AI systems generate high-quality music, but rely on vast musical datasets, which creates biased models. DAACI uses pioneering AI technology that allows our AI to compose in real-time without relying on pre-recorded tracks or edited audio samples. We encode composers' ideas to achieve this. In this project, we will build a tool with the University of the Arts London that enables musicians to contribute to our AI models directly. Our approach involves responsible co-design and creating a usable and intuitive front end for our dataset AI tools. Once the proof-of-concept is developed, we aim to crowd-source musical content and enable musicians to be recognised for their contributions. DAACI's approach has the ethical use and production of music at its heart.

In the emerging Web3.0 world, artificial intelligence (AI) offers composers/artists access to new ways of music generation by adopting generative AI music synthesizers. These Generative AI music tools generate music faster and more affordably compared to traditional methods. However, enormous productivity and efficiency opportunities are being held-up by widespread uncertainty of the legal implications regarding how to licence this AI content, to ensure a fair split between writers, publishers, labels, artists, producers and performers. This project focuses on the development of an ethics standard for all AI music companies, for royalty distribution to contributing rights holders. This addresses a widely held uncertainty of the legal implications regarding how to licence AI content, to provide a fair split between writers, publishers, labels, artists, producers and performers. Our project aims to benefit composers and artists by increasing their efficiency and productivity. It will benefit policy makers through a clear ethical framework. Its overall benefit is in consolidating the UK's position as a leader in AI for creative industries. DAACI is a UK-based SME in the emerging global music composing software market. DAACI's mission is to be the ultimate compositional assistant, taught by and learning from the artist, thus amplifying their efficiency and ability to create their own, novel music. We now seek to develop DAACI further to provide evidence of the ethical stance that we firmly uphold in the context of AI music responsibility. Generative AI music tools will be extended and tested during the project to generate music faster and more affordably providing enormous productivity and efficiencies. The Project partners are BIMM University (BIMM) and Lewis Silkin LLP (large enterprise). BIMM is the second largest provider of creative industries higher education in the UK. The BIMM Music Institute AI\_labs will support the research, providing testing activity and specialist inputs. Lewis Silkin LLP is a UK top 100 commercial law firm. The team on this project will look to provide market insight into the role of ethical AI and sustainable models for rewarding creators and rightsholders, given their broad expertise of the field of Creative AI.

This project aims to develop an AI tool which will instantly recommend music tracks that would go well with a specific video clip (i.e. movie trailer). Our proposed recommendation engine will be able to dynamically recommend music tracks that are well-suited to the video content, even if the user does not have a specific music track in mind. This project unites Pyrsos' outstanding research capabilities with DAACI's existing music catalogue and software platform infrastructure to build cutting edge machine learning technology and make it available to a broad audience. It builds upon state-of-the art representation learning for multimedia and advances it by training a neural network that can map video and music excerpts into a shared semantic space. Extensive user testing will be conducted during the project to evaluate the technology and provide feedback.

DAACI is a UK-based SME in the emerging global music composing software market. DAACI's mission is to be the ultimate compositional assistant, taught by and learning from the artist, amplifying their ability to create their own music. This project will develop a novel AI compositional tool for the production music market, capable of generating a dynamic live stream of truly original music to meet the demands of our customers. Key to the innovation will be the ability to specify the music that is created based on mood, narratives, need, and intensity. A prototype will enable trial users to create adaptive generative music.