GTCH - GBT Receives Patent Grant Notification Covering its Integrated Circuits Reliability Verification Analysis and Auto-Correction Technology | Benzinga
The Patent is scheduled for Grant on September 19, 2023
SAN DIEGO, Sept. 07, 2023 (GLOBE NEWSWIRE) -- GBT Technologies Inc. (OTC PINK: GTCH) ("GBT" or the "Company"), received a grant notification for its microchip's reliability verification and auto-correction EDA patent application, internal project's code name, Epsilon. The patent will be granted as U.S. Patent No. 11,763,062 on September 19, 2023. GBT's Epsilon patent application covers the innovative technology to address advanced semiconductor node physics with the goal of ensuring a high level of reliability, optimal thermal design, lower power consumption and high performance. The described technology includes machine learning algorithms to enable robust design, process optimization, characterization, modeling, and simulation. The technology underlying the patent identifies reliability flaws, describes the found issues, and allows an automatic correction of these reliability issues early during the IC's design phase. Machine Learning techniques will be performing data analysis, identification, categorization, and reasoning about executing the optimal IC layout automatic correction. The technology aims to allow IC designers to analyze and fix circuits early during the design phase in real time with the goal of creating higher efficiencies. GBT plans to continue its R&D efforts in this domain, inventing modern technologies and enabling reliable, low-power, high-performance, next-generation microchips.
"We are excited to share that our Epsilon patent has been granted. This patent aims to perform an early electrical and power analysis of a microchip during the design phase. The goal is to identify potential failures and provide solutions as early detection and elimination of reliability issues can save a significant amount of time in engineering redesign. The technology is planned to be powered by GBT's machine learning algorithms for pattern recognition and vast data analysis, especially ...