Robbyant, Ant Group’s embodied-intelligence unit, has released LingBot-World-Infinity (LingBot-World 2.0). It is a causal video generation model that behaves as an interactive world simulator. It is how the team attacks two failure modes: long-horizon drift and interactive latency.
An interactive world model generates video frame by frame, conditioned on a stream of user actions. Each state depends only on past frames and current input. The research team formalizes this as a causal factorization:
p_θ(x_1:T | a_1:T) = Π_t p_θ(x_t | x_<t, a_≤t)
Here x_t is the visual state at time t. The action a_t combines a camera pose and a text prompt. Camera pose uses Plücker embeddings, injected through adaptive layer normalization (AdaLN). Text enters as chunk-wise prompts through cross-attention.
The research team claims four upgrades over LingBot-World:
