As a leader in the artificial intelligence (AI) domain and a recognized expert specializing in embedded machine learning, I have firsthand experience with the profound potential of these emerging ...

The embedded machine learning features mean developers don’t have to extract data from another database to populate training models.

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.

Machine learning embedded A careful separation between machine learning and AI is necessary since both focus on implementing the best possible business solutions.

"We're thrilled to join the AWS ISV Accelerate Program and bring our embedded machine learning development tools to even more customers," said Zach Shelby, CEO of Edge Impulse.

The course includes segments on "how to use machine learning to make decisions and predictions in an embedded system" and "the concepts and vocabulary necessary to understand the fundamentals of ...

In this motor-control demonstration, a Renesas engineer explains how machine learning can help the system detect unbalanced load conditions.

A practical example from my own work in building AI responsibly involves deploying embedded machine learning—that is, running trained models directly on edge devices like smartphones without ...

A number of machine learning (ML) algorithms and techniques can be used to accomplish CV tasks, and as ML becomes faster and more efficient, we can deploy these techniques to embedded systems.

SiMa.ai, the machine learning company enabling effortless deployment and scaling at the embedded edge, today announced that it has begun shipping the ...

To solve decentralised monitoring tasks with embedded machine learning concepts and low-power IoT wireless data transmission without having to worry about the new cybersecurity requirements of RED or ...