collaboration
< local
<
< business
< google
< knowledge-markets
< collective-intelligence 2
< alexko
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Sci-mate provides several very easy solutions for academic scientists wanting to effectively distribute ideas and technology. Our goal is to help scientists capture the benefits of sharing ideas. Only when we share our ideas do they become valuable . The Sci-Mate is designed to help generate value, and then return this value to contributors. The site and its content are owned by members, free from commercial or single interest groups, and is proposed as a democratically controlled co-operative controlled by its members. Free foundation m embership is now open to Research Scientists , Technology Managers , and Industry Representatives .
This open source release has already led to many efforts to foster further development and provide EtherPad-like services. If you are looking for a service based on the EtherPad software, or want to run your own EtherPad server, see the following links (not affiliated with Google, use at your own risk): If you are looking for a Google alternative, the new document editor for Google Docs provides fully-real-time editing, chat, advanced formatting options, and commenting features.
Transparently-shared ideas, like those that circulate on popular social networks such as Digg, Delicious, and StumbleUpon, may be destroying people's creativity. According to a new study published today by two cognitive scientists, people who share ideas in large groups tend to stagnate rather than innovate. They "glom onto" popular ideas and then don't pursue new discoveries or breakthroughs because they've already accepted the common wisdom of the crowd.
Since last year I was contributing to MIT project that attempts to create a comprehensive Handbook of Collective Intelligence. This project was initiated by the newly created MIT Center for Collective Intelligence (CCI). It is quite logical that the managers of this project decided to use a collective intelligence technique to describe the collective intelligence itself. The collective intelligence techniques (e.g. human-based computation ) that process natural languages are ideally suited for this purpose and were successfully used to describe themselves in the past.