We have about 100 artificial intelligence (AI) engineers working at the company I work for. Simplifying too much, machine learning is part of AI. There are a ton of human variables in setting up machine learning. No one on the Committee has any clue what Google is doing. After working in technology for 20+ years I can go toe-to-toe with our AI engineers for only about 5 minutes and then I am completely lost. The committee could not last 5 seconds, they have a soundbite but really don't understand AI/machine learning at all. Truly scary.
By the way, Dayton must run up the score massively versus the likes of Detroit and
Fordham. It appears NET is materially influenced by raw offensive and data efficiency. In other words, it it does not adjust efficiency for competition. So for the efficiency numbers, beating #1 UVA by 5 is the same as beating #350 Fordham by 5. Huge incentive to run up the score as much as possible (proxy for efficiency) versus the likes of Coppin State, Detroit, and Fordham. This is madness. I could go on and on about the flaws of NET, but the lack of transparency is amazing.
