What Business Leaders Need To Know About Developing Edge AI

Edge AI models in medical devices, industrial robots, and smart locks require higher accuracy than cloud models. A 97% accuracy rate in lab testing can fail in real-world conditions like heavy groceries or a burglar. Validation must include real hardware, environmental noise, and actual usage scenarios. Model drift occurs when devices encounter untrained data, leading to incorrect predictions or missed alerts. Accuracy depends on training data reflecting real-world conditions.