According to a new press release, “DeepCube, the award-winning deep learning pioneer, today announced the launch of the only software-based inference accelerator that drastically improves deep learning performance on any existing hardware. Today, deep learning deployments are very limited and are primarily optimized for the cloud; and, even in these cases, they incur extensive processing costs, significant memory requirements, and expensive power costs, due to intensive computing demands. These challenges also plague deep learning deployments on edge devices, including drones, mobile devices, security cameras, agricultural robots, medical diagnostic tools and more, where the current size and speed of deep neural networks has limited their potential.”
The release continues, “DeepCube focuses on research and development of deep learning technologies that improve the real-world deployment of AI systems. The company’s numerous patented innovations include methods for faster and more accurate training of deep learning models and drastically improved inference performance on intelligent edge devices. DeepCube’s proprietary framework can be deployed on top of any existing hardware (CPU, GPU, ASIC) in both datacenters and edge devices, enabling over 10x speed improvement and memory reduction. ‘Many deep learning frameworks were developed by researchers, for researchers, and are not applicable to commercial deployment, as they are hindered by technological limitations and high cost requirements for real-world applications,’ said Dr. Eli David, Co-Founder, DeepCube. ‘DeepCube’s technology can enable true deep learning capabilities within autonomous cars, agricultural machines, drones, and could even help potentially monitor for and prevent future global health crises, much like the one we are facing now in 2020’.”
Read more at Business Wire.
Image used under license from Shutterstock.com