Google DeepMind has done it. They’ve taken their most advanced large language model, Gemini, and plugged it into robots. The result? A machine that can slam-dunk a miniature basketball without ever watching another robot do it. This isn’t just party trick territory—it’s a glimpse into a future where machines don’t just obey commands, but figure things out on their own.
The idea is bold: take the AI that powers chatbots and give it control over physical bodies. No pre-programming, no micromanagement—just raw artificial intelligence figuring out how to exist in the real world. Of course, this also opens doors to potential chaos. If AI chatbots can hallucinate nonsense responses, what happens when the same tech controls machines? A robot confidently “guessing” at reality sounds like a sci-fi disaster waiting to happen.
Carolina Parada, head of DeepMind’s robotics team, sees this differently. She envisions robots that understand both language and the physical world with unprecedented depth. A developer could simply link their machine to Gemini Robotics and suddenly have a bot that comprehends natural language *and* spatial reasoning—like giving a Roomba the brain of a seasoned engineer.
The system, dubbed Gemini Robotics, was announced on March 12 alongside a technical paper detailing its capabilities. Alexander Khazatsky, an AI researcher and co-founder of CollectedAI, calls it “a small but tangible step” toward general-purpose robots. Small step or not, it’s already outmaneuvering other AI-powered bots in real-world tasks.
Spatial Awareness—Or How to Stop Walking into Walls
Gemini Robotics started with Gemini 2.0, DeepMind’s most sophisticated vision and language model, trained on absurdly vast amounts of data. Then, they gave it an upgrade—specialized intelligence for processing 3D space. This means it can predict how objects move, recognize the same thing from different angles, and presumably avoid walking into glass doors like humans sometimes do.
To top it off, they fed the system thousands of hours of actual robot demonstrations. Instead of just simulating behavior, Gemini Robotics learned by watching real mechanical limbs perform tasks. The result? A robotic “brain” that applies logic to the physical world much like language models predict the next word in a sentence. Except, instead of stringing together words, it’s stringing together actions.
The Testing Grounds
DeepMind threw this AI into humanoid robots and robotic arms, testing it on both familiar and totally new tasks. Verdict: it didn’t just succeed; it crushed the competition. Robots running Gemini Robotics consistently outperformed existing AI-powered machines, even when details of tasks were altered to mess with their programming.
So what does this mean for the future? Picture robots that aren’t just programmed to vacuum floors or assemble car parts—but ones that can *learn* new skills on command. Today, it’s a miniature basketball dunk. Tomorrow? Maybe it’s cooking a meal, assisting in surgeries, or constructing buildings.
Of course, this all hinges on whether they stay cooperative. Because if human history has taught anything, it’s that intelligence—especially artificial—rarely stays satisfied with just playing *by the rules*.
Did You Know?
- Basketball-playing robots already exist in the NBA—Toyota built one that can shoot free throws with terrifying accuracy.
- The first robot to ever “see” was created in the 1950s at MIT. It could recognize simple shapes… which is cute compared to today’s AI overlords.
- One of the earliest autonomous robotic arms was called “Unimate”—and it worked on a General Motors assembly line in 1961, because apparently, robots have been taking jobs for *decades*.
