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.

Artificial intelligence (AI) tools for media let you create content at scale in a previously impossible way and you don't even need design experience to create something impressive. But, these sectors have only scratched the surface of AI capabilities. On a seemingly daily basis, new AI tools emerge to help people create articles, video scripts, logos, and more. Naturally, these tools have investors excited. However, they've plenty to offer to content creators, marketers, and digital agencies too.

AI and ML are top of most 2018 trend lists, with the technologies being adopted by many different industries. Indeed, experts forecast these technologies will be incorporated as part of the standard toolkit for broadcasters to transform the process of creating and managing content. BBC Research and Development Senior R&D Engineer Stephen Jolly said the demand for automated intelligence is coming from everywhere. He defined AI as the use of computers to automate tasks that would otherwise have to be completed by humans. ML is a technique under the AI umbrella and notably in the spotlight for its ability to optimise and enhance processes.