ITU AI/ML in 5G Grand Challenge Finale

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ITU AI/ML in 5G Grand Challenge Finale

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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. ​ ​

    Cash Prizes: The ITU AI/ML in 5G Challenge has set up prize pools of different sizes to reward outstanding teams totalling to around 20,000 CHF.

    Welcome remarks by TSB Dir. Chaesub Lee, Director, Telecommunication Standardization Bureau, ITU

    Congratulatory remarks by Jihyum Eum, Director, Multilateral Cooperation Division, Ministry of Science and ICT, Republic of Korea

    ITU AI/ML in 5G Challenge - 2021 Highlights Thomas Basikolo, ITU

    Overview of the solutions from the Challenge from representative Teams 

    In this talk we’ll show a number of exciting opportunities for Machine Learning in the implementation of Communication infrastructure. This can include Machine Learning based modulation detection and machine learning based Digital Pre-Distortion. In general many control and feedback loops are a candidate for novel Machine Learning applications. We’ll show a few architectures that can efficiently implement the high-rate, low latency requirements that the communication application demands.

    Closing remarks by TSB Dir. Chaesub Lee, Director, Telecommunication Standardization Bureau, ITU

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