Go is so much more complex than chess in terms of the number of possible moves and the number of possible iterations that Google didn't do what IBM did with Deep Blue. In 1997 Deep Blue, literally the programmers had Deep Blue consider every possibly move and go out to examine every single possibility and then go back and pick whichever one had the most possible mean combinations going off of that branch that it set up because Go is thousands and thousands of times more complex with so many more possible moves. I mean, I believe there's something like trillions of possible moves or possible sequences in any given Go game. What AlphaGo, which was Google's project did, they taught it by having it play itself. Playing itself against games to figure out what the best practices and best strategy were.

Over the last year, I have been immersing myself in a lot of Artificial Intelligence research, including reading multiple books on AI and taking an online class from Stanford on the fundamentals of Artificial Intelligence. FYI, this class was taught by an Adjunct Professor at Stanford, Andrew Ng, a co-founder of Coursera.org, All of this study and research has given me a much better understanding of AI, what it can and can't do, and its potential impact on our world. Although I am not an engineer and come from the marketing research side of the tech market, after nearly 40 years dealing with technology at all levels, my depth of understanding of technology and its impact on our world has always been present in my work and research. AI has been around for decades but is even more prevalent in our tech world today.