Robbyant, the embodied AI unit inside Ant Group, has released the LingBot-VA 2.0.The first embodied-native foundation model. It describes a video-action foundation model for generalist robot manipulation. The research team pretrains the whole stack for embodiment instead of fine-tuning a video generator.
What is LingBot-VA 2.0?
Most video-action models reuse two components built for digital content creation. One is a reconstruction-oriented VAE. The other is a bidirectional video-diffusion backbone, with an action module attached.
This creates three limitations. Pixel-reconstruction latents preserve appearance but carry limited physical structure. Iterative denoising over video tokens is too slow for closed-loop control. Generic video objectives never teach how actions reshape the world.
A fourth mismatch is structural. Backbones use bidirectional attention, while control unfolds strictly forward in time. LingBot VA Version 1.0 finetuned that stack into a causal model. Version 2.0 pretrains a causal DiT natively.
