Many people have begun experimenting with using machine learning in embedded systems as the two technologies have become more prominent in today’s society. That approach allows for overcoming many of ...

Somdip is the Chief Scientist of Nosh Technologies, an MIT Innovator Under 35 and a Professor of Practice (AI/ML) at the Woxsen University. As a leader in the artificial intelligence (AI) domain and a ...

Intel wrote a white paper in collaboration with Daedalean, a startup working on machine-learned solutions in the aviation space. Published this week, the report features a reference design for an AI ...

Embedded-systems designers are on a mission to squeeze powerful AI algorithms into resource-constrained gadgets, relying on cutting-edge custom hardware accelerators and high-level synthesis to push ...

Choosing flexible hardware for DNN architectures for apps like ATM camera systems. How "embeddings" can be effective in the image-recognition reidentification process. How Arcturus Networks developed ...

Machine learning is a subfield of artificial intelligence which gives computers an ability to learn from data in an iterative manner using different techniques. Our aim here being to learn and predict ...

Today, businesses face immense pressure to innovate. The rapid evolution of artificial intelligence and data analytics ...

SAN JOSE, Calif.--(BUSINESS WIRE)--SiMa.ai™, the machine learning company enabling high performance compute at the lowest power, today announced the adoption of low-power Arm® compute technology to ...

A new microcontroller claims to offer hardware-assisted machine learning (ML) acceleration for the Internet of Things (IoT) and industrial applications such as smart home, security surveillance, ...

Machine vision and embedded vision systems both fulfill important roles in industry, especially in process control and automation. The difference between the two lies primarily in image processing ...