多代理系统中消除代理冗余工作的进展

The hard part of multi-agent systems is getting agents to stay quiet. Put five agents on one task, and they duplicate work and burn tokens talking to each other. Offloop trained a dispatcher model called D1 that decides which agent moves next and when the right move is to do nothing. They achieve state-of-the-art performance on GDPval at a fraction of the usual cost. You can bring your own AI subscription. https://t.co/Q4wgI9mbM7 https://video.twimg.com/amplify_video/2080340650701008897/vid/avc1/1446x1080/AAYdTcFQCcpLkYmw.mp4?tag=29 > **引用原帖 Offloop (@Offloop):** > Introducing Offloop! > We're a team of four. Today our multi-agent harness hit state of the art on GDPval, ahead of Claude code and Codex across jobs that pay $2.4 trillion a year in the US. > Offloop gives every knowledge worker what the Fortune 500 spends billions on: a high-performing agent army that runs itself and grows the business. > https://x.com/Offloop/status/2080309689670361172