Final synposis.
Neural Networks suck.
They just plain suck.
5% error rate on the best and most convoluted problem is still way too high
Its amazing you can make something see an image its been trained on, that's awesome....

But if I can't get a simple function approximator down to lower than 0.07 on a scale of 0 to 1 difference and the error value on a fixed point system is still pretty goddamn high, even if most of the data sort of fits when spitting back inference values, it is unusable.

Even the trained turret aimer I made successfully would sometimes skip around full circle and pass the target before lining up after another full circle.

There has to be something LIKE IT that actually works in premise.

I think my behavioral simulation might be a cool idea, primitive environment, primitive being, reward learning. however with an attached DATABASE.

Epoch 2/4
777/1054 [=====================>........] - ETA: 45:31 - loss: 2.6682

Screw you Keras model