What is ensemble learning in edge AI systems?

Edge AI ensembles optimize multiple lightweight models for real-time inference on resource-constrained devices.

Edge AI systems run on limited hardware like mobile devices or IoT sensors. Ensembles in this context must balance accuracy and efficiency. Techniques include model pruning, quantized ensembles, and lightweight voting mechanisms. Instead of large models, multiple small models are combined to improve robustness while maintaining low latency.