Definition
Edge AI moves inference closer to where data is created. Instead of sending every input to the cloud, a local device runs a model and returns a fast, private, or offline result.
How it works
Teams compress or optimize models, deploy them to devices, monitor performance, and update them when requirements or data patterns change.
Why it matters at work
Edge AI can reduce latency, bandwidth, privacy exposure, and cloud dependency. It is useful in manufacturing, healthcare, retail, transport, and mobile apps.
Workplace example
A factory camera detects equipment anomalies locally so operators get alerts quickly without streaming every video frame to the cloud.
Frequently Asked Questions
Why use edge AI instead of cloud AI?
Use edge AI when latency, privacy, offline availability, bandwidth, or device autonomy matter more than centralized cloud scale.