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enerative artificial intelligence (AI) is radically changing video content creation and post production. By leveraging this technology, content creators can unlock greater workflow ef- ficiency, improve video and audio quality, and ultimately drive higher monetization. This article will highlight several ways media companies are utilizing generative AI today, and explore a few of the latest innovations that are helping transform the post industry. Why generative AI is a breakthrough for post production Generative AI is revolutionizing video content creation and post production by dramatically speeding up analysis, au- tomating routine tasks and enabling the rapid creation of new content. With gen AI, an editing job that used to take hours can now be done in just a few minutes. Gen AI frees up creatives from labor-intensive tasks, saving time and money, and enabling them to focus on more essential jobs. Moreover, gen AI lowers the barrier for content creation. Opening the door for an entire new gen- eration of content creators, the adoption of gen AI is helping media companies produce engaging content in a more efficient and streamlined way. How Gen AI is modernizing content creation and post production We can already see several ways that generative AI is fueling better workflow efficiency in the content creation and post production environment. Today, post houses are using AI algorithms to analyze large datasets of video with the goal of identifying patterns in data and making predictions. Utilizing gen AI, editors can automatically pinpoint the most engaging and high-quality shots within a vast library of video footage without having to manually view every clip. Being able to instantly find hidden gems in their video archives is a win-win. It means faster workflows for creatives and production houses, and high-quality and more-relevant content for viewers. AI is also valuable for automating tedious tasks, such as color correction, content tagging, indexing and more. Utilizing AI, post studios can perform these tasks infinitely faster and more accurately. For example, prior to gen AI, content indexing required a human to manually transcribe, describe and summarize content at an average rate of eight hours for every one hour of video. With groundbreaking technology such as Newsbridge's MXT-1 multimodal and gen AI, media companies can index hun- dreds of hours of video per minute, and automatically generate comprehensive descriptions of media assets. Automating the creation of content summaries is beneficial for editors be- cause it allows them to fully understand what content is about without watching it in its entirety. These powerful technolo- gy innovations just scratch the surface of what gen AI can offer for the automation of post production tasks. The technology is constantly evolving, with exciting new workflow efficiencies and capabilities, such as the generation of precise video titles, text descriptions, time-coded chapters and tags to dramatically speed up video publishing. In addition to this, gen AI gives post studios the space to create new content and enhance existing content. By lever- aging deep learning, computer vision and natural language processing techniques, post studios can generate entirely arti- ficial video content, including AI avatars through companies like Synthesia. This was previously very expensive, time-con- suming and only possible utilizing CGI. Gen AI can also be harnessed to seam- lessly transition between multiple images and videos, and create stunning visual effects — as we saw with Runway's cut- ting-edge AI tools in the Oscar-winning action movie, Everything Everywhere All at Once. When original content and stock footage is needed, or video needs to be revised, there is no longer a need to reshoot it, saving considerable costs. Post houses can even streamline their time spent on dubbing thanks to AI voice cloning and localization technologies. This begs the question: will people be able to tell the difference between real and AI-generated content, and how can the industry regulate it? The International Press Telecommunications Council (IPTC) announced that it has standardized different metadata tags to identify the origins of an image, including whether it's been generated by a machine or per- son. Through data mining, the IPTC has created a foundation for tagging content sources and telling machines if the con- tent can be used to train an algorithm. Google is already using an AI-generated self-label based upon technical standards from IPTC. Conclusion We've come a long way since IBM Watson used its natural language processing and machine learning algorithms to analyze the horror movie Morgan and generate a trailer. The video industry is experiencing an AI revolution, and generative AI is already playing a key role. By empowering creatives to swiftly retrieve the most relevant content from their archives and automating various elements of their workflows, AI allows them to maximize their creativity and improve efficiency. GENERATIVE A.I. TRANSFORMS CONTENT CREATION & POST PRODUCTION BY FREDERIC PETITPONT CTO NEWSBRIDGE WWW.NEWSBRIDGE.IO USING A.I. TOOLS TO EXTEND ARTISTS' CAPACITY G ARTIFICIAL INTELLIGENCE www.postmagazine.com 28 POST SEPT/OCT 2023