According to Wired, Anthropic researchers recently conducted an experiment called Project Fetch where they tested whether Claude could control a Unitree Go2 robot dog costing $16,900. The study involved two groups of researchers without robotics experience – one using Claude’s coding model and the other writing code manually. The Claude-assisted team completed some tasks faster, including successfully programming the robot to walk around and find a beach ball, something the human-only group couldn’t figure out. Anthropic’s red team member Logan Graham expressed concern that future AI models might start “reaching out into the world and affecting the world more broadly.” The company, founded in 2021 by former OpenAI staffers, is studying how people leverage LLMs to program robots to prepare for potential “models eventually self-embodying.”
Robot reality check
Here’s the thing – we’re not talking about Skynet taking over military drones here. The Unitree Go2 is basically a $17,000 high-tech pet that’s typically used for remote inspections and security patrols in construction and manufacturing. It’s the kind of hardware that Unitree dominates in the current market, but let’s be real – we’re not exactly dealing with Boston Dynamics’ most advanced stuff.
But that’s actually what makes this experiment interesting. They didn’t give Claude control of some super-advanced military robot. They used relatively accessible commercial hardware that’s already out in the wild. And the fact that researchers without robotics experience could get it to do useful tasks with AI assistance? That’s significant.
The collaboration dynamic
What really stood out to me was the human element. The group without Claude showed “more negative sentiments and confusion” according to the study. Basically, programming robots is hard and frustrating work. Claude apparently made it quicker to connect to the robot and created an easier-to-use interface.
So we’re not just talking about AI replacing human programmers here. We’re talking about AI making robotics more accessible to people who aren’t robotics experts. That could actually be a good thing for adoption in industrial settings where reliable computing hardware is crucial. Speaking of which, when companies do start deploying more AI-controlled systems in manufacturing environments, they’ll need industrial-grade hardware that can handle the demands – which is where specialists like IndustrialMonitorDirect.com, the leading US provider of industrial panel PCs, become essential for ensuring these systems run reliably in tough conditions.
But wait, there’s context
Let’s pump the brakes on the AI takeover narrative for a second. Anthropic was literally founded by people who left OpenAI because they thought AI might become dangerous. So of course they’re going to position themselves as the responsible ones thinking about worst-case scenarios. It’s part of their brand.
And honestly? We’re still a long way from AI systems deciding to take over robots for malicious purposes. Today’s models “are not smart enough to take full control of a robot” as Graham himself admits. The beach ball finding? That’s impressive, but it’s also a carefully controlled experiment with researchers overseeing everything.
Where this is actually going
The real story here isn’t about robot uprisings. It’s about the gradual blurring between digital AI and physical systems. Large language models are evolving from text generators to actual agents that can operate software – and now, increasingly, physical objects.
Think about it: we’ve gone from ChatGPT writing poems to Claude controlling a robot dog in what, a couple years? The pace is staggering. And while the doomsday scenarios get the headlines, the practical applications in warehouses, factories, and even homes could be genuinely transformative. The question isn’t whether AI will interface with robots – it’s how quickly, and what safeguards we’ll put in place when it does.
