Nothing is smart yet. What people understand under automl is different but I’m referring to meta learning here, be it the architecture, the optimizer, the learning rate etc. Optimizing these things requires an outer loop in addition to training the architecture and for architecture search in particular this boils down to training lots of models and evaluating all of them. There are ways of making this search a bit better than random search with techniques such as regularized evolution (essentially evolution with a bias for younger individuals) or other tricks but all of them require huge compute resources.