When you said that the objective was to « find the type of strategies the model currently learning before it becomes performant, and stop it if this isn’t the one we want »
But how would you define what attractors are good ones ? How to identifiate the properties of an attractor if no dangerous model as been trained that has this attractor ?
And what if the num er of attractor is huge and we can’t test them all beforehand ? It doesn’t seem obvious that the number of attractor wouldn’t grow as the network does.
Thanks for this nice post !
When you said that the objective was to « find the type of strategies the model currently learning before it becomes performant, and stop it if this isn’t the one we want » But how would you define what attractors are good ones ? How to identifiate the properties of an attractor if no dangerous model as been trained that has this attractor ? And what if the num er of attractor is huge and we can’t test them all beforehand ? It doesn’t seem obvious that the number of attractor wouldn’t grow as the network does.