How do AI and MAM provide improved live sports production?

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SCREEN AFRICA EXCLUSIVE: Everyone is talking about Artificial Intelligence (AI). This disruptive technology has entered an unprecedented stage of development and is imposing itself in our daily lives at a pace that surprises, fascinates and sometimes frightens. AI is a hot topic with inspiring and practical use cases emerging every day.

According to recently published IABM data, AI adoption in broadcast and media is still at an early stage. Only 8 per cent of media technology buyers said they had adopted AI before last year's IBC; 36 per cent said they were unlikely to adopt it in the next two to three years; and 56 per cent said they were likely to adopt it in the next two to three years.

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As we can see the broadcast and media industry is on an adoption curve. However, there is no doubt that AI will change the media landscape while providing enhanced viewing and increased opportunities for monetisation. Vendors need to consider how they add value for their customers and ensure that AI's not just another similar solution.

With all this AI news swirling around it's no surprise that this year, the industry buzzword will continue to be AI. For media asset management providers AI could be a game changer, in a recent IABM report, MAM was specified as the fourth most important priority for buyers.

The attractiveness of AI for broadcasters is the efficiency of using computers to understand audience demands, the management of data and filtering of content for specific themes, as well as creating more, original and personalised content for increased viewer and fan engagement to reduce production costs and increase monetisation.

AI and machine learning will be leveraged by industry leaders to extend their products. Recent industry news coverage has shown that a series of different applications are on track to be introduced. Many of these will focus on specific applications but most will fall into the categories of increased metadata generation and application, media augmentation and annotation, or machine learning applied to workflow operations to further automation.

The increase of sports rights due to the arrival of new comers to the digital economy such as Amazon, Facebook and Twitter are a new challenge for broadcasters who need to reduce their production costs to maintain their profitability.

So how do media companies add value for their customers and ensure that AI's not a me too solution? The answer is technology investment that efficiently automates common, repetitive tasks. Automation tools with AI will help production teams to produce more content and personalised content that allows media companies to gain more fans, viewer engagement and increased revenues.

Sport production is demanding, it's about live content and speed. This is a good example of where AI combined with MAM can help media companies to face today's challenges.

Assembling sports highlights is a prime example, broadcasters can automatically pre-configure events in the MAM to drastically reduce preparation time and avoid human errors. The question is, how do MAM providers create sophisticated AI options for broadcasters and media companies that enable these efficiencies? An AI powered metadata engine to fully automate in-game production is key.

During the live game, the programme feed is passed through a computer vision AI engine and a speech-to-text AI engine, which provide additional metadata and contextual information about the game to augment media logs.

Combined, these different technologies enable automatic logging of a live event and generation of event logs during the game. This supports Tier2 federations or smaller broadcasters and clubs who do not have funds to buy the service of an external data provider. It also allows companies still manually logging the game to optimise their resources.

AI will also assist in automatic content tagging, which is traditionally a labour heavy and expensive process. Enhanced MAM Search capability opens the door to more content creation, thereby increasing monetisation opportunities.

Together, these technologies enable automatic highlights creation with the best IN and OUT point calculated by the AI engines. Clips and EDLs are automatically created and automatically published to social networks, efficiently increasing the amount of content created with the same staff. Tightly integrated with AI tools, an advanced MAM can automatically generate an increased number of highlight clips during or after an event and deliver this advanced storytelling to a very targeted audience increasing the potential for significant growth in fan engagement while reducing production costs.

Fans are requesting more and more personalised content to be consumed anywhere, anytime on any device. Using AI to analyse hit rates on social networks and make suggestions for search engines to provide better results to producers will allow them to create tailored content. This means more opportunities for fans accessing enriched content on their preferred social platform, increasing engagement and driving more revenues from ads or sponsors.

As sports moves towards increased data in every aspect of the game (players, tracking, game data), AI will enable content to be captured and analysed and will allow enriched data to be automatically added thanks to a powerful data analytics engine.

Finally, AI can be used to increase workflow efficiency by analysing processes and predicting failures within a process. Connected to a Business Process Manager, AI can learn from errors in workflows and improve processes, minimising errors in the future and increasing efficiency.

Properly focused and applied AI helps modern broadcasters effectively reduce production costs while increasing revenue, enabling them to cope with the n

LINK:	http://www.screenafrica.com/2018/04/25/technology/storage-asset-manage...
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