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Voyager

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Last updated: August 8, 2024

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What is Voyager?

Voyager: An Open-Ended Embodied Agent with Large Language Models is a collaborative research project involving contributors from NVIDIA, Caltech, UT Austin, Stanford, and ASU. The project aims to develop an AI agent that leverages large language models for open-ended tasks in various environments. The authors include Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi 'Jim' Fan, and Anima Anandkumar. The researchers have made significant contributions to the field of artificial intelligence and embodied agents.

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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

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Voyager's pricing

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    Use Cases

    AI Researchers

    Exploring the capabilities of large language models in diverse and open-ended tasks.

    Educational Institutions

    Incorporating advanced AI agents into curricula for hands-on learning.

    Tech Companies

    Utilizing adaptable AI for automation and intelligent assistance.

    Developers

    Building upon Voyager's framework for creating custom AI solutions.

    Robotics Engineers

    Implementing embodied agents for practical robotics applications.

    Product Managers

    Integrating AI-driven features into products for enhanced user experiences.

    Healthcare Professionals

    Leveraging AI for personalized and adaptive healthcare solutions.

    Public Sector Organizations

    Deploying intelligent systems for smart city initiatives.

    Data Scientists

    Applying large language models to analyze complex datasets.

    Academic Researchers

    Studying the impact and potential of AI in various fields and scenarios.