Cover Story criteria. With user data, that will get even better, you are able to personalise cover artwork based on what is more likely to appeal to a specific user. The same is applicable to content itself.”
Cover Story criteria. With user data, that will get even better, you are able to personalise cover artwork based on what is more likely to appeal to a specific user. The same is applicable to content itself.”
“ It absolutely can,” agrees Child,“ and it could potentially bring about more timely and more relevant content to viewers, either by matching up more precisely what content a viewer is interested in, or making it easy to find. In the medium term I also hope to see even more of a feedback loop from viewers into choices of what content is being made, which will further improve those choices.
“ Yes,” says Sherwood.“ This is a major focus area for commercial AI companies who want to help broadcasters monetise the mountains of content that exist in broadcaster’ s archives, both old and new. Examples include up-sampling old content for higher resolution devices, auto-tagging content for driving higher relevancy to viewers
and advertisers, and even auto-generating schedules for programming.”
“ Many broadcasters have very large archives, and manually searching millions of hours of programmes would be simply impossible,” admits Karp.“ With the move to IP technology and the cloud, these archives become increasingly digitised, migrating the content in the right formats for the application of ML and AI.“ The recent example is BBC Four’ s experimental AI and archive programming. AI helps programme makers and schedulers unlock valuable resources and put together a manageable selection in a fraction of the time. According to BBC,‘ this enabled researchers and schedulers to uncover programmes they may never have been able to find, and will broadcast a selection that haven’ t been seen in years’.” ARCHIVE.“ AI will help reduce the number of mundane tasks in the broadcast space so that staff members can dedicate more time to creative, impactful ones,” suggests Martin.“ More than that, this emerging technology will deliver enriched information that will make it easier for them to do their jobs. Through tools like facial and voice recognition, content creators and producers have access to a more
“ However, the benefits of AI go far beyond just automation.”- Stuart Almond, Sony Professional Solutions Europe meaningful set of data that they can use to create richer, more compelling storytelling.”
“ Absolutely, yes,” says Mukherjee.“ AI will be contentaware, so it can go a long way in content curation and helping schedulers quickly identify the right content. This may require enhancing existing workflows to AI-assisted ones. Interra Systems is developing technologies for automatic classification and tagging of content using machine learning.”
“ Once broadcasters can acquire all of the sources they need in real-time, they will face a fundamental challenge that only AI will be able to solve: it would be a treasure trove of content but an overwhelming amount of video to manage,” suggest Jacobi.“ Using AI, broadcasters will automatically filter and develop refined levels of metadata to accelerate the curation and programming of all of these new live feeds. Now they’ re able to provide dynamically created, sportspecific, team-specific and athlete-specific live channels, interweaving authentic, hyper-local live coverage, creating a whole new level of tailored viewing experiences.”
“ In theory of course, after you collect the data you must harmonise it,” says Guillemot.“ However, it is very difficult to do, so, in theory it could work but it would take an enormous amount of work. Docherty is another in the‘ Yes, definitely’ camp.“ AI can be used to understand the content better, and provide information about what types of users will be interested in what specific content. It can also be used to determine when this content is most likely to be watched, which can be used to inform scheduling.” LEGACY.“ It certainly could do this,” says Morgan.“ One trend we are finding at the moment is broadcasters looking to monetise archives by making legacy content available over-the-top. There are trends where the young generation are suddenly discovering old programming and AI could certainly help surface other items in a series or similar content.”
“ There is a clear role for AI in mitigating the huge complexity of programming,” states Almond.“ It can take up to 18 months from the inception of a creative idea for a programme to be broadcast, during which time the climate in which the show is being broadcast in may have changed drastically. One way to ensure the content remains relevant is to utilise
AI to help support and make use of complex data analysis to drive better future-looking decisions.”
We should question if we want AI to determine 100 % what we want to watch.” – Petr Peterka,
Verimatrix
“ Equally, AI can help broadcasters make sense of the vast amount of legacy data they already have at their disposal. This data can be analysed and used to predict popular programmes, including when best to broadcast to increase ratings and many other factors that should be considered when making a programme and delivering it to the right audience at the right time.”
It is possible, but broadcasters need to ask themselves the question as to why they want to do this in the first place,” advises Wood.‘ What is the business value? What is the commercial value? Are they adopting AI just to jump on the bandwagon?’”
DEPTH. According to Dawes, one challenge for broadcasters is actually understanding the breadth and depth of their archive.“ In the past, fairly limited metadata was stored with content, and it would be an enormous task to go back and bring that metadata up to today’ s standards by hand. Technologies like TiVo’ s entertainment technology graph— that can automate the production of content metadata— are key to providing an enhanced set of information that can be used to open up the archive and fuel new business models.”
“ AI engines with object and voice recognition already exist to automate the process of tailoring clips to the appropriate distribution methods such as streaming to cell phones, tablets, television and social media channels,” advises Shen.“ The audience and the presentations differ, depending on the content and where it’ s being viewed. Additionally, AI can make this process simpler through creating metadata to archived material that does not contain the granularity of metadata as well as creating data for live video in real-time. Right now, producers hand-craft the multiple versions required for a TV show. In the‘ smart studio’ AI engines will be able to automate the assembly of the material and deliver it in the most effective way to the target audience.” HUMANS. In terms of scheduling, it has been said that humans have nuance, taste and judgement – the qualities of which no algorithm or machine can replace- yet. To what
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