The combination approach jives well with my use of the models in a number of areas. I guide models to use best-in-class algorithmic approaches as available. (Eg using constraint solves for a particular problem where pure Monte Carlo rarely gives "in-bounds" data.)
I find it odd that frontier models often don't suggest the most powerful methods for crushing problems, but it may be that the training data doesn't actually have "good enough" experts on the problems I encounter. If the experts don't know about the best ways to solve the problem, they'll get dinged in training for even trying.
I find it odd that frontier models often don't suggest the most powerful methods for crushing problems, but it may be that the training data doesn't actually have "good enough" experts on the problems I encounter. If the experts don't know about the best ways to solve the problem, they'll get dinged in training for even trying.