Collaborative AI

As the universe of artificial intelligence applications grows, we find that the smartest collaboration is are smart re-use. There is increasing value to be found in meta-projects which are projects of projects of projects ... it's a matter of increasingly smarter digestion and value-addition looking at crowdsourced re-use of crowdsourced intelligence. Effectively, the technologies and methods which are used to achieve anything LASTING in the realm of collaborative AI are fundamentally an intelligence skill, a matter of sustainability engineering ... it might sound like new stuff, but it's really a matter of applying an old school process engineering mindset information reliability engineering and doing it in a infinitely maintainable and extensible fashion as the technology and people using the technology develop and advance ... crowdsourcing is no different than leading a population was thousands of years ago -- intelligence is about watching and understanding people.


As an example of the ventures being built in this realm in the last few years, consider the artificial intelligence and machine learning ventures working to provide smarter, faster, better ways of performing the necessary task of business intelligence footprinting. One specific example in this particular realm involves a relatively new startup like Owler relies upon engineered crowdsourcing to provide users with a Daily Snapshot of the latest industry insights and curated news events per a user's personalized competitive graph or selection of companies that a user follows, comments upon, interacts with.

CollabAI project on GitHub

GYGbot project