The Evolution of Learning to Learn

Chelsea Finn is an Assistant Professor at Stanford University, where she leads the IRIS lab that studies intelligence through robotic interaction at scale. Her PhD thesis is titled "Learning to Learn with Gradients", which she completed in 2018 at UC Berkeley. Chelsea received the prestigious ACM Doctoral Dissertation Award for her work in the thesis. We discuss machine learning for robotics, focusing on learning-to-learn - also known as meta-learning - and her work on the MAML algorithm during her PhD, as well as the future of robotics research. Episode notes: https://cs.nyu.edu/~welleck/episode10.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview