All of these things are still just statistical models.
People hope that by training on enough data, these things will produce inferences. But they don't. They just train on the data.
A baby who grows up to the age of, say, five doesn't need to know that a baseball bat on the head hurts just as much as a Tonka toy or whatever else. It infers that from the data it has and applies it to everything it sees.
This is the crucial step that we can neither define, detect or induce in our "AI" of today. People just hope that a complex enough system will somehow display this trait that we can't define without us doing anything different to what we're doing now. I can't see it. I'm not even sure it's possible with classical computing.
960 hours of training is also NOTHING for a system that is itself only a slow-running tiny-sliver mockery compared to even insect-sized neural networks running in real-time.
We honestly need to just find something new... anything that needs ANY human parameter-tweaking or hand-holding obviously is not sufficiently able to make its own inferences about what those parameters should be, what's important or not, and what's going to lead to success.
Biting the hand that feeds IT
