[rl-list] Safe RL Talk Invitation: The future of large embodied models

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Josip Josifovski

May 28, 2024, 4:07:51 PMMay 28
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Dear colleagues,


On Thursday (30.05.2024) we are hosting a talk in the scope of the Safe Reinforcement Learning Online Seminar. The details for the talk are given below. We invite you to join via zoom if you are interested and feel free to share this invitation with colleagues or students that might find the talk relevant.


Talk Title: The future of large embodied models

Speaker: Prof. Yang Gao (Tsinghua University)

Talk Time: 30.05.2024, 04:00 PM CEST Time (Amsterdam, Berlin, Rome, Stockholm, Vienna) / 07:00h California time / 22:00h Beijing time

Host: Shangding Gu


Join Zoom Meeting:


Meeting ID: 672 6957 6319

Passcode: 903926


Abstract: Embodied intelligence is one of the important milestones of artificial intelligence. In this talk, I will introduce several important data sources in the embodied intelligence large model, and how to train the embodied large model from these data. Specifically, it includes Internet video data, pre-trained vision language large models, imitation learning data and reinforcement learning data. I will introduce the following work: (1) General Flow, which learns world priors from human video data (2) ViLa and CoPa, that extract world priors from pre-trained large vision language models (3) Foundation RL, which employs large models to assist real world RL, to greatly improve the model success rate.


Bio: Yang Gao is an assistant professor at IIIS, Tsinghua University. Before that, he got his Ph.D. degree from UC Berkeley, advised by Prof. Trevor Darrell. He also spent a year at Berkeley for his postdoc, working with Trevor Darrell and Pieter Abbeel. He is mainly interested in computer vision and robotic learning. Before that, he graduated from the computer science department at Tsinghua University, where he worked with Prof. Jun Zhu on Bayesian inference. He has interned in Google Research on natural language processing from 2011 to 2012, with Dr. Edward Y. Chang and Dr. Fangtao Li and in Waymo autonomous driving team during the summer of 2016. He also worked on autonomous driving problems at Intel research during the summer of 2018, with Dr. Vladlen Koltun.


Safe RL Online Seminar Homepage: https://sites.google.com/view/saferl-seminar/home, We welcome the researchers and students who are interested in safe RL to join us! To receive relevant seminar information in time, please click the link to register.


Best regards,

Josip on behalf of the Safe Reinforcement Learning Online Seminar organizers


Josip Josifovski


Technical University of Munich (TUM)

School of Computation, Information and Technology

Chair of Robotics, Artificial Intelligence and Real-time Systems (I6)

Schleißheimer Str. 90A, 85748

Garching bei München


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