This AI's Secret Two-Step Method is Creating Smarter, More Adaptable Robots скачать в хорошем качестве

This AI's Secret Two-Step Method is Creating Smarter, More Adaptable Robots

Have you ever dreamed of a robot that could understand complex, everyday instructions and just get the job done? That future might be closer than you think. Researchers have developed a new framework called InternVLA-M1 that teaches robots to think more like we do, leading to some incredible performance boosts. In this video, we'll break down the secret behind InternVLA-M1: a clever two-step training process. Instead of trying to learn everything at once, the AI first masters the skill of understanding 'where' to act by connecting language to specific locations in its vision. Only then does it learn 'how' to act, using that spatial knowledge to guide its physical movements. This simple but powerful idea is a game-changer for robot intelligence. We'll look at the amazing results, from outperforming previous models on standard benchmarks to successfully handling unseen objects, cluttered environments, and even receiving new instructions mid-task. Find out what this breakthrough in spatial reasoning means for the future of general-purpose robots that can work alongside us in our homes and workplaces. Cited paper: X. Chen et al. (2025). InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy. arXiv:2510.13778v1. http://arxiv.org/abs/2510.13778v1 Images shown are page renders from the paper PDF for commentary/education.