Introduction

Machine co-creativity continues to grow and attract a wider audience to machine learning. Generative models, for example, have enabled new types of media creation across language, images, and music including recent advances such as IMAGEN, Flamingo, and DALL·E2. Machine learning models achieving state-of-the-art in traditional media creation tasks (e.g., image, audio, or video synthesis) that are also being used by the artist community will be showcased. Researchers building the next generation of machine learning models for media creation will be challenged in understanding the needs of artists. Ethical implications, ranging from the use of biased datasets, replicating artistic work, and potential eroding trust in media content.