AI 精选动态
智能评分 65
Anthropic 展示 Claude Opus 4.7 编程机器狗，速度提升 20 倍
AI 推荐理由
差异点：Claude Opus 4.7 能将硬件接口转化为工作代码，但实时物理闭环仍是关键瓶颈。核心解读
Anthropic 在 Project Fetch 第二阶段中，让 Claude Opus 4.7 独立编程机器狗完成 5 项任务，耗时 12 分钟，比去年人类团队（264 分钟）快约 20 倍，代码行数从 10309 降至 1045，但因闭环控制失败未能抓取球。
全文
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.
https://video.twimg.com/amplify_video/2067652514313646080/vid/avc1/1280x720/Bp0DKrIBl0o4Dgen.mp4?tag=28
> **引用原帖 Anthropic (@AnthropicAI):**
> New Frontier Red Team blog: Phase 2 of Project Fetch, where we test how well Claude can program a robodog.
> Opus 4.7, on its own, was ~20x faster than last year's best human team aided by Opus 4.1. (The robodog, alas, still failed to fetch a beach ball.)
> https://t.co/CgbBtRf85e
> https://x.com/AnthropicAI/status/2067651699486200091