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 ...

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 ...

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 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 ...

Configurable high-bandwidth RISC-V cores with vector units can be made to directly address challenging applications like machine learning, AI, and other cutting-edge spaces. Semidynamics is a European ...

Qeexo spun out of Carnegie Mellon University, has for a long time developed multi-touch technology for handset manufacturers which does ML on the device level. It has applied this approach to a new ...

CAMBRIDGE, Mass.--(BUSINESS WIRE)--InterSystems, a creative data technology provider dedicated to helping customers solve their most critical scalability, interoperability, and speed problems, today ...

How deep learning enhances rule-based machine vision in quality and process control inspection applications. How edge learning compares to deep learning in machine-vision applications. Which ...

Machine learning, with its ability to analyze large datasets and identify patterns, is particularly well-suited to address the challenges presented by the vast and complex data generated in ...