An abstract, multidimensional space that organizes essential features extracted from the data used to train machine learning models. We can think of latent space like an organized warehouse where complex information (images, text, etc.) is stored in a simplified form and similar items are positioned close together. This mapping of features allows the AI (artificial intelligence) to understand patterns and relationships embedded in the data and use this knowledge to generate new content.