Ladies and gentlemen, thank you for standing by, and welcome to the GSI Technology's 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 fifth, two thousand twenty-two, at the request of GSI Technology. Hosting the call today is Lee-Lean Shu , the company's chairman, president, and chief executive officer. With him are Douglas Schirle, Chief Financial Officer, and Didier Lasserre, Vice President of Sales. I would now like to turn the conference over to Mr. Shu. Please go ahead, sir.
Good afternoon, and thank you for joining us to review our fiscal 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 increased costs. As a result, we narrowed our operating loss year-over-year by 19%. We ended the year with $44 million cash equivalents, and 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 two of the Gemini-I compiler stack. The second is a major hardware project, representing the most significant portion of the R&D budget, the design of Gemini-II that we intended to complete by calendar year end. We will incur a one-time mask charge when we tape-out. 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, application, and the library.
This is exciting because our team will be armed with the tool to increase our Gemini-I customer engagement across the various markets we are pursuing. GSI 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 result in the first-place win in two challenges. We took one of the top spots in Billion-Scale Approximate Nearest Neighbor 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 U.S. 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 tracking category. GSI wrote 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 distance and under diverse lighting conditions using image from real-time HD video sourced from the moving drone.
This capability has many applications in the large global security market. The MoSAIC Challenge gave GSI high-profile exposure to the leading agency in the Israeli and American military and the defense organizations, including the US Department of Defense. The new agency, the Irregular Warfare Technical Support Directorate. Using our contacts from the military and defense SRAM business, we are working aggressively to pursue the additional opportunities that the MoSAIC challenge win may offer. In fiscal year 2022, we also had wins in other challenges. GSI was among the billion-scale Approximate Nearest Neighbor Search Challenge leaders. We proved that APU technology and software could perform on par with prominent industry leaders in AI. In addition to the industry exposure, participating in this contest also teach us a lot about what we need to work on and how we can improve our performance.
Our first prize win in the MoSAIC challenge resulted in several valuable benefits to GSI. First was our POC with Elta, which is funding a SAR image processing acceleration system on APU technology. Second is the exclusive perpetual license of the Fast SAR algorithm. Elta will allow GSI to sell 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 excited to deploy this system in volume, assuming that the POC is successful. In fiscal year 2022, we increased the customer engagement for the APU and made contacts into new market segments. We are in the early stage of working with numerous POCs and expect to further our engagement with a second version of our compiler.
In fiscal year 2023, we plan to launch our OpenSearch platform on AWS Marketplace with a software plugin to accelerate vector search. Our OpenSearch software plugin is particularly good at all multi-modal search that can search with multiple inputs like image, text, voice, et cetera. We are working with a partner to build a software platform that performs multi-modal and multilingual vector search with hardware acceleration based on the APU in AWS OpenSearch. The software platform, called View, will be presented at the Berlin Buzzwords Conference in June, being held in Berlin, Germany. We have a server in place and are building the website with the goal of having the OpenSearch platform available for client use by the third quarter of calendar 2022.
Ideally, we are targeting a fully functioning platform where clients can download a plugin and work independently of our support through 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 a future revenue stream for the APU. The U.S. team has been working on the design of Gemini-II and finalized the layout for tape-out the chip. We are very excited about what Gemini-II could deliver. Gemini-II could extend our addressable market with a simpler board, 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 a lot of motivation to achieve them. I thank all the GSI shareholders for the support, and I value the contributions from many of you who make the feedback and input. As the CEO and a shareholder, I am determined to make the APU successful. Now I will hand the call over to Didier, who will discuss our business performance further. Please go ahead, Didier.
Thank you, Lee-Lean. 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 Rad-Hard 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 a Rad-Hard 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, Rad-Hard is a high growth profit product, and if a few of these prototypes move to production, it could add incrementally to fiscal years 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. SigmaQuad sales were 47.6% 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 which 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 in the future. GSI and the industry as a whole are constrained by the availability, excuse me, of FPGAs. Since we use FPGAs on our Leda board, 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. I'd now like to turn the call over to Doug. Please go ahead, Doug.
Thank you, Didier. GSI reported a net loss of $4.3 million, or $0.18 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 $0.21 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 $0.19 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 31st, 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 of $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 thousand, compared to $753 thousand in the comparable quarter a year ago, and $740 thousand in the prior quarter. On March 31st, 2022, the company had $44 million in cash equivalents and short-term investments, and $3.3 million in long-term investments, compared to $54 million in cash equivalents and short-term investments and $5.8 million at March 31st, 2021. Working capital was $45.8 million as of March 31st, 2022, versus $56 million at March 31st, 2021, with no debt. Stockholders' equity as of March 31st, 2022 was $63.1 million, compared to $75.6 million as of the fiscal year ended March 31st, 2021.
For the fiscal year ended March 31st, 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 on 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- II. 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.
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. If you would like to register a question, please press the one followed by the four 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 one and the three. Our first question is from Jeff Bernstein with Cowen. Please go ahead.
Hi, guys. I just wanted to get an update. I think you were supposed to get a ride for Rad-Hard part or parts satellite here at some point so you could get that space legacy. What's the schedule on that now?
Great question. This is Didier, Jeff. That was shipped out last year or, yeah, it was sometime last year. It was as you said, it was gonna 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.
Any visibility on when that might happen?
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 gonna be some time in the summertime. They should have all the components.
Gotcha. Okay. Just curious, what's the cost of the mask set for the Gemini-II , and what process node is that on? Is that a 14 nanometer part, or what is it?
Gemini-II tape-out.
Yeah. Well, you're talking about the process or the tape-out now?
Oh, yeah. The process is 16 nanometer.
Oh, the process.
Yeah, the process node. 16 nanometer.
Yeah.
As far as what would that mask set cost?
About $2.5 million .
Gotcha. Okay. I was curious about what kind of visibility you have with Nokia in fiscal 2023. I think you had better visibility this last year partly because of all the supply constraints, etc. What kind of visibility do you have now?
Same. We have a 12-month rolling forecast right now, and that's remained the same. The visibility is constant. We still have, you know, pretty good visibility.
Gotcha. That's indicating what? A flat year? A lower year? What kind of a year with Nokia?
Good question. It looks right now it'll be flat to maybe a touchdown, but it's pretty constant.
Gotcha. Okay. I'm curious, we had talked about the potential and the MoSAIC win kind of suggest this, that there might be application in the very large driver monitoring and cockpit monitoring applications that are gonna be legislated here in Europe and then potentially in the U.S. What have you guys figured out there?
It's still an ongoing process. There's some areas we think there could be a fit. Other areas are closer to the edge, and we think it's gonna have to be more of a Gemini-II play. As you know, with the Gemini-I , it goes on a board that has an FPGA. With the Gemini-II, -
Sure.
We don't have those constraints. We're still looking into it. We think there's certainly some opportunity with Gemini-I , but I think a lot of it, because it's more of an edge application, will require the Gemini-II .
Gotcha. Okay. You mentioned that you think the brand is getting known in the right places. What are the right places?
Certainly the markets we're going after, right? You know, we've made some announcements recently with the SAR initiative that we have. I mean, certainly that came out of the original MoSAIC challenge we won. As Lee-Lean mentioned, we have the POC with Elta. What we're doing now is with that relationship, we got access to a very fast back-projection SAR algorithm, which we're gonna be able to use without any license or anything for any other customers. 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 giving us inroads into some of the DoD programs.
Certainly the areas that we're going after are, you know, certainly the markets where there's certainly a need for our type of fast search.
Gotcha. Okay. Then you talked about this new OpenSearch multi-modal search, which sounds very interesting, that it can take natural language and symbolic language and pictures for searching. Is that correct? Just talk about what's your angle here, you know? What do you think the objective is with that?
Yeah, just as I mentioned, I mean, we are working on the multi-modal multi-model which mean 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. Especially good is we have a software plugin for OpenSearch. I mean, the OpenSearch or Elasticsearch has a lot of installed customer base. We, you know, the software plugin, so customer doesn't require to learn another software to do the search. I mean, right now you see some websites can do the search service, but they require, you know, the proprietary software to do it, okay? Now we-
I see.
We're going with OpenSearch or Elasticsearch. I mean, that's, you know, all these software is really behind the customer. Customers don't even have a visibility for it. That is what we are excited about. With all the installed customer base in the industry and, you know, that's a big marketplace we can go after.
Lee-Lean, just so I understand. 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 say, take a picture of a bicycle and say, "I want this bicycle in a different color." 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. They would be able to essentially plug that functionality into their search without doing a lot of heavy lifting.
Oh, exactly. They can plug 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, $50, $100- $1,000. You give it. I mean, you will give exact merchandise that you are looking for.
Gotcha. Okay. 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?
Yes. Yeah, we can provide either the cloud service or we can provide hardware for the on-premise applications.
Gotcha. Okay, that's great. Thank you very much.
Thanks, Jeff.
Our next question is from James Pocal, who is a private investor. Please go ahead.
Hi. A couple questions regarding the development of Gemini and the one and two and the APU. What is the budgeted CapEx cash burn for fiscal year 2023? What's the expectations?
Right now, going into the year, I would expect something similar to fiscal 2023, 2022.
What's that?
Probably something less.
Well, approximately.
I know $10 million-$12 million.
Yeah. Also, regarding development of the Gemini-I, according to past company statements, the compiler stack was supposed to have been available in 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?
Well, compiler has. Okay. The Gemini software, we have two portion of the software. One is the library, you know. The library, functional library can drive the all processing array. That's the one portion of the software. The other portion is we have embedded processor, or we call it coprocessor, in the chip, which is control the instruction flow and the data flow. Okay. Right now we have complete the Python compiler on the instruction side, you know, the microcode, the functional library. We can use C for the embedded processor or for the coprocessor. 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. Okay. On the version two we are talking about, you know, they can do the Python for everything, right? For the coprocessor and for the library. Okay. That's not really the extra delay. It's just extra step we need to go through to have a full compiler stack for it. Yeah.
How many people are testing the Gemini-I APU? How many customers?
You're talking about customers?
How many potential or how many right now are using it or testing it?
It's on multi-level. 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. We have a data center set up in our Israeli facility, here in our Sunnyvale, California facility. We also have, as we've talked about in the past, the setup that we have a CoreSite for the OpenSearch Elasticsearch. We have a lot of folks doing their testing there. How many? Right now we're talking about dozens.
Well, we also have, just like I mentioned in the earnings call, I mentioned. We have a partner developing, you know, the multilingual vector search. That's a development, and that's going to be presented in the conference. That's the customer also behind us, you know, so he can promote the algorithm with the APU's hardware.
Right. Just to take a little bit more color, we're 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. It's hard to determine, you know, how many more customers we touch via these integrators.
The share price sits at a, you know, a multi-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 kinda 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? What do you?
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 yet. You know, we put out some TAM and SAM data a couple of quarters ago.
Yeah, you did. $4.5 billion on a SAM, and you got some pretty large numbers there. Well, we're a small company. We have an enterprise value of about, what? $50 million right now. You know, a couple 100 million in sales would make a huge impact.
Yeah. I think, you know.
How does it look in that?
As DDA said, there's a lot of activity going on, and 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. We believe that there's a large opportunity. There's a lot of traction, as DDA and Lee-Lean have talked about here today, that we believe will lead to that revenue growth.
I hope so. Regarding AWS, wasn't there another 2.0 coming up or what's happening there?
Correct. That's so, it's, as you say, it's 2.0, and AWS has not released it yet.
When is the expectations for that?
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. We're still working on, you know, on the current version just to get everything up and running, but, you know, 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.
Anything else you can add to, you know, to help shareholders understand, like, what the potential is for APU? Because, you know, the shares are sitting at, $50 million enterprise value. It's pretty disappointing.
Well, you know, hopefully we'll have a lot more to say in terms of commitments from customers, design wins and so on. I think that's where we're gonna see the benefit to the stock prices when you start talking about-
That's when you get the compiler stack done in July. Is that correct?
No, the compiler stack will only make the process easier. I mean, the first release in February of the initial compiler stack that Lee-Lean mentioned that had the combination of Python-
Yeah.
C++, depending on the, that certainly started the process. This is the next step to make it even simpler, so everything's in Python. That helps build the ecosystem. We're certainly working, even outside of that, we're working with customers. As I mentioned, you know, the SAR applications that we're going after, and some of these other areas that aren't, you know, 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.
Well, we need to get that done, and I'm holding you accountable for that July date that you guys mentioned.
Yep.
All right. Very good. Thanks for your time, and I appreciate you taking all my calls and all my questions.
You bet, James.
Thank you.
Thank you.
As a reminder, to register, you may press the one followed by the four. Our next question is from Luke Ebany, private investor. Please go ahead.
Hi. Can y'all hear me?
Yes.
Good. I'm gonna 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 would be difficult for common investors, you know, who aren't in the field to understand, like the billion 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. Very curious about the landscape there with Facebook and Yandex. I can't remember the other participants, but I could call that up now.
Just curious if you all could unpack that a little bit about your 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. Yeah, curious what the-
Sure.
Different sub-competitions were like, and when you say, yeah, ranked, yeah, like highly, somewhat like a first place for one of the components and, competed well with, yeah, low resources against these, yeah, large, players who are.
Right.
Kind of gatekeeping this. Yeah. Yeah, curious how that.
Right.
How that looked and felt for you all.
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 that we had written on the subject, and so they had asked if we wanted to participate, and we said, sure. 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. As you said, there were, you know, 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.
They were all supplied by those folks, and we didn't, you know, none of us had access to it beforehand. What was used as a baseline was the FAISS, the Facebook AI similarity search. That was kind of the baseline, which was the state-of-the-art for quite some time. Now you would test your, you know, your solution, which is both a hardware and a software solution, to try and better that baseline of FAISS. There were many participants that entered the challenge, and many could not improve upon the baseline.
Of course, there were a few entries by Intel and a few entries by NVIDIA, and then we had our single entry. We were the only ones that were able to better the baseline, which is why they, you know, 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.
As you said, we had a very limited team compared to the other folks. And 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. With us, it was just, you know, a handful of software engineers out of our Israeli team. It was all done. Again, this was before we had our, you know, first release of the compiler stack.
This was all done in a microcode level, which, you know, 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. We were proud of the results. You know, with the team we had and the resources we had, we were able to improve upon the baseline in all six of the databases. We certainly feel like going forward, with the introduction of the compiler stack, you know, we'll be able to develop algorithms much faster, you know, for these kind of competitions and for real-life use cases.
Excellent. That's phenomenal versatility, phenomenal performance. Like you said, it's David and Goliath, you all versus those other competitors. It would seem like that would afford you all a parade and would be getting knocks on the door to help you to maximize R&D, to expedite as well as build out. 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 this theory be interested in, say, buying a 20% stake in the company and lending resources or something like that.
Just yeah, curious yeah, what the chatter is at your all's door. Yeah.
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.
Because I know that you could have an incredible, you know, ceiling as fully independent. Just curious if there was anything you were able to get a say about whether you have gotten or have not just in general. But yeah. I'm thinking another quick question about the Rad-Hard and the Gemini combination. I've gathered some industry research showing that there are, there's great eagerness in the satellite and aerospace industry to get better processing up there. Wondering if that is motivated enough for you all to open a channel, you know, for that development and, say, within this fiscal year or so.
Absolutely. Yeah, you hit it on the head. 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. We actually. I want to say it was about a year and a half ago, could have been longer. We actually put the Gemini-I under the beam, and the beam was just coming back online when we did it. 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. The part did great.
We are right now, we need—we're getting a board together because we wanna go back to TAMU, I'm sorry, Texas A&M, where the beam is, and to do further testing. We wanna take it all the way up to the full radiation hard levels. Then we're also gonna do additional tests along with the SEE, SEL. We're gonna do some SEU and SEFI testing as well, so that we can get the full spectrum of the testing required to enter this area. 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.
We are actively working on getting all of the data from these radiation tests.
Excellent. Yeah, another quick point. Gur Kimchi is still your only advisor on the APU project? Is that correct?
Gur.
Gur. Is Gur the only advisor?
Advisory board. Gur.
You're asking about Gur Kimchi.
Is he our only advisor right now?
Yeah, right. He's right now the only technical advisor in our board.
Okay. Yeah. I know he's very accomplished, very forward thinking. Yeah, curious if you all are seeking or have gotten any interest for further or other advisors to join him.
If some great technical advisor come along, we definitely will look into it.
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, yeah, intimidated you are there, or have you already, yeah, assessed what the proper differentiation is for, yeah, for kind of final application and, do you see a healthy coexistence basically for the next, you know, the next five, ten years?
I'm sorry, you're kind of a little in and out, but it sounds like you're talking about competition and anything we're seeing. Is that correct?
Yes, specifically in photonics and sort of this gateway into-
Photonics.
Quantum computing. Wondering how you all see yourselves coexisting with that and differentiating in your specific application?
Yeah. I'm not, yeah. So I mean, the quantum computing, it's. I mean, I don't think we have anything to say at this point on that. You know, what we're doing is we're looking at the competition of what's out there and what's coming out. What we're seeing is, you know, 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, that we're doing the processing in place and the data is there, and after we've used it remains there in place, so we're not, you know, going back and forth fetching and writing data. 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.
Excellent. Yeah, you have a yeah, very impressive patent portfolio checked out. That's all my questions. I appreciate it. Yeah, very, very excited for y'all's future, and I'll be alongside. Thanks.
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Thank you all for joining us. We look forward to speaking with you again when we report our first quarter fiscal 2023 result. Thank you.
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