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.