By leveraging AI/ML-driven modeling, Keysight enables semiconductor companies to accelerate innovation, reduce development ...

What happens when intelligence moves off the cloud and onto the device? Edge AI Studio cuts latency, improves performance, ...

Vikram Gupta is Chief Product Officer, SVP & GM of the IoT Processor Business Division at Synaptics, a leading EdgeAI semiconductor company. In my previous articles, I explored how the rapid growth of ...

Machine Learning (ML) algorithms have revolutionized various domains by enabling data-driven decision-making and automation. The deployment of ML models on embedded edge devices, characterized by ...

Overview: Edge AI devices prioritize local inference to ensure user data remains stored on the physical hardware instead of ...

SAN JOSE, Calif.--(BUSINESS WIRE)--Edge Impulse, the leading platform for building, deploying, and scaling edge machine learning models, has unveiled a suite of new industry first edge AI tools ...

Keysight Technologies has launched a new Machine Learning Toolkit within its Device Modelling Software Suite, designed to ...

Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...

AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...

The value of edge AI within various industries. How edge AI utilizes machine learning. Which hardware works best with edge AI workloads. From smart-home assistants (think Alexa, Google and Siri) to ...

Artificial intelligence has become a crucial part of research and everyday life. The most powerful models require a large amount of data and energy for their training and development, and the ...