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How Artificial Intelligence is Transforming the Video Industry

Artificial intelligence is revolutionizing the video streaming industry. Explore how AI technology can increase video workflow efficiencies.
August 30, 2023
5-Minute Read
Senior Manager, OTT & IPTV Solutions

There is a buzz around artificial intelligence (AI) technology today. Almost every industry is adopting AI. For video streaming, AI is empowering service providers to enhance video quality, reduce piracy, create rich metadata, personalize content and more. Nearly every streaming provider is implementing AI in their core business functions. 

Let’s take a moment to go back to the fundamentals of AI and dive deeper into AI’s role in video streaming. 

What is artificial intelligence (AI)? 

AI refers to the machines and systems that perform tasks that usually require human intelligence. It uses machine learning (ML) to model or even improve upon the capabilities of the human mind. 

AI ingests massive amounts of labeled training data, analyzing the data for correlations and patterns and using these patterns to make predictions about future states. Popular applications of AI include automation, natural language processing, speech recognition, and machine vision. 

AI and ML are not the same

Artificial intelligence (AI) and machine learning (ML) are often used interchangeably. But they are two different concepts. ML is a subset of AI. 

AI is computer software that simulates how humans think to perform complex tasks, such as analyzing, reasoning, and learning. ML is a subset of AI that uses data-trained algorithms to produce models for performing complex tasks. The majority of AI today uses ML. 


AI has been rapidly evolving

It is interesting to observe AI’s evolution over the years. At first, humans created algorithms, such as decision-tree algorithms, that could produce complex data correlations.

Deep-learning algorithms were next to be created. This algorithm uses neural networks that try to mimic the human biological neuronal system and brain. The research in deep-learning algorithms was highly productive in the last decade with variants called auto-encoders, generative adversarial networks, etc. Deep-learning algorithm research demonstrated spectacular improvements in image and video restoration, super-resolution, and image and video manipulation. 

Recently, there was a breakthrough in deep-learning algorithms with generative AI models, like OpenAI GPT and Bard by Google. 

Ushering the new era of generative AI

Generative AI has been gaining immense popularity recently. It is an AI model that can generate text, images, audio, and video by predicting the next word or pixel. Generative AI currently relies on Large Language Models (LLMs) characterized by emergent abilities, i.e., the ability to perform tasks that were not included in their training examples.

The transformational architecture of these new neural networks has been a key advancement. There have been spectacular improvements in understanding and generating human languages. The most recent developments include generative image and video, apart from text and speech in multimodal training.

Generative AI is crucial for the media and entertainment (M&E) industry – enabling more efficient content creation, rapid experimentation, and improved understanding of viewer behaviors and expectations. Content providers can now create content faster and more efficiently. 

Let’s explore AI’s influence, particularly on the video streaming landscape. 

AI’s impact on the video industry

The AI for video production market is expected to grow at a CAGR of 22.37% from $362.500 million in 2021 to $1.489 billion by 2028, according to Research and Markets. The upside to leveraging the power of machines for video streaming is that you can process a massive amount of information faster than usual.

AI is particularly good at repetitive, detail-oriented tasks, such as analyzing large datasets with a high degree of accuracy and efficiency. Video content providers are reaping many benefits from using AI, including:

Localizing content: The key to reaching global audiences and growing your business footprint is localizing content. With AI-driven technology, content providers can speed up the process of capturing, translating, and uploading subtitles. You can even use AI to translate social media posts, chat responses, catalog info, and more. However, it’s a good idea to hire industry experts to guide video localization.

Tackling piracy: AI-powered solutions can enable content providers to keep video content secure. Using AI solutions, you can quickly identify pirated streams and take them down. AI is also beneficial for watermarking purposes. You can extract the digital watermarks of pirated content and block users who are abusing the service, protecting your precious revenue streams.

Improving video quality: Traditionally, video service providers have applied the same type of encoding to all content. However, with AI-driven encoding, service providers can automatically adjust the settings depending on the type of content to improve compression efficiency. AI-powered encoding solutions reduce video streaming costs and improve the quality of the viewing experience by reducing buffering and enhancing image quality.

Auto-analysis: AI algorithms can automatically analyze content and streamline some tasks in the video workflow. Content providers can use AI-driven solutions for generating metadata, tagging, creating descriptions, and more by identifying actors, directors, genres, and other details. Ultimately, AI simplifies the content search for end users. 

Personalizing content: By analyzing content with AI-enabled solutions, service providers can identify patterns, similarities, and relationships between different types of content. The result is better content recommendations and increased viewer satisfaction. 

There is no better time than now to implement AI solutions into your video workflows. Let’s explore how you can achieve that. 

Watermarking Technology in Video Streaming

Five approaches to optimize video workflows using AI

The key to understanding how to best use AI in video workflows is knowing when and where to implement it in the video workflow stages. There are various ways to implement AI in a video streaming workflow, including: 

Content-aware encoding: In the next-generation content-aware encoding process, AI understands what kind of content is being streamed and then optimizes the bitrate, latency, and protocols. This process enhances image quality while reducing data storage and transfer costs. Users benefit from reduced buffering times and consistent image quality across various video streaming devices.

Advanced content-aware encoding technology enables high compression with advanced video coding (AVC) and high-efficiency video coding (HEVC) codecs. Such technology enables service providers to reduce storage and CDN requirements decreasing overall costs and buffering time while improving quality. The groundbreaking AI optimization for real-time video compression enables the streaming of live video channels at significantly lower bit rates while delivering exceptional quality of experience (QoE).

Automated scheduling: Scheduling is one of the most significant challenges in streaming video, particularly for free ad-supported streaming TV (FAST) channels. In many cases, FAST channels are designed to repurpose and monetize an existing catalog of content into linear channels that can be distributed on any platform. To minimize the cost of operation of these channels, video content providers need to be able to create schedules quickly and offer groundbreaking targeting.

Leveraging AI-driven solutions, content providers can automatically generate entire thematic channels from a VOD library and identify appropriate break-points for advertising. AI also aids with personalizing channels to individual users or a qualified cluster of users.

With AI-powered technology, content providers can automatically create playlists based on content themes, targeted demographics, and maximum ad inventory per hour. AI-driven solutions can quickly identify and schedule relevant assets into a FAST channel. This results in an increase in operational efficiencies and a boost in revenues.

Programmed clip extraction: Having the ability to quickly extract short video clips and highlights from long-form video is critical, especially for live sports streaming. With AI-enabled solutions, content providers can automatically create the best video scenes and highlights. AI clip extraction saves time and enables content providers to create clips with the highest potential to drive viewer engagement based on analytics.

AI-driven solutions analyze live sports content in real-time based on AI algorithms. Content providers can automatically create highlights and drive viewer engagement. 

Automated video-on-demand asset (VOD) segmentation: AI is also empowering video service providers to easily segment video-on-demand (VOD) assets. Before, this was a manual process that could be time-consuming. With AI-enabled solutions, service providers can quickly identify the most accurate place for advertising in a VOD asset. You can automatically create ad inventory while ensuring a smooth experience for viewers.

Dynamic brand insertion (DBI): Targeted advertising has become a growing source of monetization for video service providers, with an estimated billions of dollars of projected ad spend. Dynamic brand insertion is a type of targeted advertising wherein video content service providers virtually insert a product within video content to monetize content. Products are inserted into the content seamlessly so that it isn’t distracting to viewers.

Service providers are using dynamic brand insertion solutions to enable individual targetability at a massive scale. With AI-driven technology, service providers can insert products into video streaming services with frame accuracy, making in-content advertising a highly targeted and scalable ad format. 

AI-augmented video streaming is the future

AI is transformational for the video streaming industry. With AI-driven technology, service providers can unleash new workflow efficiencies, improve video quality, personalize content, fight piracy, and reduce costs. By embracing recent AI advancements like content-aware encoding, and dynamic brand insertion, you can elevate your video streaming service to boost viewer engagement and monetization. 

Harmonic is leading the way for AI innovation in video streaming with its VOS®360 Media SaaS and Harmonic's VOS®360 Ad through our partnerships across the video streaming ecosystem. To find out more about how our solutions can help you, contact us today. 

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