5G To Autonomous: Making Networks Think

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What if your network could understand intent, adapt in real time, and deliver the exact experience you need—whether you’re at a packed concert, inside an ambulance, or running a factory floor? We dive into the shift from manual engineering to autonomous networks and how open standards are making AI practical, measurable, and global.

Claudia Muñiz, Global Head of Sales for Cognitive Network Solutions at Ericsson, explains why 5G’s real promise is differentiated connectivity and how the Service Management and Orchestration (SMO) layer unlocks it. We trace the journey from early self-organizing networks to an open RAN ecosystem where developers ship RAN apps once and deploy everywhere. Expect clear examples of digital twins and multi-objective reinforcement learning tuning antennas across massive configuration spaces, with live results: higher throughput, faster speeds, fewer dropped calls, and better spectral efficiency—proof that AI at the radio layer moves the needle when paired with the right data and processes.

We also separate hype from reality on large language models in telco. Lightweight, energy-aware models handle millisecond decisions at the edge, while LLMs shine in cloud workflows, documentation, coding, and natural language operations. With partnerships that blend domain expertise and elastic compute, engineers can ask plain-English questions and get guided actions, all built on a unified, secure data layer. The conversation lands on what matters most: time-to-first value, measurable gains in churn, revenue, energy, and effort; and the near future of intent-based networking that coordinates specialized agents to meet business goals across open interfaces.

If you care about 5G, open RAN, AI-driven operations, developer ecosystems, and the real-world path to autonomous networks, this is your roadmap. Subscribe, share with a colleague who lives in dashboards, and leave a review with the one question you want us to tackle next.
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