Edge AI networks - Ian F. Akyildiz Challenges and opportunities - ITU Journal 2022

Edge AI networks - Ian F. Akyildiz Challenges and opportunities - ITU Journal 2022
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In this webinar, we discuss the challenges and opportunities offered by edge AI networks. Fueled by the availability of more data and computing power, recent breakthroughs in cloud-based machine learning (ML) have transformed every aspect of our lives from face recognition and medical diagnosis to natural language processing. However, classical ML exerts severe demands in terms of energy, memory, and computing resources, limiting their adoption for resource-constrained edge devices. The new breed of intelligent devices and high-stake applications (drones, augmented/virtual reality, autonomous systems, etc.), requires a novel paradigm change calling for distributed, low-latency, and reliable ML at the wireless network edge (referred to as edge ML).
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Speakers 🎙
Mérouane Debbah, Chief Researcher, AI and Telecommunication Systems, Technology Innovation Institute (TII)
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Moderators 🎙
Ian F. Akyildiz, Editor-in-Chief, ITU Journal on Future and Evolving Technologies (ITU-J FET)
Alessia Magliarditi, ITU Journal and ITU-T Academia Coordinator, International Telecommunication Union (ITU)
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This Webinar is organized by the ITU Journal on Future and Evolving Technologies (ITU J-FET) an international journal providing complete coverage of all communications and networking paradigms, free of charge for both readers and authors. The ITU Journal considers yet-to-be-published papers addressing fundamental and applied research. Open topics for future research will be discussed.
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