AI Matchmaker

What do you think of when you hear the term ‘AI’?

The Terminator?

Allen Iverson?

Robots taking over?

AI (Artificial Intelligence) is fascinating. It means so many things to so many people. 

Some of us embrace AI, feeling as though it will automate mundane tasks to allow humans to concentrate on more advanced tasks. Others fear AI, believing it’s the beginning of the end of humans providing value.

Regardless of where we sit on the spectrum, AI is becoming mainstream. We each interact with it every day.

AI is our personal assistant (Siri, Alexa, etc.).

AI helps drive our cars.

AI pushes advertisements to us.

AI enhances our video games.

AI makes our social platforms more relevant.

AI is everywhere.

AI can be complex, if you let it. AI encompasses deep technical sub-categories like Machine Learning, Robotics and Neural Networks.

We don’t need to know these things inside and out in order to explain AI.

AI is about solving problems and gaining efficiencies. Find a problem or something that’s inefficient – you’ve probably stumbled on an AI use case.

Some that immediately come to mind:

  • A coffee shop espresso machine going down (problem)
  • The line at the DMV (inefficient)

The problems and inefficiencies are there. The tools and technology are there. We just have to play matchmaker between the two.

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