{"version":"1.0","type":"card","id":"12db32db-ff80-47c8-89fe-8b07d96afc85","url":"https://stacklist.com/card/12db32db-ff80-47c8-89fe-8b07d96afc85","title":"Multi-agents collaborations are among the most interesting agent behaviors right now!","source_url":"https://www.linkedin.com/posts/thom-wolf_multi-agents-collaborations-are-among-the-ugcPost-7475901816602476546-CFFA/?utm_source=share&utm_medium=member_ios&rcm=ACoAAAI21ZsBNnZPaKuTab7nquKLCveUW7o-1DE","note":"This page discusses an experiment involving over 100 agents collaborating to enhance the inference speed of Gemma 4 in vLLM. It highlights various interactions, self-policing measures, and emergent collaborations observed during the experiment, showcasing the innovative dynamics of multi-agent systems.","image":{"url":"https://ucarecdn.com/3ec25e61-917f-4281-9270-910f5f086a6f/","alt":"Multi-agents collaborations are among the most interesting agent behaviors right now!","width":400,"height":400},"stack":{"id":"614ecd6d-12cd-4195-bf9c-3def755c89b2","title":"AI Inbox","url":"https://stacklist.com/stack/614ecd6d-12cd-4195-bf9c-3def755c89b2"},"created_at":"2026-06-26T02:33:58.312Z","updated_at":null,"aco":{"summary":"Multi-agent collaborations achieved a 5x improvement in Gemma 4 inference speed through 100+ agents working together in vLLM, demonstrating emergent governance, self-policing behaviors, and sophisticated knowledge-sharing practices. The experiment revealed agents spontaneously establishing communication norms, flagging verification loopholes, and organizing into specialized divisions of labor while maintaining communal knowledge bases and playbooks.","tags":["multi-agent-collaboration","emergent-governance","inference-optimization","gemma-4","vlm","self-policing","knowledge-sharing"],"key_entities":[{"name":"Thomas Wolf","type":"person","confidence":0.95},{"name":"FusionCow","type":"person","confidence":0.85},{"name":"Gemma 4","type":"technology","confidence":0.95},{"name":"vLLM","type":"technology","confidence":0.95},{"name":"Marlin","type":"technology","confidence":0.8},{"name":"MTP speculative decoding","type":"technology","confidence":0.85},{"name":"Modal","type":"technology","confidence":0.75},{"name":"HuggingFace","type":"organization","confidence":0.9},{"name":"emergent-governance","type":"concept","confidence":0.9},{"name":"self-policing","type":"concept","confidence":0.9},{"name":"division-of-labor","type":"concept","confidence":0.85},{"name":"multi-agent collaboration experiment","type":"event","confidence":0.9}],"classification":"analysis","language":"en","confidence":0.85,"provenance":{"model":"claude-haiku-4-5","tool":"@stacklist/be@0.1.0","confidence":0.85,"timestamp":"2026-06-26T02:34:09.743Z"},"token_counts":{"approximate":1293,"cl100k":1178},"content_hash":"sha256:5270aacd9864a9688e7968239d5ff8830194fbc345d908948eaa77d603aa6bc7","acp_version":"0.2","body_available":true,"body_tokens":1293,"visibility":"public","agent_accessible":true,"status":"final"},"_links":{"self":"/api/public/card/12db32db-ff80-47c8-89fe-8b07d96afc85.json","html":"https://stacklist.com/card/12db32db-ff80-47c8-89fe-8b07d96afc85","md":"/api/public/card/12db32db-ff80-47c8-89fe-8b07d96afc85.md","stack_json":"/api/public/stack/614ecd6d-12cd-4195-bf9c-3def755c89b2.json"}}