10080229Feasibility Study with Edinburgh Innovations: Scaling Solutions for Neural Network Training with Artist IP ProtectionClosedCollaborative R&DInnovate UKArtificial Intelligence (AI) is radically altering the way we define, produce, sell, experience, protect, and share music. DataMind Audio is a new company created by musicians for musicians with the invaluable support of the AHRC-funded Creative Informatics project. (University of Edinburgh). During this feasibility study, conducted in partnership with Edinburgh Innovations Ltd, led by Dr. Martin Parker, Head of the Reid School of Music (University of Edinburgh), DataMind Audio will work with electronic musicians to evaluate a scaling solution for training our neural networks or 'Artist Brains'. Our AI-based plugins or electronic instruments allow users to feed any input sound into an 'Artist Brain' trained on the creative output of an artist. Our 'Artist Brains' ethically access the essence and patterns of an original artist's style. We sell these online from our UK-based marketplace. Currently, our algorithms are trained on the creative output of 20 world-class artists including Richard Devine, Max Cooper, and Mr. Bill. These algorithms unlock new soundscapes for sound designers to explore and share in totally new ways. Our list of notable artists and pioneers in the field of sound design and AI speaks to the quality, originality, and integrity of our endeavor. Our recent month-long AI workshop series was supported by electronic music production stars such as Tipper and Slander, as well as seasoned field leaders like the head of User Research for Ableton, Till Richter. Our founder team has already built a breakthrough product system that protects the intellectual property of original artists and pays them royalties for the use of their 'Artist Brains', which are neural networks trained on their musical output. We use AI to increase, rather than curtail, musicians' income streams via an ethical UK-based online marketplace. As a vital step in scaling, Edinburgh's Dr. Parker has structured a feasibility study with DataMind Audio in order to: * Develop a cost-efficient, standardized workflow for training our neural networks, or 'Artist Brains'; * Test an AI-focused job-spec for 4 human trainers of the 'Artist Brains', who we call Model Reliability Engineers (MREs); * Engage a group of the next generation of musicians/sound designers, drawing on graduates of the relevant University of Edinburgh teaching programmes, to train the 'Artist Brains', and introduce them to advances in neural networks; * Evaluate our findings from this project to assess the best ways to replicate and scale up, while retaining authentic human-curated musical quality -- the key differentiator of our product.