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 ...

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 ...

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 ...

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 ...

From surveillance and access control to smart factories and predictive maintenance, the deployment of artificial intelligence (AI) built around machine learning (ML) models is becoming ubiquitous in ...

AI models have demonstrated impressive results in experiments, but deploying them in real-world applications requires combining neural networks with pre- and post-processing steps. Thus the need for ...

Building on its growing momentum in the market for hybrid transactional/analytical database management systems, Oracle Corp. today added machine learning capabilities ...

The courses offered in this catalog are a curated collection of learning materials that provide an overview of Industry 4.0. It is designed to provide resources that businesses can use to understand ...

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 ...