiler. In fiscal year 2023, we plan to launch our open search platform on AWS marketplaces with the software to accelerate vector search. Our OpenSearch software plugin is particularly good on multi-model search that can search with multiple inputs like image, text, voice, etc. We are working with a partner to build a software platform that performs multi-model and multilingual vector search with hardware accelerations based on APU in AWS OpenSearch. The software platform called Mewv will be presented at the Buzzwords conference in June being held in Berlin, Germany. We have servers in place and are now building the website with the goal of having the open search platform available for client use by the third quarter of calendar 2022. Ideally, we are targeting a fully functioning platform where clients can download the plugin and work independently of our support to the process. Another important goal will be the new version of the compiler and then using the Santa Clara data center to allow customers to work with the APU more easily. This will enable us to build a funnel of prospects and move toward building the future revenue stream for the APU. The US team has been working on the design of Gemini 2 and finalized the layout for taking out the chip. We are very excited about what Gemini 2 could deliver. Gemini 2 could extend our addressable market with a simpler goal, dramatically enhanced performance, and much lower cost. We have a great team, and I appreciate their dedication and hard work. We are aligned on our goal for this year and have lots of motivation to achieve them. I thank all the HSI shareholders for the support. And I value the contribution from that many of you make the feedback and input as a CEO and a shareholder and determined to make the APU successful. Now I will hand the call over to Didi, who will discuss our business performance further. Please go ahead, Didi.
spk05: Thank you, Lillian. Let me start with an update on our radiation-hardened or rad-hard business. We have seen increased traction in this area, and in the fiscal year 2020, we shipped four prototypes to three separate RadHard customers. All the customers are currently testing these systems that require chips to withstand harsh conditions. In the first quarter of fiscal year 2023, we have another program with a major prime contractor for RadHard prototype, which is anticipated to ship in the first half of this fiscal year. This prototype order could potentially be the same revenue magnitude as all of our radiation hardened orders from last fiscal year. As a reminder, RadHard is a high-growth profit product, and if a few of these prototypes move to production, it could add incrementally to fiscal year's 2023 and 2024 revenue. In terms of building a pipeline for APU right now, we are creating awareness of our technology and getting the brand known in the right places. We are encouraged by the response and the incoming interest that we have received from these efforts. The company is evolving from the engineering to the production stage, meaning we are getting the tools and systems in place and modifying how we work to build a sales culture for the APU. I'm optimistic we can progress on these fronts in the upcoming fiscal year. Let me switch now to customer and product breakdowns for the fourth quarter. In the fourth quarter of fiscal 2022, sales to Nokia were 2.0 million, or 23.1% of net revenues, compared to 2.8 million, or 36.5% of net revenues in the same period a year ago, and $1.9 million, or 24.0% of net revenues in the prior quarter. Military defense sales were 22.3% of fourth quarter shipments compared to 22.5% of shipments in the comparable period a year ago, and 27.1% of shipments in the prior quarter. Sigma quad sales were 47.6% percent of fourth quarter shipments compared to 52.9 in the fourth quarter of fiscal 2021 and 40.5 in the prior quarter. Lastly, I want to comment on the supply or the current supply chain situation. We currently moved the majority of our chip substrate suppliers out of China last year to limit the potential damage by any COVID-related lockdowns in China could cause. We are actively addressing supply chain variances that could potentially impact our order fulfillment, but the situation remains fluid. Overall, most of the cost increases from our suppliers were successfully passed on to our customers in December of 2021. We are closely watching costs and evaluating if we need to change prices and procedures. GSI and the industry as a whole are constrained by the availability of FPGAs. Since we use FPGAs on our leaderboard, we could potentially be constrained if we receive a large order for an APU platform. For our SRAM sales, we have implemented some changes to our supply chain management to ensure that we can fulfill orders that we have in hand for the upcoming quarters for our SRAM customers. We are optimistic that we have sufficient capacity to meet this demand. And now I'd like to turn the call over to Doug.
spk01: Please go ahead, Doug. Thank you, DDA. GSI reported a net loss of $4.3 million, or 18 cents per diluted share, on net revenues of $8.7 million for the fourth quarter of fiscal 2022, compared to a net loss of $5 million, or 21 cents per diluted share, on net revenues of $7.7 million for the fourth quarter of fiscal 2021, and a net loss of $4.6 million, or 19 cents per diluted share, on net revenues of $8.1 million for the third quarter of fiscal 2022. Gross margin was 58.6% in the fourth quarter of fiscal 2022 compared to 50.2% in the prior year period and 55.3% in the preceding third quarter. The improvement in gross margin was primarily due to changes in the mix of products sold and price increases effective in December 2021. Total operating expenses in the fourth quarter of fiscal 2022 were $9.4 million compared to $9.1 million in the fourth quarter of fiscal 2021 and $9 million in the prior quarter. Research and development expenses were $6.5 million, compared to $6.1 million in the prior year period and $6.2 million in the prior quarter. Selling, general, and administrative expenses were $2.9 million in the quarter ended March 31, 2022, compared to $3 million in the prior year quarter and $2.8 million in the previous quarter. Fourth quarter fiscal 2022 operating loss was $4.3 million compared to an operating loss of $5.3 million in the prior year period and an operating loss of $4.5 million in the prior quarter. Fourth quarter fiscal 2022 net loss included interest and other expense of $47,000 and a tax provision of $21,000 compared to $21,000 in interest and other expense and a tax benefit at $304,000 for the same period a year ago. In the preceding third quarter, net loss included interest and other income of $15,000 and a tax provision of $64,000. Total fourth quarter pre-tax stock-based compensation expense was $714,000 compared to $753,000 in the comparable quarter a year ago and $740,000 in the prior quarter. On March 31, 2022, The company had $44 million in cash, cash equivalents, and short-term investments, and $3.3 million in long-term investments, compared to $54 million in cash, cash equivalents, and short-term investments of $5.8 million at March 31, 2021. Working capital was $45.8 million as of March 31, 2022, versus $56 million at March 31, 2021, with no debt. Stockholders' equity as of March 31, 2022 was $63.1 million compared to $75.6 million as of the fiscal year ended March 31, 2021. For the fiscal year ended March 31, 2022, we reported a net loss of $17.7 million, or $0.73 per diluted share, on net revenues of $33.4 million compared to a net loss of $21.5 million, or $0.91 per diluted share, a net revenues of 27.7 million in the fiscal year ended March 31st, 2021. Gross margin for fiscal 2022 was 55.5% compared to 47.7% in the prior year. Total operating expenses were 36.2 million in fiscal 2022, an increase of 5.1% from 34.5 million in fiscal 2021. Research and development expenses were 24.7 million, compared to $23.3 million in the prior fiscal year. Selling general and administrative expenses were $11.6 million compared to $11.1 million in fiscal 2021. The increase in research and development expense was primarily related to the development of Gemini 2. The operating loss for fiscal 2022 was $17.7 million compared to an operating loss of $21.3 million in the prior year. The improvement in the operating loss was primarily due to the increase in revenue and gross profit. The fiscal 2022 net loss included interest and other expense of $60,000 and a tax benefit of $45,000 compared to $94,000 in interest and other income and a tax provision of $335,000 a year ago. Operator, at this point, we'll open the call to Q&A. Thank you.
spk00: If you would like to register a question, please press the 1 followed by the 4 on your telephone. You will hear a three-tone prompt to acknowledge your request. If your question has been answered and you would like to withdraw your registration, simply press the 1 and the 3. Our first question is from Jeff Bernstein with Cowan. Please go ahead.
spk03: Hi, guys. I just wanted to get an update. I think you were supposed to get... a ride for Red Heart Parts satellite here at some point so you could get that space legacy. What's the schedule on that now?
spk05: Great question. This is GDA, Jeff. So that was shipped out last year, or, yeah, it was sometime last year. And so it was, as you said, it was going to be very end of calendar 2021 or beginning of calendar 2022 they were supposed to go up. We've been in constant contact with this prime contractor, and they're still waiting for some other components for that satellite. As you know, I'm sure you know, the semiconductor lead times are way out right now for everything, and so there are still some components they have not received, and so the satellite has not been launched yet.
spk03: Any visibility on when that might happen?
spk05: No, they're not telling us too much about that. They're not telling us what components are missing and when, but they certainly feel that it's going to be some time in the summertime they should have all the components. Gotcha.
spk03: Okay. And then just curious, what's the cost of the mask set for the Gemini 2? What process node is that on? Is that a 14 nanometer part or what is it?
spk02: Yeah, well, you're talking about the process or the taping now?
spk05: Yeah, the process 16. So, Jeff, the process is 16 nanometer. Oh, the process. Yeah, the process node, 16 nanometer. And as far as what would that mass set cost? About $2.5 million.
spk03: Gotcha. Okay. And... I was curious about what kind of visibility you have with Nokia in fiscal 23. I think you had better visibility this last year, partly because of all the supply constraints, et cetera. What kind of visibility do you have now?
spk05: Same. So we have a 12-month rolling forecast right now, and so that's remained the same. So the visibility is constant. So we still have pretty good visibility.
spk03: Gotcha. And so that's indicating what, a flat year, a lower year? What kind of a year would Nokia?
spk05: Good question. It looks right now it'll be flat to maybe a touchdown, but it's pretty constant.
spk03: Gotcha. Okay. And I'm curious, we had talked about the potential and the mosaic when kind of suggest this, that there might be application in the very large driver monitoring and cockpit monitoring applications that are going to be legislated here in Europe and then potentially in the U.S. What have you guys figured out there?
spk05: It's still an ongoing process. So there's some areas we think there could be a fit. Other areas are closer to the edge, and we think it's going to have to be more of a Gemini 2 play. As you know, with the Gemini 1, it goes on a board that has an FPGA system, With the Gemini 2, we don't have those constraints. So we're still looking into it. We think there's certainly some opportunity with Gemini 1, but I think a lot of it, because it's more of an edge application, will require the Gemini 2.
spk03: Gotcha. Okay. And then you mentioned that you think the brand is getting known in the right places. What are the right places?
spk05: Certainly the markets we're going after, right? So we've made some announcements recently with the SAR initiative that we have. I mean, certainly that came out of the original MAFAT challenge we won. And as Leline mentioned, we have the POC with ALTA. And so what we're doing now is with that relationship, we got access to a very fast back projection SAR algorithm. which we're going to be able to use without any license or anything for any other customers. And so we're putting together a marketing sales package to be able to address that to all the other SAR players. We also, with this latest win at Mosaic, it's getting us inroads into some of the DOD programs. And so certainly the areas that we're going after are certainly the markets where there's certainly a need for our type of fast search.
spk03: Gotcha. Okay. And then you talked about this new open search, multiple input search, which sounds very interesting that it can take natural language and symbolic language and pictures for searching. Is that correct? And just talk about what's your angle here? What do you think the objective is with that?
spk02: Yeah, just as I mentioned, I mean, we are working on the multi-model, multi-model, which means you can have a query which come in, you know, the text, the image, and the voice, you know, everything coming together for the query. And especially good is we have a software plugin to OpenSearch. I mean, the OpenSearch or ElastiSearch has a lot of installed customer bases. And we, you know, the software parking, so customer doesn't require to learn another software to do the search. I mean, right now you see some website can do the search service, but that requires, you know, the proprietary software to do it. Okay. And now we're going with OpenSearch or Elasticsearch. I mean, that's you know, all this software is really behind the customer. Customer don't even have a visibility for it. So that is how we are exciting about and with all the install customer base in the industry and, you know, so that's a big marketplace we can go after.
spk03: So, Lalit, just so I understand, so if a retailer has a search button on its mobile website and you could plug in the back end, put your software in between, and allow somebody to take a picture of a bicycle and say, I want this bicycle in a different color. And the search algorithm would be able to search and take those two inputs, the picture and the person's voice, and come out with search. And they would be able to essentially plug that functionality into their search without doing a lot of heavy lifting.
spk02: Oh, exactly. And they can park in the price range too, right? Yeah. You can have a picture of the bicycle, and then you say you want the color, and then you want the, you know, $500 to $1,000. You know, you will give it, I mean, you will give an exact merchandise that you are looking for.
spk03: Gotcha. Okay. And then so this could be run by you as a business where those queries would go to APU boards that you owned and it would be a cloud accessible kind of search? Or if it caught on, you would just sell the APU boards to the retailer or whoever their cloud provider was?
spk02: Yes. We can provide either the cloud service or we can provide hardware for the on-premise applications.
spk03: Gotcha. Okay. That's great. Thank you very much.
spk02: Thanks, Jeff.
spk00: Our next question is from James Pockel. He's a private investor. Please go ahead.
spk04: Hi. A couple questions regarding the development of Gemini and the 1 and 2 and the APU. What is the budgeted cash burn for fiscal year 2023? What's the expectations?
spk01: Right now, going into the year, I would expect something similar. to fiscal 2022. And what's that? Probably something less.
spk04: Approximately.
spk01: I don't know, $10, $12 million? Yeah.
spk04: And also, regarding development of the Gemini 1, according to past company statements, the compiler stack was supposed to have been available in
spk02: 2021 and it you know faced repeated delays now we're looking at july if we even get it done then could you tell me why that's taking so long uh well compiler has uh okay the the gemini software we have a two portion of the of the the software one is that the the library, you know, the functional library can drive our processing array. That's one portion of the software. The other portion is we have an embedded processor, or we call it coprocessor, in the chip, which is to control the instruction flow and the data flow. Okay. So right now, we have completed the Python compiler on the instruction side, you know, the microcode, the functional library, and We can use C for the embedded part for the coprocessor. So we do have a compiler available if a customer want to use a high-level language to program the APU. They can use the C compiler for the coprocessor side, and they can use the Python for the functional library. So the version 2 we are talking about, they can do the Python for everything, right? for the coprocessor and for the library. Okay, so that's not really the extra delay. It's just an extra step we need to go through to have a full compiler stack for it.
spk04: How many people are testing the Gemini 1 APU? How many customers? Are you talking about customers? Yeah, how many potential? How many right now are using it?
spk05: So we have some people, right, so it's on multi-levels. So we have some people who have purchased some boards for prototyping. We have a couple boards that are out as loaners. And then a fair amount of folks are doing their testing with us, not with physical hardware, but over the cloud. And so we have a data center set up in our Israeli facility here in our Sunnyvale, California facility. And then we also have, as we've talked about in the past, the setup that we have at CoreSight for the open search, elastic search. And so we have folks doing their testing there. And so how many? Right now we're talking about dozens.
spk02: Well, we also have, just like I mentioned in the earning call I just mentioned, we have a partner developing the multilingual vector search. So that's a development, and that's going to be, and also that's going to be presented in the conference. So there's a customer also behind us, so he can promote the algorithm with the APU hardware.
spk05: And just to take a little bit more color, we also have begun working with some integrators, and the integrators would be a single entity itself, but they're working with multiple customers on their end. So it's hard to determine how many more customers we touch via these integrators.
spk04: And the share price sits at a multiple-year low. What is management's position there to try to improve on that? Because that's... sitting at quite a low level. I'm not sure what it closed today, but if you look at a chart, that's kind of rock bottom. Why do you think the company shares don't gain any respect for what they're doing with the APU and the Gemini wanted to?
spk01: Well, I think the biggest thing is that there's not a lot of visibility in terms of what the revenue stream is going to be. I don't think people understand that well yet. We put out some TAM and SAM data a couple of years ago.
spk04: Yeah, you did. $4.5 billion on a SAM, and you got some pretty large numbers there. We're a small company. We have an enterprise value of about, what, $50 million right now? A couple hundred million in sales would make a huge impact.
spk01: Yeah.
spk04: So how does it look in that?
spk01: As DDA said, there's a lot of activity going on. We don't have a lot of input from customers in terms of volumes and quantities and so on, so we haven't put any revenue forecast. But we believe that there's a large opportunity. There's a lot of traction, as DDA and Leland have talked about here today, that we believe will lead to that revenue growth.
spk04: I hope so. And regarding AWS, wasn't there another 2.0 coming up, or what's happening there?
spk05: Correct. So as you say, it's 2.0, and AWS has not released it yet.
spk04: When's the expectations for that?
spk05: It was supposed to be March. Well, it was supposed to be last year, then it was supposed to be March of this year, and it hasn't come out yet. I mean, we're still working on the current version just to get everything up and running, but we don't control the release of 2.0, and so I don't know what the latest projection is on the release of that.
spk04: Anything else you can add to help shareholders understand what the potential is for APU? Because the shares are sitting at $50 million enterprise value. It's pretty disappointing.
spk01: Well, you know, hopefully we'll have a lot more to say in terms of... commitments from customers, design wins, and so on. And I think that's where we're going to see the benefit to the stock price.
spk04: And that's when you get the compiler stack done in July. Is that correct?
spk05: The compiler stack will only make the process easier. I mean, the first release in February of the initial compiler stack that Lillian mentioned that had the combination of Python and C++. So that certainly started the process. This is the next step to make it even simpler so everything's in Python. So that helps build the ecosystem, but we're certainly working, even outside of that, we're working with customers. As I mentioned, the SAR applications that we're going after and some of these other issues, some of these other areas that aren't strictly tied to the compiler stack. The compiler stack is really to get us to a much broader, larger level where we're not involved in the POCs or the algorithm writing.
spk04: Well, we need to get that done, and I'm holding you accountable for that July date that you guys mentioned.
spk05: Yep.
spk04: All right, very good. Thanks for your time, and I appreciate you taking all my calls and all my questions.
spk01: You bet, Shane.
spk04: Thank you.
spk01: Thank you.
spk00: As a reminder to register, you may press the 1 followed by the 4. Our next question is from Luke Bainey, private investor. Please go ahead.
spk06: Hi. Can you all hear me? Yes. I'm going to possibly reiterate a few things or components of other questions from past quarters and this quarter, but also trying to really gain some resolution in this bigger picture and also zoom in to some of the esoterics that It would be difficult for common investors who aren't in the field to understand, like, the Big N Nearest Neighbor was a competition that had a great deal of complexity, it seemed like. There were maybe sub-competitions within that main competition category that you all participated in. Yeah, very curious about the landscape there with Facebook and Yandex. I can't remember the other participants, but I could call it up now. But, yeah, just curious if you all could unpack that a little bit about, yeah, both the networking involved there as well as the actual operations being tested. Specific to that competition? Yeah, just trying to get myself into that competition a little bit. And there's very little information available publicly online. So, yeah, curious what the different sub-competitions are like. And when you say, yeah, ranked, highly somewhat like a first place for one of the components and competed well with low resources against these large players who are kind of skate keeping this. Curious how that looked and felt for you all.
spk05: Sure. I have to think back a little bit on this. It's been a little while. We were introduced to the competition via Microsoft. They had read one of our blogs and that we had written on the subject, and so they had asked if we wanted to participate, and we said sure, and they had a few tracks, and again, this is off the top of my head, so I may be a little off on this, but I want to say we were in track three, which was the custom silicon category. Okay. And as you said, there were Yandex, and there was Microsoft and Facebook, and I can't remember who else had some databases in there, but there were six databases total. And they were all supplied by those folks, and none of us had access to it beforehand. And what was used as a baseline was the FAS, the Facebook – AI similarity search. So that was kind of the baseline, which was the state of the art for quite some time. And so it was now you would test your solution, which is both a hardware and a software solution, to try and better that baseline of face. And so there were many, many participants that entered the challenge, and many could not improve upon the baseline. And then, of course, there were a few entries by Intel and a few entries by NVIDIA, and then we had our single entry. And so we were the only ones that were able to better the baseline, which is why they presented our data. The other folks dropped out. One of the – highlights was that we actually ran and beat the baseline on all six of the databases, and we were the only one to do that. The other entries focused on two or three or four of the databases and didn't go with the others. We were able to improve on all six of them. And as you said, we had a very limited team compared to the other folks When you looked at, you know, the quote-unquote winners, they – you know, when it came down to, you know, who do you recognize at the company, there were several groups, and there were also external folks like universities and researchers that had a hand in helping them write the algorithm for this competition. And with us, it was just, you know, a handful of software engineers out of our Israeli team. And it was all done – again, this was before we had our – first release of the compiler stack. And so this was all done in a microcode level, which if you folks out there are familiar with coding in high level versus microcode, it's a much larger effort to do it in microcode. So again, we were proud of the results. So with the team we had and the resources we had, we were able to improve upon the baseline in all six of the databases. And we certainly feel like going forward, with the introduction of the compiler stack, we'll be able to develop algorithms much faster for these kind of competitions and for real-life use cases.
spk06: Excellent. That's phenomenal. Phenomenal versatility, phenomenal performance. And like you said, David and Goliath, you all versus those other competitors. It would seem like that would award you all a parade and would be getting knocked on the door to help you to maximize R&D to expedite as well as build out. And so just curious, are you getting pitches for partnerships that you're turning down or anything to that extent where you are kind of choosing an independent path rather than taking on either investment money from a large corporation like Microsoft who would, in theory, be a interested in, say, buying a 20% stake in the company and lending resources or something like that. So just, yeah, curious, yeah, what the chatter is at your all store.
spk01: Well, there's nothing that – sorry, I can take my mask off. There's nothing to talk about at this time, but obviously if something were to come along that made sense to do and benefited the company and the shareholders, we would certainly consider it.
spk06: Okay. Yeah, because I know that you could have an incredible, you know, feeling as, yeah, fully independent. Just, yeah, curious, yeah, if there was anything you were able to say about whether you have gotten or have not just in general. Yeah, so I'm thinking another quick question about the Radhard and the Gemini combination. I've gathered some industry research showing that there are Yeah, there's great eagerness in the satellite and aerospace industry to get better processing up there. And so wondering, yeah, if that is motivated enough for you all to open a channel, you know, for that development within this fiscal year.
spk05: Absolutely. And so, yeah, you hit it on the head. So there's certainly, if you look at some of the other technologies out there, they don't lend themselves well to the radiation, you know, harshness of space. And so we actually... I want to say it was about a year and a half ago. It could have been longer. We actually put the Gemini 1 under the beam, and the beam was just coming back online when we did it. And so we were only able to take it up to a certain level, which was something above rad tolerant but below rad hard as far as the intensity of the beam. And the part did great. And so we are right now getting a board together. because we want to go back to TAMU, I'm sorry, Texas A&M, where the beam is, and to do further testing, and we want to take it all the way up to the full radiation hard levels, and then we're also going to do additional tests along with the SCE, SEL. We're going to do some SEU and SCFI testing as well so that we can get the full spectrum of the testing required to enter this area, but you're right. I mean, we have been presenting to the space folks, and we've attended some conferences, and there is tremendous interest in having a part like ours in space that can do some processing. So, we are actively working on getting all of the data from these radiation tests.
spk06: Excellent. Yeah, another quick point. Ger Kim Chi is still your only advisor on the APU project? Is that correct? Ger.
spk05: Is Ger the only advisor?
spk02: You're asking about Ger Kim Chi?
spk05: Is he our only advisor right now?
spk02: Yeah, right. Right now he's the only technical advisor in our pool.
spk06: Okay, yeah, I know he's very accomplished, very forward-thinking, and Yeah, curious if, yeah, you all are seeking or have gotten any interest for further or other advisors to join him.
spk02: Yeah, if we, yeah, if we, if some technical, great technical advisor come along, yeah, we, yeah, we definitely will look into it.
spk06: Okay. Excellent. Yeah, I know there's a great, like, competition coming into play. Seems like neck and neck with you all with photonics. I'm just curious how intimidated you are there or have you already assessed what the proper differentiation is for final application and do you see healthy coexistence basically for the next five, ten years?
spk05: I'm sorry, you're kind of lulling it out, but it sounds like you're talking about competition and anything we're seeing. Is that correct?
spk06: Yes, specifically in photonics and sort of this Yeah, this gateway into quantum computing. So wondering how you all see yourselves coexisting with that and differentiating in your specific application.
spk05: Yeah. So, I mean, the quantum computing, I don't think we have anything to say at this point on that. What we're doing is we're looking at the competition of what's out there and what's coming out. And what we're seeing is there certainly have been some announcements recently but they are not addressing the issue, which is the Von Neumann bottleneck, and that's what we've addressed. I mean, they certainly are having access to faster external memory, but at the end of the day, they're still fetching data and bringing it back, and that's where our advantage is, is that we're doing the processing in place, and the data is there, and after we've used it, it remains there in place, so we're not you know, going back and forth, fetching and writing data. So that's certainly – we're not seeing anybody in that area, and that's where we've done extensive work on building our patent portfolio to make sure we protect that unique technology.
spk06: Excellent. Yeah, and you'll have a very impressive patent portfolio. That's all my questions. I appreciate it. Yeah, very, very excited for y'all's future. And I'll be alongside. Thanks.
spk00: And there are no further questions at this time. You may continue with your presentation or closing remarks.
spk02: Thank you all for joining us. We look forward to speaking with you again when we report our first quarter fiscal 2033 result. Thank you.
spk00: And that does conclude the conference call for today. We thank you all for your participation and kindly ask that you please disconnect your lines. Have a great day, everyone.
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