Scaling Edge AI: A Call for Hardware, Data and Talent
Edge devices, with their small footprints and low power, are often too constrained to support AI. What’s needed are new approaches to address these issues.
How edge computing and edge analytics use real-time data for a variety of applications, including IoT.
Edge devices, with their small footprints and low power, are often too constrained to support AI. What’s needed are new approaches to address these issues.
In this week's real-time analytics news: The MLCommons Association announced datasets to advance innovation in machine learning research and commercial …
Increased connectivity, such as that planned by Verizon via Amazon’s Project Kuiper, can bring organizations into the digital
Smart systems powered by 5G and edge technologies have the potential to improve safety on the roads and in industrial facilities. Jillian Kaplan of Dell …
As enterprises evolve to 5G edge-intensive architectures to deliver and process information, security basics get elevated in
Smart cities based on sustainable, resilient infrastructures enable structures, services, and technology frameworks to work together opening up limitless …
Edge computing requires elements that can fit into the limited space available, withstand harsh conditions, and run sophisticated analysis
With edge computing, workloads, storage, and networking infrastructures are moved closer to the sensors, actuators, and other IoT devices that generate and use …
Untethering compute from the cloud allows the broadening of AI’s reach. And it speeds up response time by reducing the lag caused by communicating with …
IoT gateways act as middlemen connecting your devices to the cloud and managing everything from data security, connectivity protocols to edge