First, the frameworks that provide theoretical support to the main flavors of automatic learning will be sketched. Then the focus will turn to algebro-geometric neural networks (their nature depends on the kind of inputs-outputs processed by their neurons) and the extensions of those frameworks to this kind of nets. The talk will finish by pointing out some challenges and opportunities for further research.