AI in post-production: What’s the best take?
Opinion piece by André Kamps, CEO at ELEMENTS
When it comes to AI post-production, people’s emotions range from deep concerns that fully autonomous, self-improving AI may affect the human workforce negatively, to great enthusiasm about AI as an exciting new tool with a lot of potential to push the limits.
The big question is: How to deploy Artificial Intelligence-based technologies particularly in post-production?
We all know: Artificial intelligence is changing almost every aspect of modern life today, and the media and entertainment industry is no exception. For the TV business and home entertainment providers like Netflix, for instance, AI is already providing noticeable benefits, as both advertising and content can be presented in a tailored fashion to the audience, increasing revenue due to an unprecedentedly customized and targeted approach. But Artificial intelligence (AI) and machine learning (ML) technologies will inevitably also transform the way we handle post-production tasks. But how can specifically post-production facilities deploy AI – and actually benefit from it?
AI to boost efficiency and productivity
Aside from highly ambitious attempts to let AI take over script writing or editing tasks, for example, there are ways to usher in the new era – and leverage the power of AI purposefully and successfully.
One rather tedious, yet utterly important and helpful task in post-production is, without a doubt, the tagging of media assets in your media asset management (MAM) system. Adding “intelligent” metadata (yes, pun intended) to the footage used to require hours and hours of manual work, and at the end of the day you still couldn’t be certain that all relevant descriptive data was attached properly.
AI can easily execute this task, probably in a much more diversified fashion than any human being, but definitely a lot faster than any human being could ever do it. If analyzing and tagging of an entire day of footage takes only minutes instead of multiple hours, while providing even more valuable in-depth information compared to the human attempt, both efficiency and productivity are increased significantly. This boost in capability will have a positive impact on the post-production of the entire project, as the enhanced searchability of the media assets
Another daunting task is the preparation of transcripts. With the right AI engine, transcripts can be performed automatically – and even be translated into a multitude of other languages, almost simultaneously. The benefits are obvious: Subtitling becomes a breeze with AI, even in different languages.
While we at ELEMENTS always strive to design our media storage solutions with easy-to-use features for workflow automation, AI can increase the productivity by decreasing the manual effort in other ways. After careful consideration we have decided to partner up with Veritone®, and enabled aiWare to work seamlessly on all our appliances. With a simple mouse-click, media assets are automatically analyzed for objects, words, faces, brands and many more parameters without diminishing the hardware performance. The analyzed data will appear and tied to the correct asset.
While AI is still in its infancy, and we expect many more purposeful applications to come around over time, AI can already make a big difference today – especially when it comes to media asset management. In a fast-pace environment such as post-production, human beings don’t have to bother with crunching the data anymore – but can use their precious time elsewhere. Designed to perform extremely tedious and time consuming tasks, AI gets the job done faster and probably better than any human, increasing efficiency and usability significantly.
Keep in mind though: When deploying AI for your media asset management be prepared to spend some time “teaching” your AI application what you need. Because that’s where the ML (machine leaning) comes into play.