This article was originally published in early 2025 and was last updated on June 11th, 2025. Tension: Companies ...

However, bringing AI capabilities to IoT edge devices presents a significant challenge. Artificial neural networks (ANNs)―one of the most important AI technologies―require substantial ...

Edge and cloud computing will probably work more in concert in IoT’s future. Low-latency communication will enable even more fluid integration of edge and cloud capabilities as 5G networks spread.

Predictive maintenance, driven by the Internet of Things (IoT) and edge computing, is one important innovation that has surfaced to enable financial institutions to remain resilient and cost ...

Towards implementing neural networks on edge IoT devices Researchers propose a novel magnetic RAM-based architecture that leverages spintronics to realize smaller, more efficient AI-capable circuits ...

And last June, Google released its Cloud IoT Edge platform, which “extends Google Cloud’s data processing and machine learning to edge devices,” according to Forbes. Challenges in Embracing an Edge ...

Edge computing, machine learning algorithms and centralized management platforms work in tandem to ensure industrial systems keep running.

The Internet of Things (IoT), which refers to the use of connected sensors and actuators to control and monitor the ...

Taking immediate action on sensor data is vital in modern Internet of Things (IoT) systems. Real-time streaming serves as the fundamental structure of IoT analytics because it enables automated ...

CMU's Swarun Kumar explains how software-defined wireless networks, low-power IoT, and edge computing will define the post-6G ...

BrainChip and HaiLa collaborate to deliver ultra-low-power edge AI connectivity for IoT sensor applications.