GSI Technology, Inc. (NASDAQ:GSIT) Q4 2023 Earnings Call Transcript May 16, 2023
Operator: Greetings, and thank you for standing by. Welcome to the GSI Technology’s Fourth Quarter and Fiscal 2023 Results Conference Call. [Operator Instructions] 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 & Exchange Commission. Additionally, I have also been asked to advise you that this conference call is being recorded today, May 16, 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.
Lee-Lean Shu: Good day, everyone, and welcome to our fiscal fourth quarter and full year 2023 financial results earnings call. The 2023 fiscal year was filled with many positive developments, new partnerships, and progress toward achieving our goals. We also experienced setbacks and unforeseen delays on several fronts with the APU. We learned a lot during the year about the addressable market Gemini-I can reasonably pursue with our team, given our limited resources. However, we recently have made significant strides in leveraging third-party resources to help identify users, resellers, and OEMs. These resources are proving valuable in helping us identify opportunities for capturing revenue and increasing awareness of the APU’s tremendous capabilities.
We have also sharpened our focus for Gemini-I to leverage our resources and prioritize near-term opportunities, such as synthetic aperture radar, or SAR, and satellites, where we have a superior solution. We understand these markets and know whom we can support and help with our offering. Another focus application for Gemini-I is vector search engines, where our APU plug-in has demonstrated enhanced performance. To this end, we have dedicated more resources and prioritized the target customers that have expressed interest in leveraging our solution. Our data science team has been busy working on a SaaS search project with one leading provider, and we plan to pivot to other players in the space once we have met our deliverables with the first partner.
Looking ahead on our roadmap, we will build upon the work we are doing today in future APU versions to address large language model or LLM for natural language processing. Vector search engines are a fundamental part of ChatGPT architecture and essentially function as the memory for ChatGPT. Large language models use deep neural networks, such as transformers, to learn billions or trillions of words and produce text. This is another reason that vector search is an appropriate focus application with the APU. Additionally, we are improving our SearchiumAI SaaS platform to support our go-to-market strategy for search. We intend to use this tool to develop more potential partnerships like an Open AI plugin integration that we recently launched, and with other open-source, decentralized search engines that use machine learning algorithms and vector search engines.
The increasing size and complexity of enterprise data sets and the proliferation of AI in all aspects of business are driving rapid growth in these search engines. Encouraged by the positive reception of our APU plug-in by several key players, we are optimistic about generating modest revenue from this market in the fiscal year 2024. For both of the Gemini-I focus applications I have just mentioned, SAR and Fast Vector Search, we have set specific revenue goals that we aim to achieve this fiscal year. Our L-Python compiler stack has progressed in the past quarter. Our L-Python compiler stack is designed to offer Python’s development advantages while delivering C’s high performance without compromising either. Although our current focus applications do not require a compiler, we have a beta version in use currently and are on track to release a production-ready version later this year.
L-Python will demystify the APU for any Python or C-developer. I am excited to announce that we are on track to complete the tape-out for Gemini-II by this summer and evaluate the first silicon chip by the end of calendar year 2023. We aim to bring this solution to market in the second half of 2024. Gemini-II’s design will provide significant performance enhancements with reduced power consumption and latency. These features will expand the future addressable market for the APU to larger markets such as edge applications, Fast Vector Search, LLM, and advanced driver assistance systems, or ADAS, the last one being a vertical we would go after with a strategic partner rather than directly. Gemini-II is built with TSMC 16nm process. The chip contains 6 Mega-Byte of associative memory connected to 100 Meg-Byte distributed SRAM with 45 Mega Byte per second bandwidth or 15 times the memory bandwidth of the state-of-the-art parallel processor for AI.
This is more than 4 times the processing power and 8 times of memory density compared to Gemini-I. The Gemini APU is built with bit processing, which allows fully flexible data format operation, an inherent advantage versus other parallel processors. Gemini-II is a complete package that includes a DDR4 controller and external interfaces for PCIe Gen4 by 16 and PCIe Gen4 by 4. This integrated solution allows Gemini-II to be used in affordable edge applications while still providing significant processing capabilities. In simpler terms, Gemini-II combines different components together, allowing it to be used in less expensive devices while still being powerful enough to handle demanding tasks at the edge of a network. Put another way, Gemini-II brings data center capabilities to the edge.
This means that computationally intense applications can be done locally. For example, ADAS, delivery drones, autonomous robots, and UAV or unmanned aerial vehicles and satellites. Another application for Gemini-II would be IoT edge applications like critical infrastructure or processes requiring a reliable and efficient operation, for example, wind farms, to mitigate failure modes that can lead to significant financial losses or operational disruptions. Gemini-II’s combination of high processing power, large built-in memory with tremendous bandwidth and low-cost solution provides a best-in-class solution for AI applications like Fast Vector Search, a growing market driven by the proliferation of big data and the need for fast and accurate processing.
Recently, we were granted a new patent for Gemini-II’s in-memory full adder, which is a basic building block to allow Gemini-II to perform high processing power. We are thrilled to announce that we are currently in very early-stage discussions with a top Cloud Service Provider to explore how Gemini-II’s foundational architecture could deliver performance advantages. Just this year, we have seen the disruptive impact of large language models that understand and generate human-like language, like ChatGPT, Microsoft BING and Google’s Bard. As the boundaries of Natural Language Processing continue to be pushed, we envision abundant opportunities in this market for Gemini-II and future versions of the APU. We believe that we have merely scratched the surface of the potential of large language models and the transformative impact they can have across numerous fields.
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Large language models’ attention memory requires very large built-in memory and very large memory bandwidth on-chip. The state-of-the-art GPU solutions have built-in 3D memory to address the high-capacity memory requirement but has poor memory bandwidth for adequate memory access. The limitation is going to get worse as large language models are progressing. Gemini chip architecture has inherently large memory bandwidth, it is a natural migration to add 3D memory for the next generation Gemini chip to address the large memory requirement. This substantial improvement potentially translates into orders of magnitude better performance. As a result, we would be strongly positioned to compete effectively in the rapidly expanding AI market, standing ahead of the industry’s leading competitors.
Our resources and teams are focused on applications where we have a high probability of generating revenue to capitalize on Gemini-I’s capabilities. As we bring Gemini-II to market, we will be more experienced in approaching target customers and creating new revenue streams. We are formulating our roadmap for the APU, which holds tremendous potential. With future versions, the APU has the capability to cater to much larger markets, and the potential opportunities are quite promising. In parallel with our Board of Directors, we are actively exploring various options to create shareholder value. I remain fully committed to driving sustained growth and innovation in the years ahead. Thank you for your support and for joining us today. We look forward to updating you on our progress in the coming quarters.
Now I’ll hand the call over to Didier, who will discuss our business performance further. Please go ahead, Didier.
Didier Lasserre: Thank you, Lee-Lean. As Lee-Lean stated, we have sharpened our focus on a few near-term APU revenue opportunities. In addition, we strengthened our team with a top data science contractor whose primary job is to accelerate the development of our plugin solution for the high-performance search engine platforms that Lee-Lean mentioned. We have also begun working with a company that offers custom, embedded AI solutions for high-speed computing using Gemini-I and Gemini-II. Another critical development to improve our market access for the APU has been adding distributors. We are pleased to announce that we have added a new distributor for our Radiation Hard and Tolerant SRAM, and our hardened APU, for the European market.
In addition to our partnerships and focus on near-term opportunities, we plan to build a platform to enable us to pursue licensing opportunities. This is in the very early stages, and we have work to do before we formally approach potential strategic partners. That said, we have had a few preliminary conversations on determining what is required to integrate Gemini into another platform. This would allow us to identify the specific performance benefits for a partner’s applications to ensure effective communication of the problem we solve in their system or solution. We recently demoed Gemini-I for a private company specializing in SAR satellite technology. They provide high-resolution Earth observation imagery to government and commercial customers for disaster response, infrastructure monitoring, and national security applications.
The satellites are designed to provide flexible, on-demand imaging capabilities that customers can access worldwide. They recently provided the datasets to conduct comparison benchmarks on Gemini-I, and we are commencing the process of running those benchmarks. SAR is one market we anticipate that we can generate modest revenue with Gemini-I this fiscal year. GSI was recently awarded a Phase 1 Small Business Innovation Research, or SBIR, contract. SBIR is a United States government program that supports small business R&D projects that could be commercialized for specific government needs. For this contract, we will collaborate with the Air and Space Force to address the problem of edge computing in space with Gemini-I. Gemini I is already radiation-tolerant, making it particularly well-suited for Space Force missions.
This contract is a milestone for GSI Technology, as it will showcase the APU’s capabilities for the military and other government agencies and provide great references for similar applications. We have submitted other proposals for a direct-to-Phase 2 project and have other SBIR proposals in the pipeline. On that note, we received verbal confirmation just this morning that we have been awarded a Research and Development contract, which could be worth up to $1.25 million, to integrate GSI’s next-generation Gemini-II for Air and Space Force Missions applications. This revenue would be recognized as milestones are achieved, and a typical timeframe is 18 months to two years. Once the agreement has been finalized and executed, we will issue a press release with the full details.
Let me switch now to the customer and product breakdown for the fourth quarter. In the fourth quarter of fiscal 2023, sales to Nokia were $1.2 million, or 21.8% of net revenues, compared to $2.0 million, or 23.1% of net revenues, in the same period a year ago and $1.3 million, or 20.0% of net revenues, in the prior quarter. Military/defense sales were 44.2% of fourth quarter shipments compared to 22.3% of shipments in the comparable period a year ago and 26.2% of shipments in the prior quarter. SigmaQuad sales were 46.3% of fourth quarter shipments compared to 47.6% in the fourth quarter of fiscal 2022 and 45.2% in the prior quarter. I’d now like to hand the call over to Doug. Go ahead, Doug.
Douglas Schirle: Thank you, Didier. I will start with the fourth quarter results summary, followed by a review of the full-year fiscal 2023 results. GSI reported a net loss of $4 million, or $0.16 per diluted share, on net revenues of $5.4 million for the fourth quarter of fiscal 2023, compared to a net loss of $3 million, or $0.12 per diluted share, on net revenues of $8.7 million for the fourth quarter of fiscal 2022 and a net loss of $4.8 million, or $0.20 per diluted share, on net revenues of $6.4 million for the third quarter of fiscal 2023. Gross margin was 55.9% in the fourth quarter of fiscal 2023 compared to 58.6% in the prior-year period and 57.5% in the preceding third quarter. The decrease in gross margin in the fourth quarter of 2023 was primarily due to the effect of lower revenue on the fixed costs in our cost of goods.
Total operating expenses in the fourth quarter of fiscal 2023 were $6.9 million, compared to $8.1 million in the fourth quarter of fiscal 2022 and $8.5 million in the prior quarter. Research and development expenses were $5 million, compared to $6.5 million in the prior-year period and $5.5 million in the prior quarter. Selling, general and administrative expenses were $1.9 million in the quarter ended March 31, 2023, compared to $1.5 million in the prior-year quarter and $3 million in the previous quarter. Fourth quarter fiscal 2023 operating loss was $3.9 million compared to an operating loss of $2.9 million in the prior-year period and an operating loss of $4.8 million in the prior quarter. Fourth quarter fiscal 2023 net loss included interest and other income of $101,000 and a tax provision of $191,000, compared to $47,000 in interest and other expense and a tax provision of $21,000 for the same period a year ago.
In the preceding third quarter, net loss included interest and other income of $61,000 and a tax provision of $84,000. Total fourth quarter pre-tax stock-based compensation expense was $515,000 compared to $714,000 in the comparable quarter a year ago and $654,000 in the prior quarter. For the fiscal year ended March 31, 2023, the Company reported a net loss of $16.0 million, or $0.65 per diluted share, on net revenues of $29.7 million, compared to a net loss of $16.4 million, or $0.67 per diluted share, on net revenues of $33.4 million in the fiscal year ended March 31, 2022. Gross margin for fiscal 2023 was 59.6%, compared to 55.5% in the prior year. The increase in gross margin was primarily due to product mix. Total operating expenses were $33.5 million in fiscal 2023, compared to $34.9 million in fiscal 2022.
Research and development expenses were $23.6 million, compared to $24.7 million in the prior fiscal year. Selling, general and administrative expenses were $9.9 million, compared to $10.2 million in fiscal 2022. The decline in research and development expenses was primarily due to the cost reduction measures announced by the Company in November 2022. The operating loss for fiscal 2023 was $15.8 million compared to an operating loss of $16.4 million in the prior year. The fiscal 2023 net loss included interest and other income of $202,000 and a tax provision of $372,000, compared to $60,000 in interest and other expense and a tax benefit of $45,000 a year ago. At March 31, 2023, the Company had $30.6 million in cash, cash equivalents, and short-term investments and no long-term investments, compared to $44 million in cash, cash equivalents, and short-term investments and $3.3 million in long-term investments at March 31, 2022.
Working capital was $34.7 million as of March 31, 2023, versus $45.8 million at March 31, 2022, with no debt. Stockholders’ equity as of March 31, 2023, was $51.4 million compared to $64.5 million as of the fiscal year ended March 31, 2022. Operator, at this point, we will open the call to Q&A.
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GPT’s reaction to this article:
The article reports on GSI Technology’s Q4 and fiscal 2023 results conference call, where the company’s Chairman, President, and CEO, Lee-Lean Shu, discussed the progress made in leveraging third-party resources to identify revenue opportunities and increase awareness of the APU’s capabilities. The company has sharpened its focus on near-term opportunities, such as synthetic aperture radar and satellites, where they have a superior solution, and vector search engines, where their APU plug-in has demonstrated enhanced performance. They are also improving their SearchiumAI SaaS platform to support their go-to-market strategy for search. The company is optimistic about generating modest revenue from these markets in fiscal year 2024. The company is also on track to complete the tape-out for Gemini-II by this summer and evaluate the first silicon chip by the end of calendar year 2023. Gemini-II’s design will provide significant performance enhancements with reduced power consumption and latency.