Faculty Candidate Talk: Karl Pertsch

Newell-Simon Hall 4305

Talk Title:  Unlocking Scalable Robot Learning in the Real World Abstract:  Many domains of machine learning, from language modeling to computer vision, have recently undergone a shift towards generalist models, whose broad generalization abilities are fueled by large and diverse real-world training datasets and high-capacity model architectures. In robotics, however, it has been challenging to [...]