GSI Technology, Inc.

Greetings and thank you for standing by. Your conference will begin momentarily. We thank you for your patience and ask that you please remain on the line. Thank you. Greetings and thank you for standing by. Welcome to the GSI Technologies fourth quarter and fiscal 2023 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 been asked to advise that this conference call is being recorded today, May 16th, 2023, at the request of GSI Technology. Hosting the call today is Li-Lin Xu, the company's chairman, president, and chief executive officer. With him are Douglas Shirley, chief financial officer, and Didier Lasserre, vice president of sales. I would now like to turn the conference over to Mr. Xu. Please go ahead, sir.

Good day, everyone, and welcome to our physical fourth quarter and full year 2023 financial results earning 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 APU, We learned a lot during the year about the stressful market GeminiOne can reasonably pursue with our team, given our limited resource. However, we recently have made significant strides in leveraging third-party resources to help identify users, resellers, and OEMs. These resources are proven 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 1 to leverage our resources and prioritize near-term opportunities, such as synthetic aperture radar, OSAR, 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 One is vector search engines, where our APU plugin 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 the 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 owner. Looking ahead on our roadmap, we will build upon the work we are doing today in future APU versions to address large language models. 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 levels, such as transformers, to learn billions or trillions of words and produce text. This is another reason that vector search appropriate focus application with the APU. Additionally, we are improving our search and AI SaaS platform to support our go-to-market strategy for search. We intend to use this tool to develop more potential partnerships, like 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 datasets 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 physical year 2024. For both of the Gemini OneFocus applications I have just mentioned, SAR and Fast Factor Search, we have set specific revenue goals that we aim to achieve this physical year. Our L-Python compiler stack has brought progress in the past quarter. Our L-Python compiler stack is designed to offer Python's development advantage by delivering C's high performance without compromise either. Although our current focus application 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. Your Python will demystify the APU for any Python OC developer. I'm excited to launch this. We are on track to complete the table for Gemini 2 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 2's design will provide significant performance enhancement with reduced power consumption and latency. This feature will extend the future addressable market for the APU to larger markets, such as edge applications, Fast Factor Search, LLM, and Advanced Driver Assistance System, or ADAS. The last one being the vertical we could go after with a strategic partner rather than directly. Gemini 2 is built with a TSMC 60nm process. The chip contains 6MB of associated memory. connected to 100 megabytes distributed with 45 terabytes per second bandwidth, or 15 times the memory bandwidth of the state-of-the-art parallel processor for AI. This is more than four times the processing power and eight times the memory density compared to Gemini One. The Gemini APU is built with big processing. which allows fully flexible data format application and inherent advantage versus other parallel processors. Gemini 2 is a complete package that includes a DDR4 controller and external interface for PCIe Gen 4 by 16 and PCIe Gen 4 by 4. This integration solution allows Gemini 2 to be used in foldable edge applications while still providing significant processing capabilities. In simple terms, Gemini 2 combines different components together, allowing to be used in less expensive devices, while still being powerful enough to handle demanding tasks at the edge of a network. To another way, Gemini 2 brings data center capability to the edge. This means that computationally intensive applications can be done locally, For example, ADAS, delivery zone, autonomous robot, and the UAV, or unmanned aerial vehicle, and satellites. Another application for Gemini 2 could be IoT edge application, like critical infrastructure, or process requiring a reliable and efficient operation. For example, wind farms to mitigate failure mode that can lead to significant financial losses, or operational disruptions. Gemini 2's combination of high processing power, large viewing memory, with tremendous bandwidth and low cost solution provides the 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 growing a new patent for Gemini 2's in-memory food adder, which is a basic building block to allow Gemini 2 to perform high processing power. We are thrilled to announce that we are currently in very early stage discussion with the top cloud service provider to explore how Gemini 2's foundational architecture could deliver performance advantage. Just this year, we have seen the disruptive impact of large language models to understand and generate human-like language, like ChatGVT, Microsoft Bing, and Google's Bar. As the boundary of natural language processing continues to be pushed, we envision abundant opportunity in this market for Gemini 2 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. Large language models attention memory requires very large built-in memory, a very large memory bandwidth armchair. The state-of-the-art GPU solution has built-in 3D memory to address the high capacity memory requirement, but has a 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 natural migration to add 3D memory for the next generation Gemini chip to address large memory requirement. This substantial improvement potentially translates into orders of magnitude better performance. As a result, we could be strongly positioned to compete effectively in the rapidly expanding AI market, standing ahead of the industry-leading competitors. Our resources and teams are focused on applications where we have a high probability of general revenue to capitalize on Gemini 1's capabilities. So we bring Gemini 2 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 the 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 and remain fully committed to drive sustainability. growth and innovation in the year 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 will hand the call over to Didi, who will discuss our business performance further. Please go ahead, Didi.

Thank you, Lilien. As Lilien stated, we have sharpened our focus on a few near-term APU revenue opportunities. In addition, we have strengthened our team with a top data science contractor whose primary job is to accelerate the development of our plug-in solution for the high-performance search engine platforms that Leline mentioned. We have also begun working with a company that offers custom embedded AI solutions for high-speed computing using Gemini 1 and Gemini 2. 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, but also 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 a few preliminary, I'm sorry, we have had a few preliminary conversations on determining what is required to integrate Gemini technology into another platform. This would allow us to identify the specific performance benefits for partners' applications to ensure effective communication of the problem we solve in their system or solution. We recently demoed the Gemini One 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 the Gemini 1, and we are commencing the process of running those benchmarks. SAR is one market we anticipate that we can generate modest revenue with Gemini One this fiscal year. GSI was recently awarded a phase one small business innovation research, also known as SBIR. 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 1. Gemini 1 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 two project and other SBIR proposals are 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 2 for air and space force mission applications. This revenue will be recognized as milestones are achieved and a typical timeframe is 18 months to two years. Once this agreement, I'm sorry, once the agreement has been finalized and executed, we will issue a press release with 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 million or 23.1% of net revenues in the same period a year ago. and 1.3 million or 20% 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. Sigma quad 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.