It depends on what I’m trying to communicate. For example:
“ML selects for low loss” → “Trained networks tend to have low training loss”
This correctly highlights a meaningful correlation (loss tends to be low for trained networks) and alludes to a relevant mechanism (networks are in fact updated to locally decrease loss on their training distributions). However, it avoids implying that the mechanism of ML is “selection on low loss.”
What’s your preferred terminology?
It depends on what I’m trying to communicate. For example:
“ML selects for low loss” → “Trained networks tend to have low training loss”
This correctly highlights a meaningful correlation (loss tends to be low for trained networks) and alludes to a relevant mechanism (networks are in fact updated to locally decrease loss on their training distributions). However, it avoids implying that the mechanism of ML is “selection on low loss.”