It has performed more than 8,500 AI training jobs across 10,000 edge devices, and its open-source federated machine learning library has become the most popular in the industry, surpassing Google ...

Researchers have developed a new binarized neural network (BNN) scheme using ternary gradients to address the computational challenges of IoT edge devices. They introduced a magnetic RAM-based ...

Edge AI offers the capability to unlock better performance, scalability, security, and innovation. It’s transformative because it uses AI directly within a device, computing near the data source ...

Edge AI can reduce costs and provide a more privacy for running large AI models. Qualcomm knows how to do it.

Diversity of compute elements proliferates for inference, but the mix varies by application. With AI changing so fast, it’s a ...

The extensive deployment of edge devices reveals numerous concerns, which can be particularly challenging when remote debugging is essential in multi-tenant environments.

Devices and sensors must be able to operate in a standalone manner to perform computing, analysis, learning, training, and inference in the field, wherever that may be. Whether on the battlefield or ...