Just because one internal operation is understandable, doesn't imply that the whole network is understandable.
Take even something much simpler: decision trees. Textbooks give these as an example of understandable systems. A tree where you make one decision based on one feature at a time then at the leaves you output something. Like a bunch of if statements. And in the 90s when computers were slow and trees were small this was true.
Today massive decision trees and approaches like random forests can create trees with millions of nodes. Nothing is interpretable about them.
We have a basic math gap when it comes to understanding complex systems. Yet another network type solves nothing.
Just because one internal operation is understandable, doesn't imply that the whole network is understandable.
Take even something much simpler: decision trees. Textbooks give these as an example of understandable systems. A tree where you make one decision based on one feature at a time then at the leaves you output something. Like a bunch of if statements. And in the 90s when computers were slow and trees were small this was true.
Today massive decision trees and approaches like random forests can create trees with millions of nodes. Nothing is interpretable about them.
We have a basic math gap when it comes to understanding complex systems. Yet another network type solves nothing.