Weird thought I had based on a tweet about gradient descent in the brain: it seems like one under-explored perspective on computational graphs is the causal one. That is, we can view propagating gradients through the computational graph as assessing the effect of an intervention on some variable on all of a nodes' children.
Reason to think this might be useful:
Reasons why this might not be useful:
In light of reading Hazard's Shortform Feed -- which I really enjoy -- based on Raemon's Shortform feed, I'm making my own. There be thoughts here. Hopefully, this will also get me posting more.