Here we go again? Searchable video. #knowledge-transfer #video #search


Back in the early days of KM, big 4 consulting firms (I think there were six back then) saw the potential of KM and started experimenting with various tools and approaches. And it made sense for them to get onboard early: their assets were purely knowledge-based and went down the elevator every night. 
Back in 1989, Andersen Consulting hired AI guru Roger Schank and gave him $30million to play with and continue his research (he was at Stanford) hoping for some breakthroughs they could apply to their business. 

One KM-related project he worked on involved conducting and videoing knowledge elicitation interviews with experts. The thought was that if we could simply interview people and video it all, it would capture knowledge in a way that could be then inventoried, tagged and searched for future retrieval and re-use. I don’t know how much he spent on it, but word was it was in the millions. 
In any case, that didn’t work. When I learned about this effort I was at IBM, and I knew it wouldn’t work. We didn’t have the tools to cope with vast amounts of unstructured data, even when it was in text format, much less video format. 
But maybe now that is about to change. Some MIT alums are building a startup called Netra around an AI engine that is supposed to be able to parse video content and categorize it automagically. Might be a good one to watch. Who knows? Maybe Schank will be vindicated after all, and video knowledge elicitations will become a thing again. 
Now MIT alumnus-founded Netra is using artificial intelligence to improve video analysis at scale. The company’s system can identify activities, objects, emotions, locations, and more to organize and provide context to videos in new ways.


Tom Short Consulting
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