Dedicated Computing has announced general availability (GA) and NVIDIA certification of its M1300 platform, designed to accelerate the development of next-generation AI-at-the-Edge healthcare and industrial automation devices.
The M1300 is an application-ready platform for real-time AI inference of visual data in medical and industrial applications. Medical use cases include endoscopies, laparoscopic procedures and advanced surgical displays. Industrial processes that rely on video data, such as precision robotics, machine vision, quality control and safety procedures, are also appropriate applications for the M1300 system.
Phil Spivey, CEO of Dedicated Computing, said: “We are proud to announce one of the first NVIDIA-Certified systems for IGX. This certification signifies a successful system-level evaluation of the performance of the M1300 across various environmental conditions, putting AI-at-the-Edge on the fast track.
“The milestone marks a significant step in building out our AI and Edge partner ecosystem,” continued Spivey.
NVIDIA IGX is an industrial-grade, Edge AI platform that combines enterprise-level hardware, software and support. Purpose-built for industrial and medical environments, IGX empowers organisations with the performance, durability, security and safety required for AI at the Edge.
The Dedicated Computing M1300 takes the power of NVIDIA IGX and tailors it for industrial and medical applications with, for example, IP-protection for cleaning. The platform is ‘60601-Ready,’ which means we have pre-tested it for compliance with medical device safety standards. Backed by 10-years-long lifecycle management, the M1300 is available with an optional extended warranty and our technical experts provide worldwide 24/7 support.
One example application is a surgical-assistant robotics system designed to provide extra arms that can hold minimally invasive probes, cameras and instruments in place during a procedure. By adopting the Dedicated Computing M1300, powered by NVIDIA IGX, the company has been able to focus its engineering resources on AI algorithms and other unique features, saving time and resources, and helping compress its development timeline.
