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I find it interesting when people ask 'Is this normal?'

Normals aren't a state. 

They are always contextual and temporary. 

And new normals are emerging faster than ever before.

Researcher at MIT Media Lab | Creating futures | cyrus.website |

I think of “normal” as a Gaussian - in high dimensional space we’re always descending to some local minima normality (gradient descent) in retrospect but the loss function is dynamic - and there’s always new data, new context that’s emerging faster than ever 

Which sort of normality is a kind of emergent property that isn’t fixed but more dependent on framing of the data w.r.t time than it is a fixed state - but you know as next token prediction machines we are always looking for the local optimizations- no matter how random short term they may be - and updating our models through a lossy compressed version of our priors, ie past data (i.e. reality)