In this video, I look at Qwen-AgentWorld, which is a world model built to simulate RL environments for agents to get better at training.

📑 Paper: https://arxiv.org/abs/2606.24597
📖 Blog: https://qwen.ai/blog?id=qwen-agentworld
💻 GitHub: https://github.com/QwenLM/Qwen-AgentWorld
🤗 HuggingFace: https://huggingface.co/collections/Qwen/qwen-agentworld

Twitter: https://x.com/Sam_Witteveen 

🕵️ Interested in building LLM Agents? Fill out the form below
Building LLM Agents Form: https://drp.li/dIMes

👨‍💻Github:
https://github.com/samwit/llm-tutorials

⏱️Time Stamps:
00:00 Intro
03:01 Qwen-AgentWorld Blog
03:14 Paper
03:23 Benchmarks
06:15 Before and After Language World Model RL Training
07:37 Qwen-AgentWorld Pipeline
10:58 Demo

Sam Witteveen AI is a publication offering insights, tutorials, and resources for artificial intelligence (AI) enthusiasts and practitioners. Readers can learn about machine learning algorithms, deep learning frameworks, and AI applications. With tutorials, case studies, and expert interviews, Sam Witteveen AI provides  guidance and expertise for building and deploying AI solutions.

Qwen-AgentWorld The World Model for RL Environments