Gemini Robotics 2 Brings Google's AI Into the Physical World

Google DeepMind just released a new version of its artificial intelligence model Gemini, and it can control a range of different robots—including humanoids capable of dextrous tasks like screwing in lightbulbs and tying trash bags.

Gemini Robotics 2 combines several different AI models into a single system. Taken together, they allow a robot to make sense of its surroundings and how to act in it. A vision language model (VLM), which understands images and video, can communicate with humans and reason how to perform different tasks. Two vision language action (VLA) models, trained to understand how to move in physical space, control the robot’s full-body movement as well as the movements of grippers or hands.

In video demonstrations shared ahead of the release, the company showed several different robots performing complex tasks autonomously using the amalgamated model. In one demo, Apptronik’s Apollo 2 robot used hands from a company called Sharpa to tidy shelves. Google DeepMind trained the model to perform these tasks using a mix of human teleoperation, video examples, and simulations—it’s not yet possible for AI models to perform a wide range of complex tasks without specific training.

Although Anthropic and OpenAI have taken a lead with chatbots and AI coding tools, Google has a stronger track record in robotics research, and has published important work on using AI to train robots to do useful things. The release is another sign that the search giant is betting AI will need to break free from the digital realm to realize its full potential. (It previously partnered with Boston Dynamics, a leader in legged robots, to provide the brains for those machines.)

“It’s another milestone in our path towards really getting towards what we call like physical AGI, which means we get a robot to do anything that a human can,” Carolina Parada, head of robotics at Google DeepMind, tells WIRED.

Giving frontier AI models access to robots so that they can wander around workplaces or homes and manipulate objects does, however, come with risks. Previous research has shown that using frontier AI to control robots can produce unexpected and sometimes dangerous behavior. And the idea that these models can take sudden or unwanted actions in the digital realm became apparent recently, when an unreleased AI agent developed by OpenAI hacked several systems.

“The safety question is even more pressing because you’re putting them in a lot of other situations,” Parada says. “There’s a lot of uncertainty that will show up, and so you want to be able to understand the safety question more deeply.”

Parada says Google takes a multi-layered approach to safety, with guardrails applied on each model layer. It’s also introducing ASIMOV-Agentic, a new benchmark for measuring the safety of various AI systems collaborating to control a robot. The benchmark detects whether a command will result in harmful or uncertain outcome.

The company’s CEO, Demis Hassabis, previously told WIRED that he hopes to develop an AI operating system for many different robots similar to the Android operating system for smartphones.