Beyond VLA and World Models: Galaxy General Unveils LDA‑1B to Scale Embodied Data

LDA‑1B unifies world modeling and VLA in a latent dynamics action model, ingesting over 30 000 hours of heterogeneous embodied data via a five‑layer AstraData pipeline, employing a unified end‑effector space and quality‑based data allocation, and achieving state‑of‑the‑art success rates on RoboCasa‑GR1 while being fully open‑sourced.

Embodied AIScaling Lawdata ingestion

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Beyond VLA and World Models: Galaxy General Unveils LDA‑1B to Scale Embodied Data

Code Mala Tang

Apr 22, 2026 · Artificial Intelligence

How LeWorldModel Achieves Stable End‑to‑End World Modeling with Just Two Losses

LeWorldModel, a 2026 JEPA‑based world model introduced by Yann LeCun and collaborators, solves representation collapse with a minimalist two‑loss objective, delivering a 15‑million‑parameter system that trains in hours, runs 48× faster than prior baselines, and reaches near‑SOTA performance on robot control benchmarks.

Embodied AIJEPAWorld Model

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How LeWorldModel Achieves Stable End‑to‑End World Modeling with Just Two Losses

AIWalker

Mar 10, 2026 · Artificial Intelligence

MIGM-Shortcut: Learning Controlled Latent Dynamics to Speed Up Masked Image Generation

The paper introduces MIGM-Shortcut, a self‑supervised method that learns controlled latent‑state dynamics to bypass redundant bidirectional attention in Masked Image Generation Models, achieving over 4× speed‑up on state‑of‑the‑art multimodal diffusion models like Lumina‑DiMOO while preserving image quality.

AIMIGMdiffusion models

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MIGM-Shortcut: Learning Controlled Latent Dynamics to Speed Up Masked Image Generation