Postdoctoral Researcher, Carnegie Mellon University, Fundamental AI Research (FAIR) at Meta
- Date & time
- Monday, April 8, 2024 · 11:00 AM
- Location
- Donald Bren Hall 4011
Abstract
AI has revolutionized the way we interact online. Despite this, it hasn't quite made the leap when it comes to tasks like cooking dinner or cleaning our desks. Why has AI excelled in automating our digital interactions but not in assisting us with physical tasks? In my talk, I will explore the challenges of applying AI to embodied tasks — those requiring physical interaction with the environment. To address these challenges, I turn to the efficient pathways humans use to achieve embodied intelligence and propose three strategies to jump-start the learning process for embodied AI agents: (1) combining learning from both teachers and own experience, (2) leveraging external information or hints to simplify learning, such as using maps to learn about physical spaces, and (3) learning intelligent behaviors by simply observing others.
About the speaker
Unnat Jain is a postdoctoral researcher at Carnegie Mellon University and Fundamental AI Research (FAIR) at Meta, where he works with Abhinav Gupta, Deepak Pathak, and Xinlei Chen. He received his PhD in Computer Science from UIUC, working with Alexander Schwing and Svetlana Lazebnik and collaborating with Google DeepMind and Allen Institute for AI. His research focuses on embodied intelligence, bridging computer vision (perception) and robot learning (action). Unnat's achievements have been recognized with several awards, including the Mavis Future Faculty Fellowship, Director's Gold Medal at IIT Kanpur, Siebel Scholars, and two best thesis awards.