Your Best Production Assistant Could Soon Be An Algorithm

FKT Magazin 7/2018

As studio content creation and live production continues to get more demanding and complex, producers are finding that having a reliable, fast and efficient assistant is invaluable… even if that assistantis actually a series of Artificial Intelligence (AI) and machine learning software algorithms.

Most people are extremely familiar with this type of technology and use it regularly, without even realizing it. For example, Google Translate or geolocation searches via Apple Maps. These commonly used resources involve a type of machine learning to complete a single-problem task like “translate this.” Often called neural networks and machine learning, AI is being applied to solve the most difficult challenges in media production and distribution by “learning” from a large set of data. The technology can help an editor find a single clip amongst of storage arrays holding petabytes of information in mere seconds. It can automatically calibrate or learn a studio environment or field of play and instruct devices to react accordingly. And it can execute AI-powered image framing, highlights creation, graphics insertion and even serve as a virtual program director.

AI solutions bring the promise of simplifying and enhancing everything from systems to processes, in turn cutting the costs of production, speeding upcontent syndication and significantly reducing the amount of man hours required for some of the most labor-intensive tasks. In some cases a full production crew will no longer be necessary to produce a live multi-camera production. This is called At-Home or REMI (remote-integration model) operations and it’s being implemented more and more every day for many of the largest sporting events around the world. It’s become clear that AI in the media production space is here to stay. Product engineers and marketers are now looking to bring these streamlined capabilities to mid-level projects—where budgets and resources are limited—by enabling systems to replicate human decision making and even make it faster and more accurate and able to understand and naturally adjust to unpredictable occurrences during a live production. Recognizing this, a multitude of broadcast equipment vendors are touting AI features and capabilities in their products and systems in order to help users perform tasks not humanly possible.

For example:

- EVS engineers have been hard at work to develop different types of intelligence into its portfolio of live production products (servers, routers and production switchers). The idea, they say, is not to replace people with machines, but to help humans do their job better (e.g., faster and more efficiently).

As a result, setup time is significantly reduced and operators can, for example,easily place graphics onto the calibrated field with the highest level of precision to aid their decision-making process.

- A robotics company called Telemetrics has added AI to a new roving pedestal to avoid physical obstructions and for Automatic Shot Correction technology as part of its RCCP remote camera control panels to augment studio automation systems. The AI-powered reFrame technology helps users of automated news studios overcome unpredictable occurrences in the studio—like the talent slightly moving out of frame or an ill-positioned over-the-shoulder graphic or two-shot— and make quick adjustments automatically, on the fly.

- An online video processing company called Bitmovin demonstrated AI-powered encoding, claiming to dramatically speed up processing and enable service providers to deliver significant improvements in video quality. This AI-powered encoding technology works by continuously learning the parameters used in previous encodes, so that it can apply AI-optimized settings to every new video file. By enriching its containerized encoding software (which enables video to be split into chunks formore efficient encoding) with machine learning capabilities, Bitmovin is able to achieve both faster processing times and significantly higher quality with no increase in bandwidth.

- Tedial, a supplier of media asset management systems, has developed Smart Live, a live event support tool that leverages AI algorithms tools to increase the number of highlights created automatically, thus reducing production costs and boosting revenues for production companies. Smart Livei ncludes an automatic highlight creation feature that is tightly integrated with AI engines. Smart Live ingests a data feed and automatically creates an event inside its metadata engine. Simultaneously, it generates corresponding log sheets, the player grids and a schedule of the event. All these preparations are linked and organized by collections, so an entire season of sports events can be prepared automatically in advance.

During events, live data is ingested and the system can be configured to automatically create clips based on actions, keywords or logged occurrences. Smart Live automatically pushes content to AI engines, facilitating fast and reliable video and audio recognition to generate additional locator data and annotate media proxies. The systems can also automatically publish clips or push content to social media platforms. An internal metadata engine can be configured to create an automatic metadata ingest process, addressing more demanding and the more complex sport workflows.

- Veritone has developed a suite of cloud-based software tools it calls aiWARE that uses a proprietary, machine-learning orchestration layer (“Conductor”). Serving as a search engine aggregator, the software not only employs multiple AI engines at once, but it also chooses the best-available engine or engines spread out across the globe. Using natural language processing, aiWARE can predict the accuracy of each transcription engine based on the characteristics of the media being processed. Conductor then automatically selects the best engine to process that file. The newest version of Conductor under development can identify the best engine for each portion of a file, applying multiple engines when needed to fill accuracy gaps.

As broadcasters and production companies seek to maximize their available resources, AI will continue to play an increasingly important role. It’s the best (fastest, most accurate) production assistant a crew could ask for.

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