$3.200
-0.387 (-12.09%)收盤時
GSIT 資訊
GSIT 事件
GSI Technology Completes Initial Phase of Smart Eye Guardian Project in Hsinchu County
GSI Technology announced the completion and acceptance of the initial stage of Phase I of its Smart Eye Guardian project with the Hsinchu County government in Taiwan. The project, awarded in May, represents GSI's first Smart City deployment of its Gemini-II APU. Developed under the project name Hawkeye, the company's AI-powered video analytics platform has begun live monitoring of selected surveillance cameras in Hsinchu County. The initial on-prem server installation, supporting 20 cameras, was completed following successful passage of the County's mandated cybersecurity review.
GSI Technology Awarded Phase I of Smart City Project by Hsinchu County
GSI Technology announced it has been awarded Phase I of a Smart City project by the Hsinchu County government in Taiwan. The completion of Phase I will mark the company's first smart city deployment of the Gemini-II APU. The initial Phase I contract represents the first stage of a multi-phase program. If awarded, the follow-on phases could generate a multi-million-dollar opportunity for hardware and recurring software licensing revenue. The project builds on GSI's previously announced Sentinel program and, if follow-on phases are awarded, will deploy an AI-based video analytics platform powered by the Gemini-II APU across a large installed base of network-connected surveillance cameras.
GSI Technology Awarded $2M Army Contract
GSI Technology announced it has been awarded a Phase-II U.S. Army's xTech Small Business Innovation Research program to develop a ruggedized edge AI platform using the Gemini-II APU for the tactical edge. The award is valued at approximately $2M. These funds will offset the cost of designing and developing a ruggedized edge-processing platform based on the Gemini-II APU, with testing in representative operational environments intended to validate performance across real-time AI workloads, such as sensor data processing, object detection, and command-and-control analytics.
GSI Technology Confirms Standalone Strategy
The company said, "GSI Technology announced that its Board of Directors has concluded the Company's previously announced review of strategic alternatives. In reaching this determination, the Board considered the Company's operational and financial progress and the strengthened balance sheet following the October 2025 capital raise, which provided additional resources to support GSI Technology's go-forward plan. As part of the review, the Board and its advisors engaged with multiple parties and evaluated a range of potential alternatives. After careful consideration, the Board concluded that continuing to execute the Company's standalone strategy is in the best interests of stockholders at this time. The Company intends to focus on driving commercialization of its high-performance memory and compute solutions, advancing key customer programs, and prudently allocating capital to initiatives that support sustainable growth. This decision reflects the Company's view that the October 2025 financing further positions GSI Technology to pursue its strategic and operational objectives."
GSI Technology Announces Gemini-II Processor Benchmark Results
GSI Technology announced preliminary benchmark results for the Gemini-II Compute-in-Memory processor. These results demonstrated 3-second time-to-first-token performance for multimodal large language models operating at the edge with video and text inputs. "These benchmark results highlight what compute-in-memory can enable for physical AI," said Lee-Lean Shu, President and Chief Executive Officer of GSI Technology. "Edge deployments require fast response under tight power and thermal limits. A 3-second TTFT means the system can generate an initial response every three seconds, which is generally fast enough to be useful in video-based applications without missing meaningful events. Gemini-II's ability to deliver low-latency multimodal inference at low power supports a broader range of real-time applications, from autonomous systems to intelligent machines operating outside the data center."
相關文章
- How to Rebalance a Concentrated Stock Portfolio in 2026: Mag7 Drift, Tax-Aware Trims, and Practical Rebalance a concentrated stock portfolio in 2026: Mag7 drift risk, 5pp bands, tax-aware trims, RSP/IWM diversifiers, and single-name caps.
- Small Cap Stocks Investing Guide 2026: Russell 2000, Fed Hikes, and the Financing TradeSmall-cap stocks investing guide 2026: Russell 2000 vs S&P, IWM rate sensitivity, floating-rate debt, Fed hikes, valuation discounts, and a practical checklist.
- Santa Claus Rally and the Year-End Stock Market: Investor Guide for Late 2026Santa Claus rally explained: 7-day window stats since 1950, Nov–Dec seasonality, post-midterm 2026 setup, and a risk-managed year-end investing playbook.
本頁僅供研究參考,不構成投資建議。模型可能出錯。過往表現不代表未來結果。





