MIT researchers develop framework that enables robots to learn tasks from large language models.
Copyright: aibusiness.com – “MIT Researchers Use Large Language Models to Give Robots Common Sense”
MIT researchers have developed a framework that uses large language models to provide robots with common sense.
Engineers from MIT’s Computer Science & AI Laboratory (CSAIL) developed the Grounding Language in DEmonstrations (Glide) framework which enables information generated by large language models to be used as a foundation for robotic manipulation tasks providing them with a basic understanding and how to interact with it.
Traditionally, a human programmer would manually label and assign actions for a robot to perform or skills are taught via human demonstrations.
The Glide framework automates this process. A human prompts a large language model to turn high-level instructions “into a step-by-step abstract plan in language.”
The model’s basic blueprint outlines important details about what’s happening in a scene, like specific locations or important features. This helps the robot make sense of its surroundings.
The model then links these understandings to the robot’s abilities, outlining both successful ways to do tasks and potential mistakes to avoid.
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The information gives the robot the necessary information and context to understand the limitations and requirements involved in completing a task.[…]
Read more: www.aibusiness.com
MIT researchers develop framework that enables robots to learn tasks from large language models.
Copyright: aibusiness.com – “MIT Researchers Use Large Language Models to Give Robots Common Sense”
Engineers from MIT’s Computer Science & AI Laboratory (CSAIL) developed the Grounding Language in DEmonstrations (Glide) framework which enables information generated by large language models to be used as a foundation for robotic manipulation tasks providing them with a basic understanding and how to interact with it.
Traditionally, a human programmer would manually label and assign actions for a robot to perform or skills are taught via human demonstrations.
The Glide framework automates this process. A human prompts a large language model to turn high-level instructions “into a step-by-step abstract plan in language.”
The model’s basic blueprint outlines important details about what’s happening in a scene, like specific locations or important features. This helps the robot make sense of its surroundings.
The model then links these understandings to the robot’s abilities, outlining both successful ways to do tasks and potential mistakes to avoid.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
The information gives the robot the necessary information and context to understand the limitations and requirements involved in completing a task.[…]
Read more: www.aibusiness.com
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