How Artificial Intelligence Is Redefining The Video Industry
In our days defined by technological innovation, the video industry has undergone a profound transformation. AI advantages in video production, such as cost reduction, time-saving, and improved video quality, have completely reimagined this sector and brought new forms of video content. AI can now handle scriptwriting, storyboarding, scene composition, shooting, editing, and even post-production tasks, making it a prominent tool for any sort of video production.
In this article, we will take a closer look at how AI is redefining the video industry and what challenges this technology poses to industry leaders.
Artificial Intelligence Conducting Video Tasks
Digital Distribution
What makes AI a beneficial tool for the video industry is its capability to complete various video tasks, including those for both pre-production and post-production.
Digital distribution is a core aspect of the video industry that will evolve through artificial intelligence. The massive quantity of internet video makes it increasingly difficult to effectively categorize content to ensure it is reasonably easy to find in a search. Once again, the technology is on the cusp of solving this growing concern.
One example comes from a film digitalization platform developed by AI startup Clarifai through a partnership with Vintage Cloud. To automate the process of film content classification and categorization, this platform not only dramatically accelerates the speed at which objects in a movie can be classified but also saves a massive number of human work hours simultaneously.
Film and Video Production
One of the key ways AI has transformed the video industry is through generative AI, which has enabled the automatic creation of videos, making video production faster and more efficient. For instance, AI-powered video editing tools can drastically reduce production times and budget requirements. Filmmakers can use AI solutions to assist in video editing, storyboarding, visual effects, and post-production editing. AI also enhances efficiency by automating repetitive tasks, allowing creative professionals to focus more on their work.
For example, companies like Runway ML provide AI tools powered by models trained on vast amounts of video data, allowing VFX artists to complete tasks that previously took days with professional software. AI can also be used in text-to-video generation, where you can create short videos from text prompts, and in automating aspects of video creation like motion tracking and visual effects. Adobe’s Firefly, another notable example, implements gen AI models within their products, enabling creative professionals to automate time-consuming manual tasks and achieve their creative visions more efficiently. These advancements are changing the landscape of video production and content creation, offering more accessible and efficient tools for filmmakers and content creators.
Editing
One of the primary benefits of AI in the editing process is automating repetitive and time-consuming tasks. For instance, Adobe’s Project Fast Fill demonstrates how AI can quickly and easily remove or add objects and change background elements in videos with simple text prompts. This tool automates tasks that would typically require intensive manual editing, saving video editors valuable time.
AI also helps streamline the editing process by identifying and selecting the best footage based on composition, lighting, and focus. This automated selection process reduces the time and effort required for editors to sift through large amounts of footage. AI extends its capabilities beyond traditional video editing by optimizing elements like color grading and sound design. By analyzing video footage and applying pre-programmed rules or machine learning algorithms, AI can enhance the final video product’s overall quality and consistency. This now allows video editors to rely on AI to perform certain tasks more efficiently, allowing them to concentrate on their creative work.
Another example is CapCut for Business, which offers AI-powered tools for advertisers and content creators, including an AI-powered script generator, thousands of business templates, and the ability to generate video presenters using AI without extensive manual editing.
Dubbing and Voiceover
AI can now also be in charge of dubbing and voiceovers, offering creators and businesses efficient and cost-effective solutions for reaching wider audiences and enhancing video content. YouTube’s Aloud is a prime example of AI-driven dubbing technology. This tool automatically dubs videos, translates their content into multiple languages using synthetic voices, and generates a transcription of a video’s audio, which creators can edit. Yet, some dubbing firms and language service providers that offer human-based dubbing services argue that human translation and voiceovers remain crucial for maintaining brand quality and authenticity.
Besides, AI-driven solutions powered by text-to-speech software, machine learning algorithms, and natural language processing (NLP) have emerged as powerful tools for video production in terms of voiceovers. AI-generated voiceovers offer incredible benefits like speed, customization, and consistency, and they can be created in a matter of minutes, a process that typically takes much longer with human voice recordings. By leveraging AI technology, creators can customize voices, accents, and various parameters such as pitch, volume, and speed to align with their video content’s specific style and tone. Moreover, AI-generated voiceovers maintain a natural tone, consistent pace, and accurate pronunciation, ensuring professionalism and viewer engagement.
While AI-generated voiceovers are highly efficient, they have their limitations. Unlike human voice actors, AI may struggle to understand the flow and intention of the script, making it less adaptable to nuanced changes. At times, AI-generated voices may sound less human and more robotic. Despite these limitations, AI has the potential to significantly enhance the quality of voiceovers in video production with its varied options for creators.
Video Upscaling
Video upscaling with AI is basically the process of enlarging and enhancing video footage. Traditional upscaling methods typically result in larger but blurry images of lower quality. The challenge for video upscalers is to make the pictures look realistic and, ideally, clearer than before.
AI upscaling uses trained models and collected data to recognize patterns in images and videos. Like in Adobe’s Project ResUp, these algorithms are trained on low-resolution and high-resolution image pairs. The AI learns how to go from low-res to high-res by recognizing patterns, textures, and details, resulting in more vivid and detailed upscaled videos. AI algorithms are self-improving and become more efficient with each processing task.
Another example is TensorPix, an online video upscaling tool that utilizes AI algorithms to refresh low-grade or outdated videos. It offers various AI filters for color restoration, noise reduction, film scratches, and dirt reduction. TensorPix is a practical tool for enhancing older cartoon recordings, making them appear more vibrant and clear. The tool’s AI upscaling effects, like the 200% AI Upscale and 400% AI Upscale, are designed to provide different levels of enhancement for videos depending on their resolution.
Saving Time on Video Content and Metadata Management
Artificial intelligence technology can complete tasks in a minuscule fraction of the time required for a person. This statement is particularly relevant regarding the extensive job of tagging and cataloging video content. Using advanced intelligent tools in combination with manual processes, metadata can not only be entered at a much quicker pace but also auto-tagged using Object Recognition and Face/Location Recognition technologies, enhancing metadata to increase the power of content discovery. The overall tasks involved in video content management can be greatly assisted with AI technology, and while people are still required for much of the decision-making, automation tools can save enormous amounts of time and strengthen accuracy.
Analytics
Analytics tools, combined with AI capabilities, allow businesses to gain a deeper understanding of their audience and enhance video marketing strategies. AI can track viewer engagement by analyzing behavior like watch duration and content skipping patterns. This data can then be used to segment and target audiences based on demographics, interests, and preferences, helping businesses tailor their content to suitable viewers. Also, AI-driven analytics tools can identify areas for content improvement, suggest changes to titles, keywords, and descriptions based on click-through and conversion rates, and even predict the likely outcomes of video marketing strategies.
Immersive and Interactive Storytelling
From cinematography to authoring tools for non-experts, AI contributes to creating engaging narratives and sensor-based storytelling for immersive experiences. One of its remarkable features is searching archives to find content that best complements the storyline, ensuring a seamless and compelling narrative flow. AI-driven audio segmentation and multimodal interactive experiences open up possibilities for creating virtual worlds where users can actively participate in the storytelling process.
AI also enables the development of personalized and dynamic immersive experiences through virtual and augmented reality technologies. With AI-powered chatbots crafting customized storylines based on user interactions and AI-generated music and sound effects enhancing the ambiance, interactive storytelling becomes more engaging and tailored to individual preferences.
Enhancing Live Broadcasting
Advancements in facial recognition technology and real-time analytics enable broadcasters to personalize their content for specific viewer demographics. AI-powered cameras can detect the emotions of the audience, enabling real-time content adjustments that cater to their preferences and responses. AI-generated graphics also offer the capability to provide real-time data visualization, enhancing the delivery of information during live broadcasts. These AI-driven features are set to redefine the live broadcasting experience, creating more interactive and engaging content for a diverse range of viewers.
Can AI Truly Improve the Industry?
As artificial intelligence increasingly intertwines with many aspects of video production and distribution, some question the value of this technology while raising concerns about the potential loss of the things that make our industry unique.
Here is an example: ScriptBook is an AI company seeking to change how movies are greenlit. This controversial software analyzes screenplays in several ways to determine factors that include its rating, target audience, and predicted box office gross. The idea is to reduce the risk involved in approving films by using AI to predict the success of a project before a studio agrees to move forward.
While this technology carries the potential to decrease the number of films that are surprisingly disappointing regarding revenue, there is also the possibility it will prevent the creation of movies that break radically new ground artistically, whereas human decision-makers may be capable of seeing this potential and taking the necessary risks to bring monumental films to fruition.
At the same time, when it comes to the filming, editing, and distribution processes, AI and ML can save massive amounts of human resources, thereby reducing the budgets required for making feature-length films and television shows without any loss of value. As is the case in every industry, resistance to new technology exists whether it is valid or not, and over time, we expect to see an increasing number of tasks being either entirely conducted or at least assisted by AI-driven tools.
Challenges and Goals
One of the many challenges when applying AI is the question of accountability. In other words, if things go awry, who is responsible? It is very early in the game, and the necessary regulations are not in place yet. However, work on these problems is certainly progressing, and the hope is that clear and comprehensive governance will be commonplace in the not-too-distant future.
Ethical and moral issues arise with AI-generated content, especially if it facilitates deepfake videos or misinformation dissemination, potentially causing harm and damage to individuals. Unpredictable results due to AI systems potentially propagating biases and unintended messages are also significant concerns.
Navigating the complex terrain of copyright and ownership for content produced by AI systems poses even more challenges. Issues related to the similarity of AI-generated content to existing works, risking accusations of plagiarism or copyright infringement, bring the importance of distinguishing originality in AI-generated content to the forefront. Balancing human-machine collaboration is another critical challenge, ensuring that AI complements human creativity without overshadowing it, thereby preserving the creative process’s integrity. Lastly, resistance to change among industry professionals, stemming from fears of job displacement and concerns about the authenticity of AI-generated content, presents a considerable obstacle to the widespread adoption of AI in filmmaking.
Additionally, fears about the potential loss of jobs to automated solutions are rampant throughout our communities as a growing number of sectors work toward providing services and products that require a decreasing amount of human labor. However, many experts believe that the opposite is true.
Final Thoughts
The integration of artificial intelligence into the film and video production industry is ushering in a transformative era. From automating repetitive tasks and enhancing editing capabilities to upscaling video quality and offering dynamic, immersive storytelling, AI-driven technologies are empowering the video industry with new tools and capabilities. Striking a balance between human creativity and AI assistance while addressing these challenges is pivotal for the industry’s continued growth and success in this AI-driven future. As AI technologies continue to evolve, video industry leaders will need to embrace the opportunities they offer while preserving the essence of human creativity that makes video-making unique and compelling.
Learn more about how DataArt can help you adopt and implement AI technology, enabling you to build solutions that keep you on the leading edge. Explore our Video expertise page and uncover the potential of next-generation solutions in this exciting domain.
Author: Max Kalmykov
Vice President of Media and Entertainment Practice at DataArt
Originally published on https://www.dataart.com/blog.