ITU AI/ML in 5G Challenge: Graph Neural Networking Challenge 2020

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ITU AI/ML in 5G Challenge: Graph Neural Networking Challenge 2020

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  • Artificial Intelligence (AI) will be the dominant technology of the future and will impact every corner of society. In particular, AI / ML (machine learning) will shape how communication networks, a lifeline of our society, will be run. Many companies in the ICT sector are exploring how to make best use of AI/ML. ITU has been at the forefront of this endeavour exploring how to best apply AI/ML in future networks including 5G networks. The time is therefore right to bring together the technical community and stakeholders to brainstorm, innovate and solve relevant problems in 5G using AI/ML. Building on its standards work, ITU is conducting a global ITU AI/ML 5G Challenge on the theme “How to apply ITU’s ML architecture in 5G networks”.

    Participants will be able to solve real world problems, based on standardized technologies developed for ML in 5G networks. Teams will be required to enable, create, train and deploy ML models (such that participants will acquire hands-on experience in AI/ML in areas relevant to 5G). Participation is open to ITU Member States, Sector Members, Associates and Aca​demic Institutions and to any individual from a country that is a member of ITU. ​ ​

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    More information here

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      Speaker abstract

      Forging the Networks of Tomorrow: Leveraging Deep Learning for Mobile Network planning and operation - The networking community is actively engaged in the search for the key technologies that will drive the success of 6G networks. In this exciting landscape, Deep Learning can be a game-changer in propelling such a revolution, especially for processing the vast amounts of data collected in networks, uncovering intricate patterns in that data, and making complex decisions in real time. This talk will present some opportunities and ongoing efforts to apply Deep Learning for planning and operation in mobile networks. We will introduce some use cases where we leverage Deep Learning for achieving unprecedented levels of connectivity and user experience. Next, we will discuss some key open challenges to achieve mature Deep Learning solutions for networks, with a particular focus on energy efficiency. Finally, we will outline some future research directions that may help materialize Deep Learning-based solutions for the Mobile Networks of Tomorrow.
      José Suárez-Varela
      Telefonica Research
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