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Voyager

Discover Voyager, an AI agent using large language models for diverse tasks. Collaborative research by NVIDIA, Caltech, UT Austin, Stanford, and ASU.

Research Updated 44 seconds ago
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Voyager

Voyager's Top Features

Use of large language models
Adaptability to various tasks and environments
Collaborative development
Contributions to AI, machine learning, and embodied agents
Applications in diverse fields
Research from top institutions

Frequently asked questions about Voyager

Voyager is an open-ended embodied agent that leverages large language models for performing a variety of tasks in different environments.

The authors include Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi 'Jim' Fan, and Anima Anandkumar.

The institutions involved are NVIDIA, Caltech, UT Austin, Stanford, and ASU.

The goals are to develop an AI agent that can perform open-ended tasks using large language models across various environments.

Voyager uses large language models to understand and perform a wide range of tasks, adapting to different scenarios and environments.

Voyager contributes to the fields of artificial intelligence, machine learning, and embodied agents.

You can contact Guanzhi Wang at guanzhi@caltech.edu and Dr. Linxi 'Jim' Fan at dr.jimfan.ai@gmail.com.

Key features include the use of large language models, adaptability to various tasks and environments, and collaborative development by leading research institutions.

Voyager advances AI research by exploring the capabilities of large language models in open-ended and adaptable scenarios.

Potential applications include automated assistance in diverse fields, intelligent robotics, and adaptive learning systems.

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Category
Research
Tags
collaborative research
NVIDIA
Caltech
UT Austin
Stanford
ASU
AI agent
large language models
open-ended tasks
various environments

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