AI (Artificial Intelligence) is becoming more and more common as new applications of it are developed. I thought it would be a good idea to share some fundamental data about this and perhaps reduce unnecessary mystery around it.

I found it interesting to learn that the basic “thought” process used by AI is extremely simple. By executing multiple learning runs very quickly and scoring success and failure each time, a Darwin-like evolution is brought about.

It’s as if we could run through the development of life forms from plankton to creative human genius in just a couple of weeks. That last statement is of course an absurd parallel on many levels, not the least of which is the fact that AI will never develop into a life form. 

On a more practical note though, there are many applications – and more being identified daily – that will benefit enormously by using the AI architecture: massive data collection, massive processing power to quickly analyze the data and, over time, create reliable predictions of future events.

Several companies are now promoting AI features in their CRM applications, and expound effusively about how CRM will never be the same, as if you will harness the power of countless minions to rip through your files and show a faster, better path to sales success. I am not saying that this will not work, but as of today (April 2021) I think this may be misplaced emphasis for smaller businesses, where you will hamper your potential by trying to put machines in where live people should be.  I’ll let history (not AI) determine if this prediction is valid or not.

The first video referenced below provides a beautifully simple explanation of the AI process, referred to as Machine Learning.  The second video is a little more in depth and hints at some of the math that can be employed.

I hope you enjoy this very brief overview and video selections, and I look forward to your comments.


Mark Thomas is a Data Solutions Master. He is always happy to receive inquiries on any topic. He can be reached here.

How Machines Learn

The 7 Steps of Machine Learning

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