Biologically-Inspired IoT Systems for Federated Learning-Based HealthcareSpeaker: David Atienza – Lausanne, Switzerland
Topic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing , Hardware, Power and Energy
AbstractInternet of Things (IoT) is the next frontier of innovation where our everyday objects are connected in ways that improve our lives and can transform industries, in particular healthcare and wearables. In this keynote, Prof. Atienza will discuss new approaches to effectively co-design the next generation of edge AI computing systems by taking inspiration from how biological computing systems operate. This new trend of bioinspired system co-design approaches combines new open-source computing platforms that operate ensembles of neural networks to improve robustness of the outputs and minimizing memory and computation resources. Consequently, this advocated next generation of IoT systems benefit from critical biological concepts, such as in-memory computing or run-time reconfigurable coarse-grained accelerators, to enable a minimal energy consumption according to the required precision of the target application. Moreover, these new bioinspired systems can go one step beyond current biological systems. In particular, they can easily collaborate through federated learning to gradually help each other improve their outcomes in different real-life operating conditions.
About this LectureNumber of Slides: 32
Duration: 40 minutes
Languages Available: English
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