AI Glossary
Edge AI
AI systems that run directly on local devices rather than relying entirely on cloud-based processing.
Edge AI
Overview
Many AI systems operate in the cloud.
When a user submits a request, information is sent to remote servers where the AI model processes the request and returns a response.
However, not every AI application works this way.
Some AI systems operate directly on local devices such as smartphones, vehicles, cameras, sensors, and industrial equipment.
This approach is known as Edge AI.
A helpful way to think about Edge AI is the difference between asking someone for directions over the phone versus carrying a map with you.
When AI runs locally, decisions can often be made more quickly because information does not need to travel to a remote server and back.
This can reduce latency, improve responsiveness, and enhance privacy.
As hardware continues to improve, Edge AI is becoming increasingly common in areas such as autonomous vehicles, smart manufacturing, healthcare devices, and consumer electronics.
Many experts believe Edge AI will play an important role in the future of artificial intelligence.
Why It Matters
Edge AI allows AI systems to operate closer to where information is generated.
Real-World Example
A security camera that identifies objects locally without sending video to the cloud is an example of Edge AI.