Media & Entertainment
Use Cases
Newsfor Media & Entertainment
Autogenerate captioning on video or audio files
Autogenerate captioning on video or audio files. This speech to text service potentially saves significant human effort but will work less well in languages that have not yet had the full research effort of - say - English and Chinese, where error rates remain a challenge.
Automate community management by monitoring online discussions and flagging abuse
Software which automates the work of human moderators to identify abuse and misconduct in online messages between video game players on community boards.
Automate flagging and/or removal of user generated and uploaded media content
Companies use AI to automatically flag and remove user content on social media and other platforms which violates regulations and government mandates
Automate generation of articles or other written work like press releases
Automate generation of articles - for example using national data sets and then producing local variant articles from this. The same can be done for press releases.
Automate generation of conversational media content
Automate generation of conversational media content for audio driven interactive programming on conversational platforms (e.g. Alexa). This is for entertainment purposes.
Automate presentation (for example of news reading) on TV and other media
Being a news anchor involves the single task of reporting - essentially reading out a script. Therefore, AI can work for automating news presentation on TV and other media, using natural language generation and processing.
Automated captioning of video from key events such as sports games
Automated captioning of video (or audio) from sporting events enables the creation of sophisticated video libraries that can be searched without the need for a huge amount of (costly) human trawling to find relevant media moments. The creation of meta-tagging hugely simplifies the indexing process. The potential to then build sophisticated, targeted media feeds - for example individual player highlights - is then possible at acceptable cost.
Automatically classify businesses
Using AI to automatically classify businesses for inclusion in a corporate listing database. Key financial and business data will be categorised at the same time. This may be an initial step in building an investment process where other steps may also be automated (potentially with AI).
Confirm animal identity through eye scans
HIgh value animals can need identifying at critical moments - for example to ensure that the right horse has been entered in a race or has been provided to stud. Individual eye scans are kept on record and then a portable scanner can be used to ensure that the right aninal is present.
Create 3D models of 2D images
Taking a 2D image this technique allows for the creation of a 3D model of the objects captured in the photos. This obviouasly works better on images of objects with known characteristics - like humans for example.
Create ersatz individual digital presence based on digital content capture
Use communication data - written and spoken - to construct a digital personality for ongoing remote interaction. Whilst largely a gimmick at this stage - able to capture tone of interactive style but little of any underlying thought processes - the potential for building out artificial constructs of departed loved ones, or simulacra of advisers or leaders may soon no longer be simply in the realm of science fiction.
Create music
Musicians have historically used innovative ways to create their music, such as digital and electronic music - but the limit has always been their muse. Generative AI can be used to create songs, melodies, and instrumentation by being trained on previously recorded music. The results can be tuned to match artists'' unique characteristic genre and style - for example creating music in the style of a long-dead master.
Create visual art
It is a matter of debate what the nature of creativity is. If it is to gather multiple inputs and then to combine these to deliver a new take - in this case as a piece of art, whether painted, digitally created or even scuplted with basic robotic functionality - then this is creativity. If creativity requires emotion or understanding then this is not it.
Customise media library catalogue images to drive user click through
Based on customer''s media interests and viewing history, automate the creation of the media image (e.g. from a movie) that is most likely to drive click-through to the media product - although the technique has wider uses in optimising the purchase funnel in ecommerce.
Detect manipulated or falsified media
Detect manipulated or falsified media to discover attempts to damage reputations or create unwarranted legal situations. The rise in concerns over `fake news` deployment - especially at such sensitive times as during an election - is a growing area of security and media concern. with potentially huge ramifications.
Detect plagiarism in documents
In a world where information is at anyone''s fingertips plagiarism is a constant challenge, especially in academic circles. NLP can be used to match content and identify suspect material.
Determine bookmaking odds for sports and other events
Sports betting is a hugely growing area, where increased data volumes on individual, team performance and market statistics means machine learning can build betting odds for bookmakers - and also for bettors to attempt to game the odds offered. Some areas - reading human emotions mid-game for example - remain harder to access reliably. This creates the opportunity to offer more targeted products (for example: chances of a given player scoring in the next x minutes).
Discover new trends in content consumption patterns
Discover new trends in consumption patterns (e.g., viral content). Increasingly this sort of data-driven approach is driving editorial decisions - potentially to the detriment of risk-taking originality.
Generate research for news content
Generate research for news content - stories may emphasise AI (negatively or positively) or simply be data journalism on large data sets
Generate works of literary fiction
Machine learning can be use to generate works of fiction - the algorithm will recreate common patterns of wording in a way that implies artistic output. However, the machine does not understand what it has created - and there remains significant scepticism as to the average quality of output. It may be argued that this is a broader issue of what constitutes art.
Highlight likely issues like copyright infringement or audience age suitability in media content
Identify pertinent features like copyright infringement or audience age suitability in media content. This will support deployment of control tools (eg deletion) especially on high volume video viewing sites.
Improve accuracy of sports event scoring using real-time sensors
Use 3D sensors to support the decision making process for judges in sports that require scoring or judgement calls. An example of this would be gymnastics where the tool can be trained on routine peformances. These tools may also be used to support individual''s althletic training regimes.
Improve audio quality
Improving audio quality - for example by eliminating background noise or static - has numerous follow-on applications: helping deliver better outcomes from translation or hearing impairement support devices, delivering cleaner data for NLP products and providing better consumer experiences.
Improve image (and video) quality
Use deep neural networks to remove clutter from images - this can vary from blurring to watermarks. This will often be used when poor quality image data has been captured and mass data cleaning will help improve training data for other AI applications.
Integrate security systems at public entertainment venues such as sports stadiums
Managing event security has the benefit of operating inside a closed environment where huge volumes of data can be generated by multiple video, sensor and other data feeds. Integrating this and ensuring fast and reliable data visualisation and risk monitoring is a sophisticated AI use case.