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spk02: Thank you. Thank you. Thank you. Thank you. Ladies and gentlemen, you are currently on hold for today's conference call. At this time, we're assembling today's audience and we plan to be on the way very shortly. We appreciate your patience. Please remain on this line. Thank you. Thank you. Thank you. Ladies and gentlemen, thank you for standing by. Welcome to GSI Technologies second quarter fiscal 2021 results conference call for the quarter ended September 30, 2020. 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 Dave Harbour statement. The matters discussed in this conference call will include four looking statements regarding future events and the future performance of GSI technology that involves 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 files with the Securities and Exchange Commission. Additionally, they've also been asked to advise you that this conference call is being recorded today, which is October 29, 2020, at the request of GSI Technology. Hosting the call today is Leland Hsu, the company's chairman, president, and chief executive officer. And with him are Douglas Shelley, chief financial officer, and Didier Lezere, vice president of sales. And I'd like to turn the conference over to Mr. Xu. Please go ahead, sir.
spk03: Good afternoon, everyone, and thank you for joining us to discuss our second quarter 2021 financial results. Throughout the first half of fiscal year 2021, business disruptions related to COVID-19 continued to impact our financial results. The second quarter revenue of $6.7 million was at the midpoint of our revenue guidance. Higher SMA sales in the quarter improved gross margin to 46.7%, exceeding our forecast. Second quarter sales to Nokia were below last year's levels, but were up 89% from the prior quarter, offsetting weakness in other consumer segments, customer segments. Nokia is our largest customer, and earlier this year, they downgraded their outlook for the full year 2020 due to declining demand as customers delay pending plans. We have made significant progress on multiple forms with the Gemini One APU. Our revolutionary in-memory processor has continued to amaze us with its adaptability to new applications and our ability to improve the chip's performance through the software. Our software team has developed NeuroHash, a new algorithm to improve the speed of similarity search for a given accuracy rate. In October, we presented NeuroHash at the 2020 BayLearn Conference held by the Bay Area Machine Learning Symposium. Senior people from companies including Google, Apple, and Netflix, to name a few, make up the BayLearn organization and advisory committees, providing high-level industry exposure for GSI. The Bayland Symposium's goal is to bring together scientists in machine learning from the San Francisco Bay Area. This event offers exposure to key members of the research community and the technology industry. Second, to simplify writing code for the Gemini One APU, we developed a code generator and plan to release a compiler stack in early calendar 2021. The compiler will translate code written in Python to APU machine language. This program will allow developers to write code in high-level language like Python without requiring them to load the chip architecture and the internal logic details. Python is now the most popular programming language with over one-third of the programming market, making this tool key to gaining traction in the market. In the first quarter of calendar 2021, we expect to begin testing the 600 MHz Gemini 1. The goal is to start the qualification and have a final product for mass production in the first half of calendar 2021. Lastly, we have made progress on Gemini 2, the second product in our APU family, with a planned launch in May 2022. With all those of magnitude, performance caused improvement over Gemini 1. In closing, I want to highlight the software capability of the APU. In addition to a novel architecture, the APU has a very sophisticated software components. We have a large team dedicated to APU software development. There are four levels to APU software. First, applications. Integration for specific market applications, like Biovia for job discovery, facial recognition, image processing, and Hashcat for password recovery. Second, machine learning algorithms. We develop dual-level algorithms to enhance APU applications. The apps. We develop a library for specific applications, a solution by developer. And lastly, compiler stack, which I mentioned earlier. It's a stack for algorithm conversion, framework support, and simplified low-level code generation. This software capability will give GSI and APU a competitive advantage because it allows us to improve performance without changing the hardware for various applications. With that point, we are beginning to see the rewards of our software investment. The Israeli Ministry of Defense Research Arm launched the Mass Fat Challenge a series of data science prize competitions. The most recent contest, the MAFET Radar Challenge, a machine learning competition to distinguish between humans and animals in a radar track. The event drew over 1,000 participants and more than 4,300 submissions. I am pleased to announce that MAFET notified the Earth This week, the GSI algorithm is at the top of the leaderboard. In the next few weeks, the market will validate the leader's eligibility and officially announce the winner. If GSI is pronounced the official winner, this prestigious award could bring attention and heightened credibility to our team's software achievements. particularly with the Israeli projects that we are currently working on. The entire GSIT team is working hard to deliver on our goal of monetizing the investment we have made in the APU. Our timeline has been extended due to the COVID-19 pandemic, but we are making material progress on the technology and the marketing to build awareness. I am grateful for everything my team has accomplished. And I thank you for your support. Now I'll hand the call over to Didi, who will discuss our business performance in further detail. Please go ahead, Didi.
spk04: Thank you, Lilien. Starting with the sales breakdown for the second quarter of fiscal 2021, sales to Nokia were $3.4 million, or 51.7% of net revenues. compared to 5.3 million or 45.2% of net revenues in the same period a year ago and 1.8 million or 26.9% of net revenues in the prior quarter. Military defense sales were 26.9% of second quarter shipments compared to 23.4% of shipments in the comparable period a year ago and 30.1% of shipments in the prior quarter. Sigma Quad sales were 65.4% of second quarter shipments compared to 63.5% in the second quarter of fiscal 2020 and 46.3% for the previous quarter. For the remainder of the fiscal year 2021, we continue to anticipate a challenging business environment related to COVID-19 restrictions. Changes in customer buying patterns, communications constraints with our customers, The postponement of investment and the restricted activity of our sales force and distributors may impact demand and our ability to close sales across customer segments. With this backdrop, our new product sales process is taking longer than usual. Selling new products requires a longer cycle than selling established products. Ideally, we conduct sales meetings in person and spend the time educating customers on how our new product will change their current practices. Without face-to-face meetings or training workshops, the pace moving the sales process forward has slowed. The targets for radiation-hardened SRAMs are mostly national assets and top secret applications. Sales communications in this channel have slowed due to the lack of access to secure communication facilities. In the late quarter, I'm sorry, in late calendar 2020 or in early 2021, Once funding is released, we anticipate radiation-tolerant SRAM orders for imaging satellites and space applications. Similarly, we are making progress on Gemini 1 customers on several fronts as prospects test the solution. We are working closely with a few potential large customers now. That said, given the business challenges to educate and train new customers, we now anticipate design wins and initial sales of Gemini leaderboards into calendar 2021. On the marketing front, GSI has taken steps to raise awareness in the relevant sectors for the Gemini One APU and our company. We are engaging with industry analysts to gain exposure to leading providers of market intelligence for the technology and telecommunication markets. Our team is expanding its participation in high-profile industry events and conferences where GSI can gain recognition as a leading developer of a revolutionary solution for AI computing and have exposure to leading companies in the sector. Globally, we are redesigning our market-facing collateral, including our website, to align our messaging and image with the technology leader's identity. All of these efforts support our sales teams as they build new relationships and bridge the GSI reputation as a leader in the SRAM memory market to an innovator in the AI market. I'd like to hand the call over to Doug Doug, go ahead, please.
spk00: Thank you, DDA. We reported net loss of $5.2 million, or $0.22 per diluted share, a net revenues of $6.7 million for the second quarter of fiscal 2021, compared to net loss of $1.8 million, or $0.08 per diluted share, a net revenues of $11.7 million for the second quarter of fiscal 2020, and a net loss of $6.1 million, or $0.26 per diluted share, when there was a $6.6 million for the first quarter fiscal 2021. Gross margin was 46.7% compared to 55.9% in the prior year period and 46.1% 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 2021 were $8.3 million, compared to $8.5 million in the second quarter of fiscal 2020 and $8.7 million in the prior quarter. Research and development expenses were $5.7 million compared to $5.8 million in the prior year period and $5.8 million in the prior quarter. Selling general and administrative expenses were $2.6 million when the quarter ended September 30, 2020, compared to $2.7 million in the prior year quarter and down from $2.9 million in the previous quarter. Second quarter fiscal 2021 operating loss was $5.2 million compared to $1.9 million in the prior year period and $5.7 million in the prior quarter. Second quarter fiscal 2021 net loss included interest income and other expense net was $16,000 and the tax provision of $62,000 compared to $210,000 in interest and other income and the tax provision of $55,000 for the same period a year ago. In the preceding first quarter, net loss included interest, another income of $106,000, and a tax provision of $487,000, primarily resulting from the settlement of a tax audit in Israel for fiscal years 2017 through 2019. Little second quarter pre-tax block-based compensation expense was $653,000, compared to $642,000 in a comparable quarter a year ago, and $755,000 in the prior quarter. On September 30, 2020, the company had $56.1 million in cash, cash equivalents, and short-term investments, and $8.7 million in long-term investments, compared to $66.6 million in cash, cash equivalents, and short-term investments, and $4.1 million in long-term investments, at March 31, 2020. Working capital is $59.2 million as of September 30, 2020 versus $70.9 million at March 31, 2020 with no debt. Stockholders' equity as of September 30, 2020 was $82.2 million compared to $89.6 million as of the fiscal year ended March 31, 2020. For the upcoming third quarter of fiscal year 2021, our current expectations Our net revenues are in a range of $6 million to $7.2 million, with gross margin of approximately 41% to 43%. Operator, at this point, we will open the call to Q&A.
spk02: Thank you. If you would like to ask a question, please press star 1 on your telephone keypad. If you are using a speakerphone, just make sure that your mute function is turned off to allow your signal to reach our equipment. Again, that is Star 1 to ask a question. We'll just pause for a brief moment to allow everyone an opportunity to signal for questions. Again, that is Star 1 to ask a question. We'll take our first question from Dennis Prattichin. On behalf of Rajeev Chetan, please go ahead.
spk06: Hi, guys. Thank you for taking my call. So I want to ask a couple questions. was the first one about the Gemini AI APU. Can you talk a little bit about just how the feedback is from early adopters and then maybe when we should expect to see revenue from this product and the revenue opportunity? How is it different from other AI startups that are doing memory processing as well?
spk04: So the feedback has been really good so far. As I mentioned, we have a couple larger guides that we're starting to talk to now that are new in this past calendar quarter. And then we've been working with some of the government folks along with some drug discovery and facial recognition companies. And all the feedback has been very good. Now, as far as how do we compare with other competitors, what we've seen so far is everyone is concentrating their efforts on the training, and that's not where we are. So we are concentrating our efforts on similarity search. So for us, we don't care who does the training, whether it's NVIDIA or a startup or Intel. For us, all we need is a vectorized database, and that's where we take over. So we're really not competing with those folks. If you look at how the search function is done today, it's mostly done in CPUs. So we're really... replacing some old servers using standard CPUs in this search function. Got it.
spk06: Thanks. Is there anything you can give us about the Nokia business going forward, the impact on the gross margins in terms of the product mix or any other call you can provide on the Nokia situation?
spk04: So Nokia is tracking about along the lines that we've been predicting for a few quarters now. We have predicted that the March quarter and the June quarter would be down and that they would be recovering in the second half of calendar 2020, and that's what happened. So the two quarters were down and then we recovered this quarter. The forecast we've seen so far seem to bring us back to kind of the levels we're at now, so more of the run rate kind of levels.
spk06: Great. Just really briefly, is there anything that you guys have been thinking about doing about the whole kind of the rat-hard customer issues with the marketing that you can't see them in person because of COVID? Is there kind of any plans about trying to do something, you know, virtually or differently about that?
spk04: So virtually doesn't work. It has to be some kind of secure communication. And so... Zoom is out, phone calls are out, emails are out. There's really two ways. It's face-to-face in a secure facility, or there are some encrypted secure communications, but those are also within buildings. They're not anything that we have. So we've had a few face-to-face meetings. One of our folks had to travel to New Mexico to do that, but it's certainly hampering that effort. on the RAT hard. As we discussed in the script, the RAT tolerant generally does not have a lot of that top secret notations on them, so we are starting to see some movement in the RAT tolerant and anticipate seeing our first order. If not this quarter, certainly it should hopefully happen next quarter, assuming the funding has been released.
spk06: All right, thank you very much. That was all for me.
spk02: We will now take our next question from Jeff Bernstein from Korn. Please go ahead.
spk05: Hi, guys. I just wanted to make sure I heard some of the timing right here. So the 600 megahertz board for the APU-1 is in testing now, and you see sales in H1 of 2021. Is that right?
spk04: So the solution is two-pronged. So it's the chip and the board. So right now we have a 400 megahertz chip with what we call the Lita G board. That's what we have today, and that's what customers who have tested our solution are looking at in all of our demos. So the next rev chip, which would be the 600 megahertz chips, we'll see it at the beginning – of 2021. In fact, we should have it in hand by January. Now, that solution also requires a little bit different LIDA board. It's actually called LIDA-E board. And the LIDA-E board, we should have some of those in hand by next month in November. So we won't start any testing until January at the soonest.
spk05: Okay. And that's sort of an interim speed bump. You don't actually really have to have that to make some sales before then.
spk04: Correct. So if you look at some of the solutions that we're going after, the facial recognition, the drug discovery, and some of these government and military applications we're looking at, The 400 megahertz solution is fine for them. Certainly, we'd like to see a bump in performance even further than what we have, and that's why we're offering the 600 megahertz. But like you said, there are applications where the 400 megahertz is fine.
spk05: Yeah, gotcha. Okay, and then on the Gemini 2, I think, did you say May 2022, you'll have that in hand, or what was that scheduling?
spk03: Yes, we say that at the end of 2022, calendar 2022, we'll have a chip on hand.
spk05: So at the end of calendar 2022? Yes. Gotcha. Okay. Okay, great. And then in terms of the design cycles for for RadHard and some of the just military applications for APU. What does that look like? So if you're talking to a guy like Mercury Computer that specializes in using off-the-shelf signal processing for CQDI kind of applications and they go, wow, this is great, super fast, right, recognition of targets and things like that, radar signals, et cetera, et cetera. We want to use that. How long is it before they can actually be buying that and have it in a subsystem that, you know, is going to UAV or whatever it is?
spk04: So that's a good question. It's hard to predict. So, you know, the first thing we need to do is obviously get the solution in their hand. So we have you know, two folks have already purchased in kind of that market segment you just mentioned, kind of the military arrow, have bought two of the Lita boards already. And we anticipate, you know, we don't have the orders yet, but we anticipate that we should sell five more Lita boards to that segment this quarter. And so these are all different customers within that realm. And so they need to get the board and start playing with it. Now, You know, we're showing them how to write their own microcode. And as, you know, Leland mentioned earlier in the talk, that we have a code generator already. But a full-blown compiler stack isn't going to be ready until January. And so if they are looking to write their own, they can get started now. If they're looking to be able to take one of their algorithms or softwares and be able to, you know, kind of throw it into our compiler on a high-level language, that's going to be – early next year before they can do that. So it's a little hard to predict the timing at this point.
spk06: All right. Thank you.
spk02: Once again, that is if you would like to ask a question. And at this time of moment, there appears to be no further questions. So I would like to send the conference back to you for any additional or closing remarks.
spk03: Thank you all for joining us today. We look forward to speaking with you again when we report our search for the physical 2021 results. Bye. That concludes today's call.
spk02: Thank you for your participation. You may now disconnect. Amen. Thank you. Thank you. Thank you. Bye.
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