Exclusive Cryptalist: AI Claude Opus 4.7 destroyed humans in the race to control a robot dog — speed increased 20 times
The artificial intelligence market continues to rewrite the rules of the game. As part of the updated Project Fetch experiment, Anthropic's Claude Opus 4.7 model demonstrated a phenomenal result: it handled the setup and control of a robot dog 20 times faster than entire teams of human engineers. This is not just progress — it is a paradigm shift in robotics.
How AI Took Control
Back in August 2024, company employees with no experience in robotics tried to program a four-legged robot, and AI only helped them find solutions. In the new testing phase, Claude Opus 4.7 worked almost autonomously, under minimal researcher supervision. The neural network independently completed a full cycle of tasks:
- Connected to video sensors and LiDAR;
- Wrote a program for manual control;
- Created a robot path monitoring system;
- Configured an object recognition algorithm.
Impressive Numbers
The comparison with human teams is overwhelming. The Opus 4.7 model turned out to be 18 times faster than a team using older AI versions, and 37 times faster than people working without chatbot assistance. But the most important thing is code quality. The neural network wrote it 10 times more compactly than humans, which directly impacts efficiency and task execution speed.
Why This Matters for the Market
The key takeaway I draw as an analyst: progress in robotics turned out to be a side effect of the general scaling of language models. Anthropic did not introduce specialized algorithms for controlling hardware — this is a pure advantage of the basic architecture. However, one should not think that AI is already ready for the physical world. Claude still experiences serious difficulties with precise physical actions. The model managed to guide the robot to the target, but failed the task of gently pushing a ball to the right spot. This requires complex real-time feedback, where humans remain unmatched for now.
My Expert Perspective
We are entering the era of "physical AI agents," and this is not just hype. In the coming years, neural networks will begin using standard tools and equipment as effectively as they currently work with code. However, investors should remember: until AI learns fine motor skills, full automation of physical labor will remain a dream. Anthropic, by the way, recently suspended access to the Fable 5 and Mythos 5 models due to US export controls — a reminder that geopolitics can adjust the course of the most powerful AI at any moment.