An Innovative and Revolutionary SME Machine-Learning AI-Powered Digital Stage, Predicted to Save 60+ Hours Per Role Cast

Flaircube Ltd(Flairbox)，由罗伯特·伊迪斯、埃利奥特·扬克斯和彼得·希克林组成的核心团队，正在为表演艺术专业人员提供革命性的机会，让他们远程联系和合作。Flairbox的平台将视频分享与机器学习相结合，允许演员轻松上传视频，选角导演可以高效地对视频进行分类，为每个角色演员节省60个小时。这一解决方案将帮助该行业在新冠肺炎关闭后恢复和重新装备，并将引领公平选角实践的道路。3和6月仍在研发中，同时为尽可能多的演员提供数字舞台，目标是在6个月前达到5,000人。到12月，Flairbox将利用收集到的数据，为他们的第一次机器学习人工智能排名系统提供动力，该系统打破了多达7,500名演员的进入壁垒，为选角导演节省了多达60个小时。到第18个月，Flairbox将拥有一个商业上可行的机器学习人工智能排名系统，供每一位英国选角导演和演员使用，已经有12000名演员在使用该平台表演和寻找工作。这项技术将为每个演员节省60多个小时，相当于为每个角色为制片人节省了2400 GB以上(选角导演时间的40 GB/小时)，同时消除了目前演员之间基于教育、经验、地点和社会经济背景的歧视。

Flaircube Ltd (Flairbox), with a core team of Robert Eades, Elliot Janks and Peter Hickling, is revolutionising opportunities for performing arts professionals to connect and work together remotely. Flairbox's platform combines video sharing with machine learning to allow actors to easily upload videos that casting directors can efficiently sort, saving 60 hours per role cast. This solution will help the industry recover and retool following COVID-19 closures and will lead the way for equitable casting practices.Months 3 & 6, still in R & D whilst providing a digital stage to as many actors as possible, with a target of 5,000 by month 6\. Giving those actors a chance to return to their profession with somewhere to perform and be discovered for their work.By month 12, Flairbox will be utilising collected data in order to power their first iteration of a machine learning AI ranking system that breaks down barriers to entry for up to 7,500 actors and saves up to 60 hours per casting for casting directors.By month 18, Flairbox will have a commercially viable, machine learning AI powered ranking system available to every UK casting director and actor, with 12000 actors already using the platform to perform and find work. This technology will save more than 60 hours per casting, equating to more than £2,400 saved for producers for every role (£40/hr of casting director's time), whilst simultaneously removing current discrimination between actors based on: education, experience, location and socioeconomic background.