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Predictions for 2019

09/01/2019

Throughout 2018, several trends dominated headlines. It's my belief that 2019 will see many of these remain centre stage, but there's no doubt that exciting changes are on the horizon in the video industries. The cloud has been growing throughout the year, despite a hesitance from some to get on board. Sadly, several misconceptions surrounding what it takes to implement a cloud strategy have held it back, and prevented many from benefiting from its flexibility.

AI has also been a huge buzzword this year, especially at numerous tradeshows where it was a common panel topic. There are still concerns surrounding the accuracy of current AI iterations and what it can really enable, but that looks set to change. On the whole, the video industry has been experiencing a time of disruption. Emerging technologies have been introducing opportunities to enhance the video experience, but it has been obvious in 2018 that they also bring their own distinct challenges.

Here's our take on what 2019 will bring.

Trend 1. Investment in the cloud will continue Despite some remaining wary, organisations look set to continue to increase their investment in the cloud in 2019, as early adopters begin to reap the benefits. Not only are they seeing that the cloud makes them much more agile and flexible, but they are also seeing the cost-savings of the cloud.

More solutions will become established in the cloud than ever before over the next year, or at least come to adopt some kind of cloud component. As an increasing amount of every workflow become more cloud-based, it will make sense for other areas to do to the same, to create one unified, seamless workflow. This is also likely to increase the rate of adoption as those cynical of the cloud come to realise that it is somewhat unavoidable.

Most of the push back we have seen from potential migrators has centred around several misconceptions. The first is usually security and a belief that the cloud is more hackable' than on-premise infrastructures. Of course, this isn't necessarily true, and in actuality, public cloud providers have some of the toughest cybersecurity measures in place. Google Cloud, for example, offers its own Cloud Data Loss Prevention API (CDLP API), which automatically discovers and redacts sensitive data.

On-premise will still remain important throughout 2019 and ahead, especially as it's unlikely that some video businesses will be able to move to a fully cloud environment for at least the next few years. For most companies, keeping petabytes of video assets in the cloud is still not relevant. Instead, what will become more prevalent is a hybrid cloud, whereby the logic (the mothership) and some of the workflows are migrated to the cloud and some remain on-premise - basically the best of both worlds.

For one, hybrid offers the option to store low-resolution representations of assets in the cloud, for browsing and collaborating, and high-resolution assets globally distributed either on-premise or in the cloud. These scenarios are much easier to implement, given that hybrid solutions can be deployed in stages, and means that investments in existing workflows don't become redundant. This is most definitely a trend we're likely to see grow in 2019.

Trend 2. AI will enable more in content production In the past, customers have told us that for every hour of content, they spend an additional three capturing and entering metadata for that asset. Artificial intelligence in content production, management and distribution already has the potential to save creative people hours in manual, time-intensive tasks such as entering metadata. But in the next couple of years, it looks set to go beyond even this.

We could begin to see AI being used to analyse entire chains, from supply to delivery, using feedback to automatically optimise systems. For example, one use case is utilising AI to evaluate dramatic events in a series, or the performance of a sports team, and then based on these events suggest content to viewers or assist in the creation of new content. This could have exciting implications in Video-On-Demand (VOD) where we are likely to see more broadcasters starting to use the first semblance of this over the course of the coming year.

The next step is automated scripting/storyboarding whereby the AI could, for example, identify the best selection of scenes in a specific movie to be used in the creation of a trailer. Following that, it will be interesting to see how much progress the industry makes in automated content production using AI. Although still a way off, this involves using data to actually create content, perhaps personalised to individual viewers or for two separate, culturally-different regions.

For the foreseeable future, AI will continue to require human interaction, particularly when it comes to accuracy. In automated distribution, for example, an actor could suddenly become more popular or be mentioned in the news. The AI may be programmed to push content to a VOD system automatically, judging that viewers will be interested in this actor. However, it's difficult for an AI to distinguish between popularity and infamy, so if an actor was mentioned in the news for an unfavourable event, such as drunk driving, then the content provider would need to reject this suggestion.

Sentiment analysis is on the horizon, with some AI's already capable of determining if footage is happy or sad. Developments in this area could see AI technology capable of calling up all footage/content in which Queen Elizabeth or President Trump appears looking happy or sad.

On a larger scale, AI-technology could, in the future, also present different types of video assets depending on the mood of the user base, i.e. by determining if the broader audience is happy or sad. Although this is still in its infancy, studie
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