April 22, 2024, 11:37 p.m. | Allen Institute for AI

Allen Institute for AI www.youtube.com

Abstract: True gains of machine learning in AI sub-fields such as computer vision and natural language processing have come about from the use of large-scale diverse datasets for learning. In this talk, I will discuss how we can leverage large-scale diverse data in the form of egocentric videos (first-person videos of humans conducting different tasks) to similarly scale up policy learning for robots. A central challenge is the gap in embodiment and intentions. I will describe how we can leverage …

abstract and natural language processing computer computer vision data datasets discuss diverse fields form humans language language processing machine machine learning natural natural language natural language processing person processing robot scale talk true understanding videos vision will

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Lead Data Modeler

@ Sherwin-Williams | Cleveland, OH, United States