Abstract
We demonstrate a system for filtering media streams according to the collective taste of a leader-less informal clan of users. Applications on mobile devices receive streams of content items that are assessed by local software agents. The agents learn the collective preferences of the tribe by forming a distributed multi-agent society that shares data on the behaviour of all users. The underlying artificial intelligence is based on support vector machines that cooperate by broadcasting new support vectors. The demo shows micro-blog readers on cell phones running support vector machine agents with text kernels and communicating over IP Multimedia System networks.