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Imagine a world where robots don’t just respond to commands, but actually understand our language and intentions. In this exciting episode, we explore a revolutionary research paper titled "Do as I Can, Not as I Say" from the groundbreaking AI system, SEIKAN. Designed to bridge the gap between language comprehension and real-world action, SEIKAN combines advanced language models with robotics, allowing it to understand complex, human-like instructions and execute them within physical environments.
Our conversation reveals how SEIKAN’s “grounding” abilities transform it from a command-following machine into an intelligent assistant capable of reasoning and contextual awareness. With over 100 different tasks tested in a real-world kitchen environment, SEIKAN successfully navigated multi-step tasks—like choosing a healthy snack or cleaning a table—demonstrating an understanding that goes beyond literal instructions.
Key takeaways from this episode:
This research is a step towards a world where robots don’t just “do as told” but reason, plan, and collaborate alongside humans. Dive in with us as we discuss the possibilities, challenges, and implications of a future where robots understand us on a deeper level.
Original link:
https://arxiv.org/pdf/2204.01691
Imagine a world where robots don’t just respond to commands, but actually understand our language and intentions. In this exciting episode, we explore a revolutionary research paper titled "Do as I Can, Not as I Say" from the groundbreaking AI system, SEIKAN. Designed to bridge the gap between language comprehension and real-world action, SEIKAN combines advanced language models with robotics, allowing it to understand complex, human-like instructions and execute them within physical environments.
Our conversation reveals how SEIKAN’s “grounding” abilities transform it from a command-following machine into an intelligent assistant capable of reasoning and contextual awareness. With over 100 different tasks tested in a real-world kitchen environment, SEIKAN successfully navigated multi-step tasks—like choosing a healthy snack or cleaning a table—demonstrating an understanding that goes beyond literal instructions.
Key takeaways from this episode:
This research is a step towards a world where robots don’t just “do as told” but reason, plan, and collaborate alongside humans. Dive in with us as we discuss the possibilities, challenges, and implications of a future where robots understand us on a deeper level.
Original link:
https://arxiv.org/pdf/2204.01691