Generative models, commonly referred to as GANs, are a family of AI architectures whose aim is to create data samples from scratch. They work by capturing the data distributions of the type of things we want to generate.

Here’s an interesting read on the topic.

These kind of models are being heavily researched, and there is a huge amount of hype around them. Just look at the chart that shows the numbers of papers published in the field over the past few years:

In this TED talk, you will meet AIVA, an artificial intelligence that has been trained in the art of music composition by reading more than 30,000 of history’s greatest scores. In a mesmerizing talk and demo, Pierre Barreau plays compositions created by AIVA and shares his dream: to create original live soundtracks based on our moods and personalities.