Google 发布 Gemini Robotics 2.0，承诺提升机器人灵巧性与安全性

由 Google Gemini AI 模型驱动的机器人如今能力更强。随着 Gemini Robotics 2 发布，这些实体机器人现在能够完成更复杂的任务、持续分析不断变化的环境，并与其他机器人协作。这得益于三个全新的子模型，其中一个自今日起已向开发者公开提供。

多年来，机器人奔跑、跳舞和后空翻的视频一直是互联网的常见内容，但这些机器原本是为执行这些非常狭窄的任务而编程的。Gemini Robotics 的目标是打造通用机器人，即能够完成任何人类可以完成任务的机器人。Google DeepMind 的科学家有时将其称为“物理 AGI”（physical AGI）。本质上，你告诉机器人该做什么，它就会执行。Google 表示，借助 2.0 版本，其机器人 AI 能以更高的灵巧性控制整台人形机器人，甚至可应对配备复杂人形手部的机器。

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Gemini Robotics 2 为机器人带来全身智能。

这一能力始于 Gemini Robotics ER 2。这是一款升级后的“具身推理”（embodied reasoning）模型，DeepMind 声称它相较于此前的 1.6 版本实现了显著飞跃。该模型已集成 Gemini Live API，让开发者有机会亲身体验这一所谓的进步。

Gemini Robotics ER 2 属于视觉语言模型（VLM）。其设计目标是理解指令以及周围世界。此次升级的关键在于，ER 2 可以处理来自机器人摄像头的实时视频流，使系统能够在机器人从一个步骤缓慢推进到下一个步骤时跟踪任务进展。Google 指出，Gemini Robotics ER 2 对视频帧完成度进行分类的准确率接近 60%。这距离完美仍有很大差距，但已显著优于 1.6 版本，以及竞争性 AI 模型视觉理解能力所能达到的水平。

Robots powered by Google’s Gemini AI models are now more capable. With the debut of Gemini Robotics 2, these physical bots can now accomplish more complex tasks, continuously analyze changing environments, and collaborate with other robots. This is thanks to a trio of new sub-models, one of which is publicly available for developers starting today.

Videos of robots running, dancing, and backflipping have been a staple of the Internet for years, but these machines were programmed to perform these very narrow tasks. The goal of Gemini robotics is to create a generalist robot, one that can do anything a human could do. Google DeepMind scientists sometimes call this “physical AGI.” Essentially, you tell a robot what to do, and it does it. With the 2.0 release, Google says its robotics AI can control an entire humanoid robot with improved dexterity, even for machines with complex humanoid hands.

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Gemini Robotics 2 brings whole-body intelligence to robots.

This starts with Gemini Robotics ER 2, an upgraded “embodied reasoning” model that DeepMind claims is a significant leap over the previous 1.6 release. It’s integrated with the Gemini Live API, giving developers the opportunity to experience that supposed leap forward.

Gemini Robotics ER 2 is what’s known as a vision language model (VLM). It’s designed to understand instructions and the world around it. The big upgrade here is that ER 2 can process live video feeds from the robot’s cameras, allowing the system to track progress as the robot lumbers from one step to the next. Google notes that Gemini Robotics ER 2 can classify video frame completeness with almost 60 percent accuracy. That’s still far from perfect, but it’s much better than the 1.6 release or what you can get with the visual understanding of competing AI models.