Feasibility Study with Edinburgh Innovations: Scaling Solutions for Neural Network Training with Artist IP Protection

人工智能(AI)正在从根本上改变我们定义、生产、销售、体验、保护和分享音乐的方式。DataMind Audio是一家由音乐家在AHRC资助的Creative Informatics项目的宝贵支持下为音乐家创建的新公司。这项可行性研究是与爱丁堡创新有限公司合作进行的，由爱丁堡大学里德音乐学院院长马丁·帕克博士领导。在这项可行性研究中，DataMind Audio将与电子音乐家合作，评估一种用于训练我们的神经网络或“艺术家大脑”的缩放解决方案。我们基于人工智能的插件或电子乐器允许用户将任何输入的声音输入到根据艺术家的创造性输出进行训练的“艺术家大脑”。我们的“艺术家大脑”在伦理上接触到了一位原创艺术家风格的精髓和模式。目前，我们的算法是根据20位世界级艺术家的创造性输出进行训练的，其中包括理查德·迪瓦恩、马克斯·库珀和比尔先生。这些算法为音效设计师打开了新的音景，让他们以全新的方式探索和分享。我们在声音设计和人工智能领域的著名艺术家和先驱名单表明了我们努力的质量、原创性和完整性。我们最近长达一个月的AI研讨会系列得到了电子音乐制作明星Tipper和Slander等电子音乐制作明星的支持，以及Ableton用户研究主管Till Richter等经验丰富的领域领导者的支持。我们的创始人团队已经建立了一个突破性的产品体系，保护原创艺术家的知识产权，并向他们支付使用费，以使用他们的“艺术家大脑”，这是对他们的音乐输出进行训练的神经网络。我们使用人工智能来增加而不是减少音乐人的收入流，通过一个基于英国的道德在线市场。作为扩展的关键一步，爱丁堡的帕克博士与DataMind Audio组织了一项可行性研究，以便：*开发一个具有成本效益的标准化工作流程来训练我们的神经网络，或称“艺术家大脑”；*为4名‘艺术家大脑’的人类训练者测试以人工智能为重点的工作规格，我们称之为模型可靠性工程师(MRE)；*聘请一批下一代音乐家/音响设计师，利用爱丁堡大学相关教学计划的毕业生，培训“艺术家的大脑”，并向他们介绍神经网络的进步；*评估我们从这一项目中得出的结果，以评估复制和扩大规模的最佳方式，同时保留真实的人类精心策划的音乐质量--这是我们产品的主要区别。

Artificial 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.