Ladies and gentlemen, thank you for standing by. Welcome to GSI Technology's second quarter fiscal 2024 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 this conference call may include forward-looking statements regarding future events and the future 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 conference call is being recorded today, October 26, 2023, 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 second quarter fiscal 2024 financial results. I am pleased to share that we have achieved two significant milestones since we reported Q1 2024 earnings. First was the successful launch of the alpha version of our Copperhead Compiler Suite, a Python-based tool that can harness the capabilities of the Gemini APU. We anticipate releasing the general release of the Copperhead Compiler Suite in early 2024. A full production version will be available later in 2024. Currently, we have partners learning, using, and developing algorithms with our compiler, including SHREC, a consortium of universities and companies developing next-generation technology for space and academic research groups exploring the future of computing architecture, like MIT and the University of California, Riverside. The second milestone was the completion of the Gemini-II tape-out, which was announced last week. As a result, we are on track to have the chip back in our hands early this calendar year, and we expect to begin sampling the device in the second half of 2024. We are targeting Gemini-II partners and customers in low-power data center extensions and enabling data center functions at edge. Example of edge applications could include advanced driver assistance systems and HPC in delivery drones, autonomous robots, unmanned aerial vehicles, and satellites. Turning to our financial results for the second quarter. Revenue of $5.7 million was at the high end of our guidance. Also, it's worth noting that our second quarter fiscal year 2023 revenue was boosted by inventory builds with several key customers, which presents a challenging year-over-year comparison. In addition to advancing the tape-out of Gemini-II, a significant area of recent focus has centered around our ongoing engagements with a key hyperscaler partner. I'm delighted to report that these discussions are making notable progress. Through our constructive dialogue with this leading cloud computing provider, we have gained invaluable insights into the precise design specifications required for Gemini-III to align with their requirements. This collaborative effort has enabled us to chart a roadmap by identifying potential partners who can bring the essential financial, engagement, and engineering resources to the table for the successful development, manufacturing, and the launch of Gemini-III. The evolution will leverage the incorporation of high-bandwidth memory into the APU architectures, thereby harnessing the full potential of in-memory compute advantage. Now, I will hand the call over to Didier, who will discuss our business performance further. Please go ahead, Didier. Thank you, Lee-Lean. Following up on the projects I mentioned last quarter, throughout the second quarter of fiscal 2024, our team continued to pursue opportunities with Gemini-I to advance our customer engagements. Currently, GSI has a Fast Vector Search plugin available that allows cloud vector search users to seamlessly add APU-accelerated search to their major cloud-provided hosted workloads with minimal latency from GSI's hosted data centers. This FVS plugin provides accelerated approximate nearest neighbor search response times, enabling access to a large enterprise service at low power that also meets price points for small and medium-sized businesses. This will be opening up larger markets for us. Switching to our SAR opportunities, due to customer feedback, we have decided to launch our low-powered, highly efficient SAR processing as a SaaS offering, along with, of course, also the on-prem version. We are now engaging to bring that service to market. Moreover, we favorably completed benchmarking on a customer's data set. One target we are engaged with, a startup building satellites that can provide computational capabilities on satellites in space, has identified the Gemini APU as its preferred provider for computing solutions for space. The big differentiator, in addition to low power performance, is the product's radiation-tolerant feature. On that note, we will be conducting full radiation-tolerant testing on Gemini-I next month. By this, I mean the full range of tests required for customers considering using Gemini-I in space. One of the applications for that radiation-tolerant Gemini-I would be ideally suited for SAR and ATR, which is automatic target recognition, and excuse me, computing in space, to name a few. This summer, we announced that GSI was awarded an SBIR contract to perform a feasibility study to adapt Gemini-II to perform computing at the edge in collaboration with the U.S. Air Force and Space Force. We are currently working on a second SBIR based on the Gemini-II software development, which is very promising and potentially a similar financial award as the first win. We continue to file more SBIRs as they bring two key benefits: number one, a source of revenue, and they also create use cases within the U.S. government for future APU opportunities. Let me switch now to customer and product breakdowns for the second quarter. In the second quarter of fiscal 2024, sales to Nokia were $1.2 million, or 20.3% of net revenues, compared to $1.2 million or 13.6% of net revenues in the same period a year ago, and $1.9 million or 33.5% of net revenues in the prior quarter. Military defense sales were 34.8% of second-quarter shipments, compared to 22.4% of shipments in the comparable year, I'm sorry, comparable period a year ago, and 33.8% of shipments in the prior quarter. SigmaQuad sales were 55.8% of second-quarter shipments, compared to 58.1% in the second quarter of fiscal 2023, and 58.6% in the prior quarter. I would like now to hand the call over to Doug. Go ahead, Doug. Thank you, Didier. We reported a net loss of $4.1 million, or $0.16 per diluted share on net revenues of $5.7 million for the second quarter of fiscal 2024, compared to a net loss of $3.2 million or $0.13 per diluted share on net revenues of $9 million for the second quarter of fiscal 2023, and a net loss of $5.1 million or $0.21 per diluted share on net revenues of $5.6 million for the first quarter of fiscal 2024. Gross margin was 54.7%, compared to 62.6% in the prior year period and 54.9% in the preceding first quarter. The changes in gross margin were primarily due to changes in product mix sold in the three periods. Total operating expenses in the second quarter of fiscal 2024 were $7.2 million, compared to $8.8 million in the second quarter of fiscal 2023, and $8.2 million in the prior quarter. Research and development expenses were $4.7 million, compared to $6.4 million in the prior year period and $5.2 million in the prior quarter. Selling general and administrative expenses were $2.5 million in the quarter ended September 30, 2023, compared to $2.4 million in the prior year quarter and $3 million in the previous quarter. Second quarter fiscal 2024 operating loss was $4.1 million, compared to $3.2 million in the prior year period and $5.1 million in the prior quarter. Second quarter fiscal 2024 net loss included interest and other income of $71,000 and a tax provision of $33,000, compared to interest and other income net of $14,000 and a tax provision of $37,000 for the same period a year ago. In the preceding first quarter, the net loss included interest and other income net of $80,000 and a tax provision of $51,000. Total second quarter pre-tax stock-based compensation expense was $676,000, compared to $661,000 in the comparable quarter a year ago and $820,000 in the prior quarter. September 30, 2023, the company had $25.3 million in cash, cash equivalents, and short-term investments, compared to $30.6 million in cash, cash equivalents, and short-term investments March 31, 2023. Working capital was $28.8 million as of September 30, 2023, versus $34.7 million on March 31, 2023, with no debt. Stockholders equity as of September 30, 2023, was $45.4 million, compared to $51.4 million as of the fiscal year ended March 31st, 2023. Given the current global economic environment, our current expectations for the upcoming third quarter are net revenues in the range of $5.4 million-$6.2 million, with gross margin of approximately 55%-57%. Operator, at this point, we would like to open the call to Q&A. Thank you. Ladies and gentlemen, we will now be conducting a question and answer session. If you would like to ask a question, please press star and one on your telephone keypad. A confirmation tone will indicate your line is in the question queue. You may press star and two if you would like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. Ladies and gentlemen, one moment please, while we poll for questions. Our first question comes from Brett Reiss with Janney Montgomery Scott. Please go ahead. Yeah, hi. Thanks for taking the question. You know, until corporate initiatives gain traction, can you just comment on cash burn rates? How long you think the cash will last without you having to, you know, do some sort of financing? Yeah, we've taken a look at that. We typically take a look at it every quarter, and if nothing improves, which we don't expect, we have cash that should last at least a couple of years at this point. If I may just follow up, what do you think your burn will be, you know, for this following year? This year will be around $13 million-$14 million. Yeah, we have one kind of extraordinary expense coming up this fiscal year that requires about $2.4 million dollar cash outlay, and that's for the mask set for the Gemini-II product that just taped out that Lee-Lean previously mentioned today. That's somewhat of an irregular occurrence that only happens every few years. Okay, thank you. Thank you. Ladies and gentlemen, a reminder, if you wish to ask a question, please press star and one. Our next question comes from the line of Orin Hirschman with AIGH Investment Partners. Please go ahead. Hi, how are you? Hey, Orin. Can you get. Good, thank God. Can you give us a little bit more color on, you know, is the data center customer interested in Gemini-II for any purpose, or only Gemini-III? Have they played with Gemini-I to understand them better? And what is attracting them to, you know, to the Gemini architecture? Sure. I have one follow-up. Okay, so let me start with that. So with the hyperscaler we're engaged with, and we've had ongoing discussions with, and we've since opened up other discussions with other hyperscalers. Certainly as Lee-Lean mentioned in, you know, in his earlier comments, you know, the information we gathered from our first engagement was instrumental to be able to shore up our story and our offering for future hyperscale conversations. And so what they're interested right now is would be a next generation, specifically, something we'll call Gemini-III for now, because that one's gonna really be geared towards Gen AI or the LLM models. With that said, as you know, these hyperscalers are very large companies, and so you know, certainly Gemini-II is certainly not out of play with them. It just wouldn't be the solution specifically for the GenAI conversations we're having. In terms of other hyperscalers and data center customers, you know, it sounds like there's some level of progress. You know, how would you characterize it? Have people played with benchmarks yet for any of them? That I think would be an important point to note, if it's true, if you've gotten that far. Correct. And so, so what we've done is we've shown obviously, the, the technology with Gemini-I, because, you know, silicon is here, software is here, we can run true benchmarks. We've then obviously run expected benchmarks off of Gemini-II. And so, you know, going back, and, and I just remembered what part of your earlier question was, was what, you know, what's interesting about our technology to them. So there's, you know, certainly a few areas. Obviously, the performance is, is important to them, but the low power has certainly grabbed their eye and also other features like the fact that we're a bit processor. This is very important to a lot of these folks, because right now, if, you know, if they're using a GPU, they're really locked into, depending on the, on the GPU, 8-bit or 16-bit, 32-bit, or 64-bit kind of traffic patterns. We're a, we're a bit processor, and so we don't, we don't care what your traffic looks like. It can be 4-bit, it can be 64-bit, it can be, make up a number, 1,000-bit, and we can adapt to that on the fly and cycle to cycle. And so that flexibility is also very important to them. In real life, you know, there's been a lot of talk about a variable bit type of super processor in the literature, and obviously no one's really had one commercially where it's programmable in that fashion. Are you programmable today in that fashion? Number one. Number two is, what are some of the applications where that becomes so enticing? You're talking about the bit processing? Yeah. Yeah. So there, there's a lot of research going on right now, and, you know, they're, they're finding out that some efficiencies aren't coming in like the, you know, the expected 16-bit and 32-bit. As I mentioned, 5-bit was one that came up recently, and candidly, I don't remember the exact application or the research on that, but 5-bit was one of them that was important. And, and so, you know, one of the benefits, you know, with this bit processing is that, you know, as our customers told us, we're future-proof. And what I mean is, if there's an application that needs 5-bit, we're there. If there's one that needs a 128-bit, 256-bit, we're there. We don't have to redesign our part to be able to address those needs because of the fact that, you know, we have, you know, 2 million bit processors on our Gemini-I, and they can work, as I mentioned, as 1 bit or make up a number between 1 and 2 million. And so we're future-proof in that respect, which is, which is, obviously, eye-opening to them. Yeah, just, just, just a comment. Right now, the Gemini, the large language model, is a very, very big model. It's a very, very memory intensive application. They will need a very big memory, they will need a very fast memory. The effort, one of the effort is you try, they try to reduce the data format. You know, if you have less number of bit to calculate, then you require less, less memory, you require less memory throughput. We have this bit processing capability, which, you know, it can, just like Didier mentioned, you know, 5-bit, 4-bit, 3-bit, 2-bit, we will be there. We have more capability to keep up with the software innovation, and that's what, you know, some of the customers like about this feature. Just going back to benchmarking, have you done benchmarking for some of the data center and hyperscaler customers? So candidly, most of the benchmarking we've done have been based essentially off of POCs, where customers have come in and said, "This is what I'm using. Here's my data set. What do your numbers look like?" And so we've done real-life case POCs. We've done that, you know, for one of our Israeli customers that we talked about, and then also one of our recent SAR customers. As far as broad, market benchmarking, we haven't done a lot, but we know that's critical, and that's something that's on our agenda to start doing. It's just been, you know, a resource issue for us to be able to make that happen. But we understand it's important, and that's what we're, you know, next on the list. Let's see, two more questions, if I may, and then I'll let other people ask. So in terms of proof of concept using customer data, have any of the hyperscalers given you data sets to actually show them what you can and can't do with it? No, this, these are other applications. These have been SAR applications and other, other applications. The hyperscalers, no, because as I mentioned, the discussions early on have been revolving around this next generation device, and so we've given them. We have given them benchmarking of what we anticipate we could do, absolutely, but they're not true benchmarks. They're calculated benchmarking. Okay, and last question, just on the, you know, you mentioned as, you know, using the processor as a service for the people's data, and you had some, you know, some early tests going back a while ago, and that needed to be revamped for some additional APIs. Where are you up to with any of the potential customers offering it as a plugin or anything like that? Yeah, so there's two areas that we're focusing the SaaS on: Fast Vector Search and SAR. As I mentioned in my, in my just, you know, comments earlier, the SAR was after discussions with one of the folks that we're talking to in that area. You know, we have an on-prem solution, which for some of their customers is needed. Obviously, you know, one of the guys we're talking to wants to put this capability on a satellite, so that would be a physical sale as well. Right now, most of their production they're doing is via SaaS, you know, over AWS, using GPU instances. That's when we, after discussing with them, that's something that we looked at, and so that obviously made sense for us to do. So we're opening up the SAR for that. The Fast Vector Search we've been putting in place, you know, we're still doing some benchmarking internally for some of the, you know, the Fast Vector Search databases, guys like, like Weaviate. And so that's, that's an ongoing project for us. In terms of trying to get that Fast Vector Search as a plugin, so that customers could actually play with it through AWS or something like that, any, any progress there? There is. I'm trying to understand what I can say there. So we had, we've had some discussions recently with, you know, a very large data center company to basically integrate you know, easier into their system right now. And so those discussions have been happening over the last couple weeks, and then certainly once those get worked out, then we'll be able to have a smoother offering right now. Because as you know, right now, it's, you know, we're basically, they're offloading the searches off to our data center that we have put into a facility called CoreSite. And so we're trying to streamline that offering. Okay, thanks so much. Thanks, Orin. Thank you. Ladies and gentlemen, a reminder, if you wish to ask a question, please press star and one. Our next question comes from the line of Luke Bohn, an investor. Please go ahead. Hi. To zoom out from parsing the applications and the, yeah, the prospects for various, you know, partnerships, could we assume that when Gemini-I hits the scene and you all are able to, you know, offer that to be tooled by, yeah, by various users, will that outperform a, you know, large swath of the current high-performance computer offerings that are on the market, including, you know, the leaders of you know, NVIDIA, AMD, Samsung, even Google, yeah, custom chips? Yeah, is that, is that safe to say? So, okay, so I'm trying to follow your question here. So first of all, we do have Gemini-I already, so I'm assuming you were referring to Gemini-II. Gemini-II, correct. Yeah. Yeah. Gemini-II, and then you also mentioned a custom chip. Gemini-II is not a custom chip. Gemini-II is going to be a standard offering that we're going to have. Yeah, obviously, we've done some calculated benchmarkings, which have looked very favorable. And once we have the chip in hand, you know, as Lee-Lean said, we'll have it in hand early next year, and it's probably going to take at least a spin to really get something we can do benchmarking. It'll be around summertime before we can do true benchmarking. Yes, we anticipate them to be very favorable over what we have and what's in the market space now. Now, I do want to add to the comment, you said custom chip. One of the things, and we've mentioned this in the past, that we're also looking to do is obviously offer IP sales as well, because we do understand we have a unique technology, but we also understand that certainly we'll start with the hyperscalers. They do a lot of their own custom silicon. One of the conversations that we're having with the hyperscalers, besides talking about Gemini-III for the GenAI, is we're also talking about IP sales as well for any custom ASICs that they're doing on their own. You asked a lot of questions in there, and I'm hoping I hit all the topics. Mm-hmm. Yep. Yeah, that does kind of answer the two implications there, that Gemini-II will be a compelling, yeah, competitor, and, depending on, yeah, how you're able to benchmark or how much tooling or rendering it requires to, yeah, via IP or via the actual, yes, that chip directly, but that it will, yeah, essentially at 16 nm, be competing toe-to-toe or even, yeah, clearly outcompeting a lot of these 5 nm, yeah, leading high-performance chips. Right. That's what I gathered, yeah, from everything you all put out. Yeah, I mean, if you recall, Gemini-I, you know, the benchmarking we've done in the past has, have been very positive against what's out there today. Now, with Gemini-II, as we discussed in the past, it has 10x the performance and 8 x the L1 memory on chip. So it, it's certainly gonna be a, you know, something that's gonna be very compelling for the market. Excellent. All right. Yep, eager for it. Thank you all. That's, that's all I have. Thanks, Luke. Thank you. Our next question comes from George Gaspar, an investor. Please go ahead. Yeah, thank you. Could you go into a little additional information for us on the APU military and defense applications and the interconnect that the company has had in Israel over the years? In fact, initially, the whole Gemini approach came out of there. And considering what's going on in space, is there broader applications for the advancements that you're making going into space? And what's happening in with Israel right now, in terms of this situation in the Middle East, is there. are you seeing anything happen that could create a more military-related effort? Okay, so let me see. Let me try and get all those questions now. So let's start with the military. So yeah, there are a lot of different possible use cases with the military, which is also why we've had some successes recently with these SBIRs that we've been filing. So some of the interests that we've seen have from, from like, we'll call the mil-aero kind of area is certainly SAR, for sure. Object detection is another, automatic target recognition, another. We've also been for imaging as well, for change detection. Oh, and also one of the customers that we're engaged with, in fact, they have two of our servers on loan that they're doing demonstrations with, is, you know, they want to start putting data centers in space. And so that's another just a standard data center application in space, and so that's another one. I'm not sure with the Israel side. So as you say, you know, this original technology was an acquisition we made, and you know, the company was out of Israel. But I'm not sure what the question was revolving around that acquisition. Well, basically, just as a reference, I mentioned it, but considering what's going on in the Middle East right now, and the connections that the company has had with Israel, I would think that there would be an attempt to try to get some applications moving forward to, and give Israel more recognition in how they're trying to monitor things. Is that? Yes. Yeah, so we have had. Okay. Yeah, so we've had some discussions obviously, with MAFAT, that we've talked about in the past and other entities there on several applications. I won't go into exact detail, but there's certainly. I'm sure we'll, there will certain areas that we've talked about with them will most likely get accelerated now because of obviously, what's happening now. But, but, but right now, you know, we're not having those discussions right now. There's more pressing issues in Israel right now. I see. Okay. Well, it looks like you're about to make some generally better movements forward with Gemini-II going to Gemini-III. Hopefully, this really starts to turn the company around in terms of its revenue volume, and would expect that by the end of this fiscal year, there's some real momentum going forward. Can you comment on it? Yeah, there's certainly momentum, and, you know, as, you know, as time goes on, we hope to announce more, more, you know, traction. But look, but the end of the fiscal year, you know, any revenue that comes will be coming from Gemini-I. So, you know, as, as we discussed, Gemini-II, we're not going to be even sampling it until summer of next year. And so that, that falls into fiscal 2025. Gotcha. Okay. Thank you. Thanks, George. Thank you. As there are no further questions, I would now hand the conference over to the management for their closing remarks. Thank you all for joining us. We look forward to speaking with you again when we report our third quarter fiscal 2024 results. Thanks. Thank you. The conference of GSI Technology has now concluded. Thank you for your participation. You may now disconnect your line.