In recent times, neural networks have been used as generative models: algorithms able to replicate the distribution of data in input to then be able to generate new values starting from that distribution. Usually, an image dataset is analyzed, and we try to learn the distribution associated with the pixels of the images to produce shapes similar to the original ones. Much work is ongoing to get neural networks to create novels, articles, art, and music.
Artificial intelligence (AI) researchers are interested in generative models because they represent a springboard towards the construction of AI systems able to use raw data from the world and automatically extract knowledge. These models seem to be a way to train computers to understand the concepts without the need for researchers to teach such concepts a priori. It would be a big step forward compared...
