Room U
Workshop

AI and Machine Learning in communication networks

In person
  • Date
    9 July 2025
    Timeframe
    09:00 - 17:15 CEST
    Duration
    2 days
    Share this session

    This workshop marks the 3rd edition of the MLComm series, continuing the exploration of AI/ML in modern communication networks. As networks evolve towards IMT-2030 (6G), AI/ML is transforming telecom architectures, enabling distributed intelligence, AI-native operations, and multimodal capabilities for automation, optimization, and decision-making.

    The 2023 edition provided foundational inputs to the Focus Group on Autonomous Networks, while the 2024 edition facilitated collaborations toward the Focus Group on AI-Native Networks.

    The workshop aligns with key ITU standardization activities, rooted in fundamental specifications from FG ML5G (ITU Y.3172) and FG AN (ITU Y.3061). It has enabled contributions to ITU Journal for Future and Evolving Technologies, ML5G Challenges, and the Discovery webinar series, promoting research and real-world AI applications in telecom.

    Several ITU ML5G initiatives such as AI/ML Challenges and Zindi-hosted competitions further demonstrated the importance of regional inclusivity, diverse datasets, and research collaborations around AI/ML in networks. Resolution 101 of WTSA-24 (New Delhi, 2024) mentioned standardization in AI-enabled networks, protocols, services, and applications. The ITU AI Readiness Initiative continues to explore AI integration challenges in SDGs, while Innovate for Impact programs foster global collaborations on use cases, datasets, and proof-of-concepts for AI-driven networks.

    This year’s MLComm workshop focuses on AI-native innovations, standardization efforts, architectural shifts, and cutting-edge toolsets for AI-driven telecom networks.

    The workshop is structured as four Key Sessions:

    Session 1: Innovations in AI models – Examining breakthroughs in reasoning models, inference optimization, agentic workflows, and generative AI.
    Session 2: Standards and Open Source – Understanding the evolving role of SDOs and research partners in AI-native telecom standardization.
    Session 3: Architecture Impacts – Exploring AI-driven transformations in RAN, core, and edge, including federated learning, Open RAN, semantic communications, and autonomous networks.
    Session 4: Tools, Simulators, and Datasets – Highlighting AI-enabled network simulators, digital twins, dataset repositories, and validation frameworks from partners.

    This workshop aims to strengthen the bridge between AI research, industry innovation, and global standardization, ensuring that AI technologies in telecom meet real-world needs while driving next-generation network advancements.

  • Share this session
    • 93
      Days
      11
      Hours
      31
      Min
      29
      Sec