Latest Tech Advancements in Video Streaming and AI

Posted By : Priyansha Singh | 10-Mar-2022


Video Streaming and AI: Top Tech Innovations


Artificial Intelligence (AI) is massively shaking up all the grounds of broadcasting and video streaming capabilities in the media and entertainment industry. Video streaming companies of all shapes and sizes are diligently hustling to implement AI services that hold the potential to distinguish their administrations from the rest. The technological advancements and innovations have been broad and the estimations, predictions, and investments are in billions. Artificial intelligence and machine learning are some of the main segments that are enabling businesses to identify their customers and realize their viewing requirements. By recognizing user demands and needs, businesses can raid into the region of personalization and from there, the concept of substance branding begins. Customizations of products and services are getting to be table stakes in order to remain pertinent in this competitive industry segment.


In this blog, we will uncover various tech advancements and trends that present innumerable opportunities in relation to video streaming and the implementation of AI.

OTT Video Streaming and AI

A Quick Glance at How AI and ML are Transforming Digital Media Production And Delivery


Without a doubt, we are amidst a streaming and broadcasting revolution. Considering the significant explosion in the numbers and availability of OTT platforms such as Netflix, Amazon Video, Disney+, and Hulu the video streaming industry has undergone a massive transformation over the past few years. Accelerated by consumer demand, preferences, and needs during the lockdown, innovation is undoubtedly underway as each platform appears to gain an edge in the competitive landscape. While we are seeing innovations that inculcate a range of technologies and functionalities, in this blog, we will only focus on AI and ML to explore how OTT content delivery is being revolutionized. Some of the examples that are incessantly relevant to the use cases of artificial intelligence and machine learning in OTT are:


  • The classification of digital images, audio, video, or speech signals that are based on low-level features (for instance, edges or pixel attributes of any image)
  • Digital image, audio, or video enhancement and analysis (for instance, detecting a person in a digital image, de-noising, estimating the transmitted digital audio signal quality, and more)
  • speech recognition or separation of sources in speech signals (for instance, mapping any speech input to speech output)


AI-Based Video Indexing


Driven by AI capabilities, the video indexer can predict the requisites of viewers in order to make the video content more operable. This not only helps in increasing the user interactivity with online video platforms but also helps in boosting the video visibility whilst offering improved search performance and recommendations. 


AI services also help in gaining valuable video insights, thereby making the video content more visible and accessible. Ultimately, it significantly amplifies the monetization value by increasing the reach of the video content. 


Content-Aware Encoding


A host of video streaming giants such as Netflix uses artificial intelligence solutions to determine the appropriate encoding settings for each video content on the basis of complexity. Subsequently, it helps in optimizing the video quality and resources.


Encoding low-bitrate streams wherever and whenever possible helps in saving bandwidth and minimizing the overall cost. On the other hand, sporting events, as well as action-packed footage, needs a high bitrate in order to accommodate the pace of the movement. 


In addition to this, Netflix also relies on machine learning algorithms to custom-tailor encoding in accordance with each type of video content by using VMAF or Video Multimethod Assessment Fusion. Similarly, YouTube uses neural networks to enhance and improve the encoding process.


Object Detection as a Censorship Method


While most prominently used in the entertainment industry, object detection inarguably offers some heavy-weight and practical benefits in the video streaming industry as well. Artificial Intelligence is paving the way for content regulation with such tech-enabled forms of censorship – which promises to remove the necessity of manual monitoring.


In the past, sensitive video streams used to go viral because of the poor infrastructure that was in place for censoring such content. There was a heavy reliance on tech teams who used to monitor and interrupt any live stream that could potentially breach the community standards.


However, with the implementation of machine learning and deep learning algorithms, video streaming organizations are now able to act smarter, faster, and more effectively. AI can also interpret harmful and sensitive video content more efficiently while protecting the privacy of viewers.


Also Read: The Revolutionizing Effects of NLP in The Healthcare Industry


Personalized Content Recommendation


Perhaps the most crucial role AI and ML can play in digital media streaming is the ability to make appropriate audio and video recommendations. For instance, Netflix’s AI recommendation engine can furnish remarkable insights into your digital content consumption habits, such as the type of TV shows or movies you intend to watch. 


A powerful and robust recommendation engine fuelled with AI can help in filtering content based on search terms, age of the video, browsing history, and other aspects in order to improve viewer personalization and participation. By calculating the data rate, it can further assist in optimizing bandwidth usage whilst maintaining an appropriate level of quality, which is impossible to achieve manually.


How Netflix Leverages AI To Spare $1 Billion A Year?


Netflix has already in the past that its accurate and strategic AI-powered suggestions spare up to a whopping $1 billion per year by minimizing churn. The implementation of Energetic Optimizer by Netflix makes a huge difference to optimize arranged information exchanges and compress codecs. In expansion to these Counterfeit Insights, it optimizes over-the-top conveyance by anticipating unsteady networks and congested joins with the further selection of relevant Internet Protocols (IP).


Moreover, Google, Microsoft, Amazon, and more have cloud-based video conveyance channels. Here, artificial intelligence solutions play a pivotal role in adaptability. The cloud administrations of these aforementioned companies have prominent sum flexibility which in simplest terms implies the ability and capacity to diminish or increment accessible assets as required. Furthermore, Manufactured Insights is used to anticipate the increment in asset necessities with a focus and point to diminish the delaying. 


The Implementation of AI in Video Streaming and OTT Industry is Here To Stay


AI holds a vital place inside the OTT and video streaming industry in a lot of ways. From content discovery and content material enhancement to video indexing and augmenting the high-satisfactory of virtual images, AI can seamlessly assist in promoting online content material and strike profound engagement inside the digital media streaming sector. 


At the moment, we are sure that artificial intelligence and machine learning solutions when implemented in the OTT and video streaming sector can present innumerable opportunities but in the future, expect them to blow your minds even further.


If you are looking to build a video streaming platform with the integrated capabilities of AI solutions, request a free quote. Our team of experts will help in creating feature-rich live/VOD/OTT applications with seamless UI/UX to entice and engage your target audience. 


About Author

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Priyansha Singh

Priyansha is a talented Content Writer with a strong command of her craft. She has honed her skills in SEO content writing, technical writing, and research, making her a versatile writer. She excels in creating high-quality content that is optimized for search engines, ensuring maximum visibility. She is also adept at producing clear and concise technical documentation tailored to various audiences. Her extensive experience across different industries has given her a deep understanding of technical concepts, allowing her to convey complex information in a reader-friendly manner. Her meticulous attention to detail ensures that her content is accurate and free of errors. She has successfully contributed to a wide range of projects, including NitroEX, Precise Lighting, Alneli, Extra Property, Flink, Blue Ribbon Technologies, CJCPA, Script TV, Poly 186, and Do It All Steel. Priyansha's collaborative nature shines through as she works seamlessly with digital marketers and designers, creating engaging and informative content that meets project goals and deadlines.

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