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LLM Embodiment in 3D Agent Interacting Within a Virtual World

· One min read

This project explores the embodiment of Large Language Models within a 3D virtual environment built in Unity, allowing for complex task simulation and interaction.

Key Achievements​

  • Developed an LLM agent embodiment framework that resulted in a 40% faster simulation of complex tasks.
  • Improved data exchange efficiency between Unity and Python by 25% using JSON-RPC.
  • Constructed a Chain of Thoughts-based ReAct agent, which increased task reasoning accuracy by 35%.

Technologies Used: Unity, Python, LangChain, PyTorch, Nvidia NIMS, JSON-RPC.