Company: GSIT
Filing Date: 2025-10-21
Form Type: 424B5
Source: 0001104659-25-101303
Chunk: 9

Company: GSI TECHNOLOGY INC
Filing Date: 2025-10-21
Form: 424B5
Chunk 9
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.S. Air Force Research Laboratory (“ AFRL ”) to leverage the compute-in-memory architecture of the Gemini ® APU. This chip is designed for various AI applications to tackle key challenges in the Department of the Air Force, including in-aircraft search and rescue, object detection, moving target indication, change detection, and structural similarity index measure (“ SSIM ”) in GPS-absent situations. We are also developing algorithms using data from the U.S. Space Force to showcase the performance benefits of our compute-in-memory APU2 integrated circuit. We will receive milestone payments totaling an estimated $1.1 million upon the successful completion of predetermined milestones, of which $157,000 was received in fiscal 2025.

In January 2025, we announced that GSI has been selected by the U.S. Army for a potential contract award of up to $250,000 under the Department of Defense SBIR program. The contract represents a significant opportunity for GSI to develop advanced, Army-specific edge computing AI solutions using our groundbreaking Gemini-II technology. The project will focus on two critical objectives that showcase the potential of our innovative architecture. First, we will determine the feasibility of integrating Gemini-II with AI models specifically tailored for the Army’s edge computing needs. This determination will involve a comprehensive assessment of operational challenges, optimization with the Gemini-II architecture, and establishing key performance metrics through detailed customer discovery and technical specifications for edge AI development. The second objective centers on identifying and validating the most suitable AI algorithms for the Gemini-II platform. We will conduct in-depth research to select efficient edge AI models, develop a detailed integration plan, and evaluate performance metrics for low-latency and high-throughput applications of value in military environments. Particularly noteworthy is the project’s focus on developing 1-bit Large Language Models (LLMs) for the U.S. Army that maintain high accuracy while providing exceptionally low power consumption and minimal latency. This innovation not only promises to benefit warfighters but also presents compelling application opportunities across multiple dual-use markets, including complex computer vision recognition, autonomous vehicle navigation and mobile data computation. There have been no payments received under this award as of March 31, 2025.

Our APU technology is implemented in a series of Gemini AI chips. Gemini-I is in full production. We are marketing specific differentiated applications and APIs as-a-Service adding Amazon Web Services, Azure, or Google Cloud Storage users to our customer base along with those that want on-prem or to build embedded edge products. We support customers with prebuilt APIs and libraries to support