I don't know a lot about AI or machine learning so I'd take what I say with a grain of salt. I do know a lot about computers, though. I'm just spit balling here.

This is kinda the reason why I think this "AI" hype is a joke. I get the idea behind it, but a computer is only as smart as the user. Or in this case the data that it soaks up. And as advanced as they are they are mostly still just a novelty save for very specific purposes. The whole idea of a black box in machine learning is just inefficient and wasteful. The fact that we have no idea how these AI's achieve their output is a big problem and a huge waste of resources. In a basic sense, if you put 2+2 into a calculator it will give an output of 2. If you put 2+2-(3x9-18)+7 into a calculator it will give you an output of 2. If all you see is the result you will have no idea how much processing power is being wasted on unnecessary processes. As long as we keep shoving information into these things without thinking about what we put into them they will only get more wasteful with unnecessary data. I know they add certain parameters and weights to negate things like this. But there's no way in hell they've accounted for even 1% of what would be needed.

Don't get me wrong, I understand the practicality of using machine learning. I just think the way we are building it from the ground up is too simple for what we are trying to achieve at this point. I honestly think we are reaching a plateau with this kind of machine learning. We need more parameterization if we want it to get better.