Tri Cascade Enters Co-Development Arrangement with Aetina Corporation

NEWPORT BEACH, CA — Tri Cascade has engaged with Microsoft A.I. Edge computing partner, Aetina Corporation. An NDA has been executed by both parties, which enables Tri Cascade and Aetina to co-develop the building of A.I. home automation products, supported by Microsoft technology. This is key to the establishment of A.I. IoT capability independently in the home as a local “in-house” operation vs. relying on data transmission from the home to the Cloud and back down to the home.

“I am thrilled to be partnered with such a powerhouse as Aetina. They have proven themselves to be leaders in A.I. edge computing and will provide reality to our vision of future independent A.I. driven homes without reliance on external internet and Cloud communication,” said Max Li, Chief Executive Officer of Tri Cascade. “In our opinion, A.I. only works securely and consistently within the home if control rests with the consumer at the ‘in house’ level. Our co-development with Aetina will provide such a solution. Separately, I’m very encouraged by the progress made to date on our innovative indoor air quality monitor with the new Quectel chipset and, with the finalization of its design, I am looking forward to being able to place it into production in the near future.”

Founded in Taiwan from 2012, Aetina is dedicated to high performance GPGPU and Jetson AI edge computing solutions for embedded applications, with its focus on the development and long term support of highly reputable GPU-accelerated computing products for wide range of image-critical applications in edge computing markets, including medical, defense & aerospace, factory automation, gaming, machine learning and surveillance.

Aetina aims to not only provide better graphics solutions for mission critical applications, but also to enable the next generation of high performance embedded systems with total solution GPU accelerated computing Modern GPUs designed for intensive real-time image processing can efficiently perform massively parallel calculations that would overwhelm traditional CPUs, enabling new capabilities such as real time visualizations on large datasets for better results in the air, on the ground, or in the operating room.