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Robotics Research Update, with Keerthana Gopalakrishnan and Ted Xiao of Google DeepMind
Apr 22, 2024
Keerthana Gopalakrishnan and Ted Xiao from Google DeepMind reveal cutting-edge advancements in AI robotics. They discuss breakthroughs enabling robots to learn from human demonstrations and handle novel objects. The duo dives into the debate on specialized versus generalist robots and emphasizes ethical considerations in robotic design. They shed light on the integration of internet-scale data in enhancing robotic learning and reflect on the challenges of training robots to navigate human environments safely and effectively.
01:24:15
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Quick takeaways
- Google DeepMind aims to train a generalist AI model across diverse robot embodiments through merging datasets from various labs.
- The RTX project focuses on training one model to control a wide range of robot embodiments, leading to better performance than specialist models.
Deep dives
Diverse Robot Morphologies Explored in RT2
RT2 project by Google DeepMind Robotics aimed to train a generalist AI model across diverse robot embodiments. It merged data sets from various labs presenting a range from baby toys to industrial arms. Despite initial limits, the model showcased diverse morphologies under common assumptions. By leveraging prior knowledge and internet-scale data, the model could demonstrate different behaviors based on varied prompts, pushing AI progress in robotics.
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