NAVER LABS Europe seminar: Towards embodied intelligence

NAVER LABS Europe (Grenoble, France) is the biggest industrial AI research lab in France with fundamental and applied research in the fields of machine learning and optimization, computer vision, natural language processing and human robot interaction. The main area of application  is  AI for Robotics where they work closely with  NAVER LABS Korea the R&D subsidiary of NAVER, Korea’s leading internet company. NAVER LABS is responsible for creating future technology in robotics, AI, autonomous driving, 3D/HD mapping and AR.LinkedIn-Bluesky

NAVER LABS Europe

Seminar: Towards embodied intelligence. Speaker: Roberto Calandra

About the speaker: Roberto Calandra is a Research Scientist at Facebook AI Research. Previously, he was a Postdoctoral Scholar at the University of California, Berkeley (US) in the Berkeley Artificial Intelligence Research Laboratory (BAIR). His education includes a Ph.D. from TU Darmstadt (Germany), a M.Sc. in Machine Learning and Data Mining from the Aalto university (Finland), and a B.Sc. in Computer Science from the Università degli studi di Palermo (Italy). His scientific interests are broadly at the conjunction of Decision-making, Robotics and Machine Learning. Research topics that he is currently developing include Model-based Reinforcement Learning, Tactile Sensing, Morphology Adaptation, and Bayesian Optimization. He has also been Program Chair for AISTATS 2020, Guest Editor for the JMLR special issue on Bayesian Optimization, and co-organized over a dozen workshops at international conferences (Neurips, ICML, ICLR, RSS, etc).*******************************Abstract: The creation of intelligent embodied artificial agents has long been a dream for roboticists and artificial intelligence researchers alike. In this talk, I will argue for several key advances that I believe are necessary before we can achieve this dream. Specifically, I will present our contributions to two of these key research areas: multi-modal sensing, and data-efficient learning for fast adaptation. Regarding multi-modal sensing, I will discuss the importance of using alternative sensor modalities in addition to vision and will present our recent research on using touch sensing to allow robots to perceive, understand, and interact with the world around them. On the topic of data-efficient learning, I will discuss the use of model-based reinforcement learning -- which explicitly creates explainable models of the world -- and present some of our recent works to understand and overcome the limitations of current approaches.*******************************We will share Zoom connect details with registered attendees just before the seminar.

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NAVER LABS Europe seminar: Towards embodied intelligence

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