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Even though AI sounds very intimidating because of our sensationalized exposure to it, it truly isn’t. The technology is simply meant to be employed to logically interpret its surroundings and compute desired results that serve our purpose.
With the given wave in the applicability of AI, it comes as no surprise that the next groundbreaking technology for video production will be artificial intelligence (AI). It is an umbrella term that encompasses Machine Learning (ML), and Natural Language Processing (NLP). Both of them will affect viewing video content, from content formation to distribution immensely. With AI increasingly becoming more prevalent in a variety of areas, it will be extensively used in video production on a larger scale in the not-too-distant future.
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To quote some real-life examples of software that employ AI to improve video production, Conviva’s Video AI Architecture, Google Cloud Video Intelligence, Nvidia DLA, and IBM’s Watson are some of the organizations and new technologies that are making strides in this domain.
There is, however, one area where Artificial intelligence has been truly revolutionary- and that is in live broadcasting. We can now create automated activities, track social media opinion, interpret audio, activate real-time animations, and auto-share thanks to modern technology.
Face identification and monitoring, facial landmarking, pose prediction, and visual speaker detection are among the features extracted from video streams by AI software. The software shows where people are in each frame, in the directions they’re looking at, and when they’re speaking. Some AI face detection and speaker detection algorithms have been programmed to reduce false positives while increasing false negatives. As a result, undetected faces or periods of expression are more common than expected. This, however, is only the case with recent software. As AI grows and evolves, these glitches shall easily be addressed and improved upon
For use of classes, performances, or functions, Natural Language Processing (NLP) helps with automatic live transcription, translation, audio narration, and captioning. Global firms that provide live subtitles for assembly meetings, product unveilings, or global messaging in diverse languages for a global audience will find this very useful. Meanwhile, it also helps people with hearing disabilities enjoy video content despite the physical challenges.
The most recent example of Artificial Intelligence being employed for video editing is when IBM’s Watson had selected footage and made a trailer for a horror film called Morgan. Since Artificial Intelligence can ‘interpret’ visuals, it can be used in almost any kind of editing software, from color calibration to object removal, cinematography, image stabilization, and so much more.
Plenty of the methods currently used in these areas aim to process videos using sophisticated algorithms, which AI could potentially replace. Various systems, such as Sensei platform by Adobe, are also commencing to provide more sophisticated AI-assisted editing software.
Many more types of editing software are beginning to achieve their own AI solutions. In the not-too-distant future, more smart editing applications that use AI to translate and render recordings are predicted to appear.
When executing a video, the Video Intelligence API by Google identifies over 20,000 objects, locations, and behaviors automatically. It can also detect frame transitions and collect detailed metadata even at the shot or frame level. While businesses are becoming more interested in broadcasting, the amount of data produced from video content is at an enormous rate. Information extracted from this data can be used in ways over and above what human beings can individually obtain.
By producing informative identifiers, groups, and synopses automatically, AI can view video streaming and retrieve metadata. More intelligent analytics, content knowledge, and improved data management would be possible as a result, laying the groundwork for efficient video monetization by assigning tailored advertising. Whether it’s a fast-moving soccer match or a more static “speaking face” monologue, the video delivery environment is now looking into something called “content-aware encoding,” in which an Artificial intelligence may study exactly what sort of content is being broadcasted and optimize its bitrate, latency, and protocols appropriately.
When working with live footage, copyright enforcement becomes more difficult. Regulatory bodies are turning to AI to avoid accidental copyright theft of a sports event or a famous song. Training or educational video applications can increasingly be used to examine live footage for copyrighted material, comparable to how Artificial intelligence can enhance content tracking and tag unlawful content.
Higher regulation of all data available, including newly consumed and currently used in the storage unit, is feasible due to the introduction of Artificial intelligence technologies within media management systems, contributing to the improved use of all information and video content available. Users save time and provide quality material for their audience by not producing or editing content that is already accessible.
All in all, Artificial Intelligence has evolved enough to make great advances in the way we create, edit and consume video graphic content. It is not a very distant future where we will be able to automate almost every aspect of video production, streaming, and consumption. With legislators now using AI to understand whether forwarded videos on social media apps are fake or not, it is already being accepted by many governments and courts as convincing evidence in legal cases where a video forms a part of the evidence or is important to the case.
It is truly a great tool that can perform a plethora of different things to make video production easier. With the current pace at which it is going, it shows a lot of potentials to become a very widespread application that gets integrated into every video-shooting or video-editing software in the future. Given its uses in video streaming platforms, it comes as no surprise that AI is now used to do everything from censoring, moderating, as well as editing live video streams, thus making sure the audience gets the most appropriate content they subscribe for.
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