Image created with Gemini. Image prompt: A flat-scanned 1920s Dada Merz collage on aged board showing a globe assembled from torn nautical maps, weather tickers, train timetables, and ledger paper with visible fiber edges and glue buckling, surrounded by cut paper arrows and horizon strips in vermilion, kraft brown, slate blue and ink black, with the title ‘World Models’ spelled in mismatched letterpress cut-out letters glued at slight angles across the top layer, flat even lighting, subtle drop shadows, no digital rendering.
📣📣 Meet Qwen-AgentWorld — a native language world model that simulates 7 agent environments (MCP, Search, Terminal, SWE, Web, OS, Android) within a single model. Environment modeling is the training objective from day one, not a post-hoc adaptation. 🤔 LLMs are trained to be”
https://x.com/Alibaba_Qwen/status/2069720365442719867
We open-source Qwen-AgentWorld-35B-A3B (MoE, 35B/3B active, 256K context) and AgentWorldBench. Two routes, one roadmap: 🔬 Build the simulator — scalable, controllable, surpassing real environments 🧠 Internalize world modeling — predict before you act Qwen-AgentWorld is our”
https://x.com/Alibaba_Qwen/status/2069720412481888400
[2606.24597] Qwen-AgentWorld: Language World Models for General Agents
https://arxiv.org/abs/2606.24597
🧠 Paradigm II — Agent Foundation Model: world modeling as agent capability. Single-turn, non-agentic environment prediction → tested directly on multi-turn, tool-calling agent tasks. No agentic RL, no task-specific tuning. Gains across 7 benchmarks, including 3 entirely”
https://x.com/Alibaba_Qwen/status/2069720397747220493
Mondo is the most adorable companion robot. It’s safe around kids, can track and follow a person, and capture high-resolution action videos. Mondo is also doing frontier research in humanoid Video-Action models built on a world model backbone:
https://t.co/vuOIngXzVa. I have no”
https://x.com/TheHumanoidHub/status/2067409544574087632
Leave a Reply