[skohan]

> Advances in network architecture (e.g. the recent trend towards skip connections and parallel processes) is likely to give insight to how an underlying, more complex system is likely to operate.

Maybe. The thing about these advances in ANNs is, so we have any reason to believe they have anything to do with the way biological neural networks work? It might be the case that these kinds of advances correlate to a more accurate understanding of how our brains process information, or it might also be the case that these are just optimizations on a mathematical model which is fundamentally different to biological intelligence.

To me advances in the other direction are much more compelling. We actually know quite a lot about how biological neural networks work. The way that electrical and chemical signals are transmitted is quite well understood, and can be accurately modeled through mathematical models derived from physics and physical chemistry. At the moment, the problem seems more to be more about how to accurately model this system at scale which we already have tons of data on.

It's not that I think these innovations in ANNS have no value, it's just that it seems that ANNs are quite tangential to neuroscience.

[crawfordcomeaux]

From studying ANNs, I've reconceived of how I view myself from a programmatic perspective. I have used the resulting models to change myself in useful ways. If they're not perfectly accurate, they may still be accurate enough to be useful.

The trick, to me, is to avoid falling into the trap of thinking imperfect models aren't useful. Then the accuracy matters less.

An example of a useful intuition was realizing choosing to believe something is a skill and I can choose to believe the opposite of anxious thoughts to safely defuse anxiety as long as I'm meeting my needs.

I know people who've been in therapy for a long time before learning that one, so I'm gonna keep using ANNs as a guide for self-hacking. It's way too useful to me.

[skohan]

It's fine and good that ANNs can serve as a metaphor for your own mind. That's something very different than saying they're going to be useful in unraveling the scientific mysteries of the brain.