Adaptable Aviators: future of autonomous navigation Liquid networks | Ramin Hasani | TEDxMIT Salon

We delve into the realm of Liquid Neural Networks, an innovative approach to artificial intelligence inspired by the humble nematode C. elegans. Learn how these tiny, adaptable networks can understand the task they are given and navigate robustly complex environments when deployed on drones!

AI, Algorithm, Engineering, Finance, Imagination, Math, Robots Ramin Hasani is a Principal AI and Machine Learning Scientist at the Vanguard Group and a Research Affiliate at the Computer Science and Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology (MIT). Ramin’s research focuses on robust deep learning and decision-making in complex dynamical systems. Previously he was a Postdoctoral Associate at CSAIL MIT, leading research on modeling intelligence and sequential decision-making, with Prof. Daniela Rus. He received his Ph.D. degree with distinction in Computer Science at Vienna University of Technology (TU Wien), Austria (May 2020). His Ph.D. dissertation and continued research on Liquid Neural Networks got recognized internationally with numerous nominations and awards such as TÜV Austria Dissertation Award nomination in 2020, and HPC Innovation Excellence Award in 2022. He has also been a frequent TEDx Speaker. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx