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How to Meet the Challenge of Exponential Database Growth

Produced by Steve Nathans-Kelly

Information is still coming at us faster than ever before. How do we figure out what it all means? At KMWorld 2022, Art Murray, CEO of Applied Knowledge Sciences, discussed the key drivers of knowledge growth and how machine learning and AI can help.

Murray noted the five Vs of information: volume, velocity, variety, veracity, and value. These are the key drivers of our current information overload.

“The amount of information we are bombarded with is coming at us even faster at an accelerated rate across a wide variety of topics, disciplines, and perspectives even,” Murray said.

To figure out the real value of this data and meet this challenge, Murray suggested a two-sided semantic web.  

“Machines can understand what’s in the content that’s passed around but, there’s still a human component that's necessary,” Murray said.

Machines can ask questions that you program into them, but they will not ask questions on their own. Humans can teach machines and machines can tell us the patterns being identified.

“If we have a system of knowledge governance underneath to keep that managed, then we have a situation where machines are working on the volume, velocity and variety piece,” Murray said. “And the humans are working on the veracity and value piece.”

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