Agentic AI

Traditional telecom networks, built primarily for voice and data services, are increasingly inadequate for modern AI workloads. The rise of edge computing, real-time applications, and autonomous AI agents requires networks…

The architecture presented here represents a practical approach to autonomous RAN implementation, moving beyond theoretical frameworks to actionable deployment strategies. By leveraging Agentic AI for intelligent decision-making and eBPF for deep network visibility, this system provides the foundation for self-optimizing networks that can meet the demands of advanced telecommunications infrastructure

A research report  conducted just prior to the passing of US tariffs ) from the Boston Consulting Group (BCG) points to a notable increase in IT budgets for 2025, with…

Traditional telecommunications infrastructure has long relied on manual configuration and semi-automated processes, leading to operational inefficiencies and lengthy deployment cycles. While AI has transformed many industries, its application in telecom…

The rising number of connected devices and data demands are putting a significant strain on network infrastructure. AI-native networks, especially those using agentic AI, are addressing these challenges by implementing…

The rising number of connected devices and data demands are putting a significant strain on network infrastructure. AI-native networks, especially those using agentic AI, are addressing these challenges by implementing…

This blog has covered spending in hardware acceleration which only has grown due to the emergence of Agentic AI. Agentic AI, referring to AI systems that can act independently to…