As Chat GPT and other like AI tools become prevalent, enterprises are enabling their teams to create custom instances for them to train to serve their own purposes.
With Confluence being a core repository for corporate data, these multiple custom Chat GPTs are all requesting access to query and ingest.
I'm interested to hear from others facing this dynamic. How are you managing to create order, maintain security and reduce duplication of queries/resource consumption while sponsoring innovation and helping find value in these AI bots?
How are you managing to create order, maintain security and reduce duplication of queries/resource consumption while sponsoring innovation and helping find value in these AI bots?
I am a SME in Artificial Intelligence specifically in Natural Language Processing and Optical Character Recognition publishing my first papers on the topic in 2014 so I am building my own. Starting from the world of endless documentation in Enterprise Operations that I live in and moving outwards. I am not sitting around waiting for someone just a qualified as I am to deliver me a glorified search tool for Confluence. ChatBots are nice to have but not need to haves. They start a glorified queries that eventually you can converse with and navigate you to the exact data point you need.
I have been developing on on and off for about 2 years and now I m making it my primary goal to be able to to Confluence into more of a Wikipedia for information distilled from data than a dumpster for everyone to put their junk in until the next order for garbage comes.
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