[quantadev]

I meant the normalized hyperspace direction (unit vector) represents a particular "skill" and the distance into that direction (extending outside the unit hypersphere) is years of experience.

This is geometrically "meaningful", semantically. It would apply to not just a time vector (experience) but in other contexts it could mean other things. Like for example, money invested into a particular sector (Hedge fund apps).

This makes me realize we could design a new type of Perceptron (MLP) where specific scalars for particular things (money, time, etc.) could be wired into the actual NN architecture, in such a way that a specific input "neuron" would be fed a scalar for time, and a different neuron a scalar for money, etc. You'd have to "prefilter" each training input to generate the individual scalars, but then input them into the same "neuron" every time during training. This would have to improve overall "Intelligence" by a big amount.