Exploring Inter-Concept Space with Neural Networks

A pocket of computational reducibility identified by an autoencoder may not align with human concepts, leading to an exploration of inter-concept space. In this space, the vast majority of images generated by a neural net may lack human narrative descriptions, showcasing unexplored territories. When seeking a scientific narrative, it's crucial to consider the constraints and complexities of operating within inter-concept space.