Opinions

Home Opinions

How AI can empower broadcasters in the changing media landscape

It became clear from this year’s EBU Production Technology Seminar (EBU PTS 2019) in Geneva that broadcasters are slowly adopting AI technology in their day-to-day operations. Several broadcasters presented their experiences with AI, but it was clear that not everyone is aware of the added value artificial intelligence delivers. This article explores four different areas where AI can benefit broadcasters: producing content, improving content accessibility, enabling advanced advertising opportunities and improving viewing experiences.

Five ways to use location data

Five ways to use location data Location data helps studios and content owners meet geographic rights requirements that carry punishing penalties for breaches. IP address translation services, which show where a device is, do not have the pinpoint accuracy of GPS but can achieve almost the same results for service providers or operators, who may well be working at country or city level. IP address translation delivers other benefits including controlling service access, so consumers do not waste time signing up to something they are not entitled to receive. It means you can stop showing them content in a catalogue that is off limits where they live. It can also be used to present local offers.

AR: the next big thing or just a gimmick?

The success of AR in television will stem from augmenting main-screen video with additional metadata and video information, which can be displayed in AR either in a headset or through a second screen experience. One exciting use-case is sports, since fans love data and that data is readily available. Some sports are especially well suited for AR, if they are dispersed over a large area, like in a motor race. It is impossible to view the entire action at once, so being able to choose additional information or viewpoints is a real consumer value-add.

Super-aggregators: the new ‘Pay TV heroes’

Consumers have unlimited content choice but may reach a point when they have had enough of fragmentation across multiple streaming services. There must be some re-bundling. Key responsibilities for a Pay TV super-aggregator include low-touch onboarding of new content and providing a bridge between content silos. They must provide an elegant, data-driven approach to personalised content discovery.

New decade, new codec

The TV industry is once again seeking new codecs to boost video compression efficiency. A successor to HEVC is under active development: VVC (Versatile Video Coding). This standard is due for completion in October 2020 and is likely be approved as H.266 (VVC), but the licensing model is currently unclear. Meanwhile, AV1 is regarded as the natural successor to VP9, though questions remain over adoption beyond the largest SVOD providers.

Always look at the bright side of life: getting in a good mood by...

Companies such as Google see their smart speakers more as computing devices that live in a shared environment than as personal devices. A happy home will need a multi-modal approach that includes remote control button-based voice interaction, as well as standard remote control input. Today’s popular smart speakers focus on what the user is saying rather than how the user is talking to the device: recognising emotion could be the next step in personalising experiences. Button-based voice control is a less obtrusive approach to emotion recognition and customisation.

“OK, Google, what’s the latest on Brexit?” – Enabling smart in-video search with...

Imagine asking your TV, tablet or smartphone for the latest on Brexit and being offered a series of broadcast-quality video clips in response. The TV operator environment would be like a search engine – and it can find your favourite celebrity, catch-phrase or pop culture topic, too. This is possible where an AI ‘reads’ faces, speech, objects, logos, on-screen text and subtitles. The engine understands what video is about and what is relevant to you. It can find, cut and present the content it finds as a series of short clips. A voice assistant becomes a natural way to find content.

How is AI technology impacting video compression?

While significant efficiencies are enabled in software-based video compression, machine learning and artificial intelligence are being used to further optimise video delivery. AI systems can fine-tune algorithms to particular needs - like face detection or dark scene processing - faster. ML and AI improve encoder density. Codec evolutions can be tested more quickly, allowing operators to experiment with new business models. There is much more scope for customisation. This article explores the implementation scenarios for AI/ML in video compression.

Best practices for targeted advertising: success factors for TV operations in the GDPR era

With advertising revenues under pressure, TV channels see targeted advertising as an exciting new opportunity. According to eMarketer, by 2019, personalized advertising spending will...

Why social reach has become the top priority for OTT platforms

Younger demographics are now far more likely to be influenced by social media and act on the recommendations of friends when deciding what TV to watch. In order for OTT platforms to grow, their content must be highly visible, accessible and sharable. Social content reach will be the most important factor in winning market share. The key challenge is positioning your social channels as the ‘go-to’ place for your target audience and delivering complementary content in ‘real-time’. This article summarises what you need to think about.

Most Popular

Processing...
Thank you! Your subscription has been confirmed. You'll hear from us soon.
Sign up to receive the weekly Videonet newsletter
ErrorHere