Exploring Creative Frontiers of AI for ME Production and Distribution

摘要

In recent years, Artificial Intelligence (AI) tools are beginning to revolutionize Media and Entertainment production and distribution industry. As with other industries, such as mobile, business, transportation, gaming, robotics, security, education. Much like non-intelligent automation, artificial intelligence applications can be trained to perform human-like tasks. Some of the common skills currently imitated by AI include visual perception, speech recognition, decision-making, and adaptability — AI tools can be applied to perform tasks that were impossible to accomplish. AI performs tasks faster and with greater precision than their experience human counterparts. AI applications are beginning to augment the creative decision making skills of the production and distribution team, enabling energy, talent and enthusiasm to be focused on what only humans can do. At least for now. — During the M&E creative production process images, sound, and metadata are collected and stored, analyzed, identified and selected. Recovery of content from the media libraries and archives is critical to the creative process. This includes production generated multiple media formats of video, audio, graphics, and other types of data including text, scripts, and playlists. — It takes multiple tools to organize, collate and curate media and data from different formats and types. Metadata creation technologies help create the metadata necessary for content search and retrieval. While several logging and recognition technologies can generate some metadata automatically, the results are often incomplete inaccurate and far from comprehensive. — AI can be applied to myriad applications enhancing, accelerating and increasing the capacity of the media supply chain: AI services such transcription, language and dialect translation. face and object recognition, social media sentiment analysis. geolocation and fingerprinting are just a few examples. — Newly developed artificial intelligence for media asset management fuses the ability to understand all media and data types and perform discovery, synthesize and curate. — Across the media supply chain employing automated technologies that can create the metadata, then index and catalog it during the creation or acquisition process would help the creative process downstream. There is a still a requirement for the creative team to identify relationaships and the preferred clip selection. It needs the legal team to add permissions, control access, contractual distribution and expiration criteria. In news production using ML techniques with pattern matching, additional content can be identified.