The rise of connected devices has created a substantial surge in data generation. Traditionally, this data would be shipped to cloud servers for analysis, but this approach faces limitations like latency, bandwidth constraints, and privacy concerns. Enter Distributed AI, a paradigm that brings machine learning capabilities directly to the endpoint.

As our world evolves increasingly interconnected, the demand for intelligent systems that can process data in real time and at scale continues to soar. Traditional centralized AI models often face challenges because to latency concerns and bandwidth limitations. This is where Edge AI emerges as a transformative solution. By integrating AI algorithm