my tldr: this explains 1) why huge models are important (so the gradient is high-dimensional enough to be monotonic) 2) why attention (aka connections, aka in

my tldr: this explains 1) why huge models are important (so the gradient is high-dimensional enough to be monotonic) 2) why attention (aka connections, aka indirections) is trainable at all; and says nothing about why they might generalize the dataset