Overview
Edge AI brings intelligence closer to the data source. By running models locally, devices can make decisions in real-time without needing a constant internet connection or sending sensitive data to the cloud.
Benefits
- Low Latency: Immediate processing for time-critical tasks (e.g., autonomous braking).
- Privacy: Data stays on the device, reducing exposure risks.
- Bandwidth Savings: Only relevant insights are sent to the cloud, not raw data streams.
- Offline Functionality: Works in remote areas with poor connectivity.
Challenges
- Resource Constraints: Limited memory, processing power, and battery life on edge devices.
- Model Optimization: Requires techniques like quantization and pruning to fit models on small hardware.