Stanford Seminar - Robot Learning in the Era of Large Pretrained Models скачать в хорошем качестве

Stanford Seminar - Robot Learning in the Era of Large Pretrained Models

February 23, 2024 Dorsa Sadigh, Stanford University In this talk, I will discuss how interactive robot learning can benefit from the rise of large pretrained models such as foundation models. I will introduce two perspectives. First I will discuss the role of pretraining when learning visual representations, and how language can guide learning grounded visual representations useful for downstream robotics tasks. I will then discuss the choice of datasets during pretraining. Specifically, how we could guide large scale data collection, and what constitutes high quality data for imitation learning. I will discuss some recent work around guiding data collection based on enabling compositional generalization of learned policies. Finally, I will end the talk by discussing a few creative ways of tapping into the rich context of large language models and vision-language models for robotics. About the speaker: https://dorsa.fyi/ More about the course can be found here: https://stanfordasl.github.io/robotic... View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist:    • Stanford AA289 - Robotics and Autonom...   ► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore