Gemini 3 Pro advances AI's ability to understand and reason with visual information, excelling in document processing, spatial awareness, screen interaction, and video analysis. It outperforms human benchmarks in complex tasks and offers solutions for education, medical imaging, and legal workflows.

UniVLA presents a novel approach to generalist policy planning using an embodiment-agnostic action space, achieving state-of-the-art results across various benchmarks with efficient training. It includes a comprehensive methodology for extracting latent actions from cross-embodiment videos and guidance on pre-training and fine-tuning models for real-world robot tasks.

GeometryCrafter is a novel framework that estimates high-fidelity and temporally coherent point maps from open-world videos, enhancing 3D/4D reconstruction and depth-based applications. It utilizes a point map Variational Autoencoder (VAE) to effectively encode and decode point maps, achieving state-of-the-art accuracy and temporal consistency across diverse environments. The approach addresses limitations in traditional video depth estimation methods, providing improved geometric fidelity for various tasks.