[fnl]

First of all, neurons don't have just one activation function. Each dendrite has. So, anything from dozens to thousands. Second, that definition doesn't cover the entire issue of multiple feedback loops. Third, this doesn't cover memory effects at structural (cytoskeleton) and local levels (vesicles), much less generic levels (RNA and your genes). And then we haven't even gotten into metabolomic and epigenetic wriring in your neurons ...

Calling those chained regressions similar to the brain is about as correct as saying that a 3y old's drawing of a car is similar to a real Tesla...

[cbarrick]

I mean, doi.

McCulloch and Pitts published in the 1950s. Of course we know more about the brain now.

If I were to ask you "How does intelligence arise from a network of activations?" Would you genuinely say that it has nothing to do with the McCulloch and Pitts theory?

[fnl]

I would honestly say we really have no clue, and maybe add that as far as we can tell, activations play as much of a role in intelligence as a myriad of other factors.

But more generally, I am just so tied of this "brain metaphor" on deep learning. It is a funny way to wake up your students (well, at least 10 years ago it was...), but trying to stretch this metaphor much more than that is just painful. Heck, even the activating "functions" (plural, as we now know) in a neutron isn't really a set (!) of (singular, independent) functions, it's just a top level name for a mind-boggling number of things happening as neurons "fire", with a mathematical formalism to approximate what's going on. In fact, calling an activation a "function" is probably belittling the biological processes behind them.