We know the brain and associated sensor behaviours are too large for us to fully simulate in a reasonable way on anything resembling current hardware (We also c

We know the brain and associated sensor behaviours are too large for us to fully simulate in a reasonable way on anything resembling current hardware (We also can't fully model it but as we approached the size of hardware to do so we'd probably solve many of the problems of doing so). So which hacks and shortcuts do you want to apply to reduce the dimensionality to something runnable? Step 1) will take far too long so AI research looks for things it can do well in the category of 2) without being a full simulation. Deep Learning has been unreasonably effective here.