Fique off-line com o app Player FM !
Decoding Animal Behavior to Train Robots with EgoPet with Amir Bar - #692
Manage episode 428029018 series 2355587
Today, we're joined by Amir Bar, a PhD candidate at Tel Aviv University and UC Berkeley to discuss his research on visual-based learning, including his recent paper, “EgoPet: Egomotion and Interaction Data from an Animal’s Perspective.” Amir shares his research projects focused on self-supervised object detection and analogy reasoning for general computer vision tasks. We also discuss the current limitations of caption-based datasets in model training, the ‘learning problem’ in robotics, and the gap between the capabilities of animals and AI systems. Amir introduces ‘EgoPet,’ a dataset and benchmark tasks which allow motion and interaction data from an animal's perspective to be incorporated into machine learning models for robotic planning and proprioception. We explore the dataset collection process, comparisons with existing datasets and benchmark tasks, the findings on the model performance trained on EgoPet, and the potential of directly training robot policies that mimic animal behavior.
The complete show notes for this episode can be found at https://twimlai.com/go/692.
713 episódios
Decoding Animal Behavior to Train Robots with EgoPet with Amir Bar - #692
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Manage episode 428029018 series 2355587
Today, we're joined by Amir Bar, a PhD candidate at Tel Aviv University and UC Berkeley to discuss his research on visual-based learning, including his recent paper, “EgoPet: Egomotion and Interaction Data from an Animal’s Perspective.” Amir shares his research projects focused on self-supervised object detection and analogy reasoning for general computer vision tasks. We also discuss the current limitations of caption-based datasets in model training, the ‘learning problem’ in robotics, and the gap between the capabilities of animals and AI systems. Amir introduces ‘EgoPet,’ a dataset and benchmark tasks which allow motion and interaction data from an animal's perspective to be incorporated into machine learning models for robotic planning and proprioception. We explore the dataset collection process, comparisons with existing datasets and benchmark tasks, the findings on the model performance trained on EgoPet, and the potential of directly training robot policies that mimic animal behavior.
The complete show notes for this episode can be found at https://twimlai.com/go/692.
713 episódios
Toate episoadele
×Bem vindo ao Player FM!
O Player FM procura na web por podcasts de alta qualidade para você curtir agora mesmo. É o melhor app de podcast e funciona no Android, iPhone e web. Inscreva-se para sincronizar as assinaturas entre os dispositivos.