Claude Opus 4.7 20倍速编程机器狗，但抓球仍失败

Anthropic just showed Claude Opus 4.7 program a robodog in 12:07 mint, about 20x faster than last year’s Claude-aided human team on the tested tasks.

Project Fetch asks whether an LLM can connect real robot hardware, read camera/lidar feeds, write movement code, track location, and detect a ball.

Opus 4.7 did 5 tasks alone versus Team Claude’s 264 minutes, while writing 1,045 lines instead of 10,309.

The gain came from choosing the right interfaces quickly and writing scripts that worked without long human trial-and-error.

It still couldn’t fetch the ball. The failure came from closed-loop control, where the robot must see a drifting ball and adjust movement after each shove.

AI is getting very good at turning messy hardware into working code, but real-time physical judgment is still hard.