The rise of instrumented devices has created a significant surge in data generation. Traditionally, this data would be transmitted to centralized servers for processing, but this approach faces drawbacks like latency, bandwidth constraints, and privacy concerns. Enter Distributed AI, a paradigm that brings machine learning capabilities directly to … Read More

The landscape of artificial intelligence evolves at an accelerated pace, and edge computing has emerged as a essential component in this transformation. By implementing AI models directly on platforms at the network's edge, organizations can obtain significant gains. Edge AI solutions empower near real-time data processing, reducing latency and enh… Read More