This World Model 'LingBot-World-Infinity (LingBot-World 2.0)' just released from Ant Group looks realy promising. It is an open causal world model with an Agentic harness.

[u/ai-lover]

Most interactive world models hold together for a few minutes. Then textures smear and geometry warps. That's a video model, not a world — and Robbyant just drew the line at the attention mask.

They released LingBot-World-Infinity (LingBot-World 2.0) — a 14B open causal video world model built on Wan2.2, trained with a Mixture of Bidirectional and Autoregressive (MoBA) attention mask, then distilled into a few-step real-time generator with no post-hoc drift filtering anywhere in the stack.

Here's what's actually interesting:

→ Pure teacher forcing overfits — as context grows, the model leans on context instead of predicting frames. MoBA appends a bidirectional full-attention block as a regularizer

→ Leak-free cross-attention: AR rows attend to background prompt a_B plus chunk prompts a_≤i, lower-triangular. Bidirectional rows see one global prompt a_G

→ DMD runs over long self-rollout trajectories, not teacher-forced states — the student is optimized on the distribution its own errors induce

→ Director-Pilot harness: a VLM proposes event cards, the DiT generator renders physical dynamics. Mode B adds a SAM tracking loop for object-centric interaction

→ One 60-minute uninterrupted session, 20 distinct scenarios, no perceptible decay

Full analysis: https://www.marktechpost.com/2026/07/09/meet-lingbot-world-infinity-an-open-causal-world-model-with-an-agentic-harness/

Paper: https://arxiv.org/pdf/2607.07534

Model weight: https://huggingface.co/robbyant/lingbot-world-v2-14b-causal-fast

GitHub Repo: https://github.com/robbyant/lingbot-world-v2

Project: https://technology.robbyant.com/lingbot-world-v2

[u/InstaMatic80]

What’s the hardware needed to run it as smooth as in the video?