Cloud computing, with its virtually unlimited set of resources, leads people to expect a lot from AI. In a big data center, the most important
A Technical Deep-Dive into Distributed AI at the Edge Introduction There is a profound architectural parallel hiding in plain sight between two of the most
A technical deep-dive into the ZEDEDA Camera Monitoring Agent for PCB Quality Inspection at the Edge using NVIDIA Jetson Thor Summary Modern electronics manufacturing demands
When I talk to customers about the edge, I always try to get to where the rubber meets the road. Over the last several years,
Why “Edge Intelligence”? When we founded ZEDEDA, our mission was simple: make it effortless to deploy and manage edge infrastructure reliably, securely and at scale, providing
In 2026, AI will increasingly be defined by where it runs. As intelligence is deployed across factories, retail environments, and remote operational sites, the focus
For software architects building edge systems, shifting from traditional systems design to AI implementation often presents a specific hurdle: how to move from centralized to
Introduction Here at ZEDEDA, we’re always pushing the limits of running AI at the edge. We’re especially excited by powerful edge platforms like NVIDIA Jetson AGX
How ZEDEDA brings consistency, choice and scale to edge environments Edge environments are diverse by design. Some sites run compact, single-purpose applications; others host distributed,
How ZEDEDA extends Kubernetes to simplify AI deployment across diverse edge environments AI workloads are moving closer to the data they analyze. But running AI