In today’s digital landscape, the demand for high-quality video content is ever-growing, driving the need for robust platforms that can support the development of modern video applications and streaming media services. One of the key challenges for enterprises, broadcasters, and content creators lies in effectively managing and delivering video content across various channels and devices. The first hurdle consumers encounter when wanting to view content is being able to access it. We’ve all heard or seen about big events where people haven’t been able to sign in at the time the event begins or where the video streaming quality has suffered.
Witbe – Greening the streaming: how real device testing can drive sustainability in the media industry
As millions of users consume streaming video content across various platforms daily, video app providers and mobile network operators face immense pressure to manage data usage and bandwidth efficiently. This challenge presents an opportunity to make the industry more sustainable. Leveraging data analytics captured through real device testing, streaming video service providers can not only optimize data transmission but also reduce energy consumption and promote sustainable user behavior. Vodafone, Telefonica, and Meta have already communicated interesting results in this field.
HPE – Is sustainability compatible with AI in the media and entertainment industry?
When none other than Tyler Perry halts an $800 million studio expansion after seeing a text-to-video AI demo, you know something major is happening in media and entertainment. AI isn’t new to the industry—Netflix has used machine learning (ML) to serve up recommendations since the early 2000s—but generative artificial intelligence (GenAI) is changing more than distribution and marketing. GenAI is primed to change how film, television, and music are imagined and produced.
NStarX – Can GenAI help with better visibility on the outcome of film making?
Financing Movie Making requires convergence of investors, bankers and several financial institutions coming together. The entire movie making process is complex across the lifecycle of pre-production, production, post-production, distribution etc.
As a producer of a movie, the intent is to ensure the success of the content (movie) and make financial profit. The entire moving making process results in a lot of data generation (from scripts, marketing assets, actors, posters, trailers, props, exchange of information, ideas and so many other aspects across the lifecycle).
Can AI or GenAI help with finding patterns through the latitude of data across the movie making lifecycle? Can it help with prediction of success of movies that allows producers, directors, financiers to take informed and wise decisions for moving making? NStarX Data Scientists have been looking at this problem for a while now!
Perifery – Intelligent Content Engine
Perifery’s Intelligent Content Engine (ICE) is a software platform that leverages AI agents and advanced AI models to manage, organize, and curate media content such as images, videos, audio files, documents, and other multimedia assets. Acting as an AI Media Content Librarian, ICE examines, understands, and catalogs every file within its view. It automatically categorizes, organizes, and understands media assets based on the content itself regardless of the existence of any traditional metadata.
Agama Technologies – Unify, simplify, and understand your data: how consolidation can streamline and empower your video services
In today’s dynamic video market, service providers have adapted and evolved their services in sync with the technology evolution in customer devices, mobility, and preferred ways to interact with entertainment content.
As a result of innovation and growth, some complexity and fragmentation have unavoidably occurred. For instance, IPTV over ABR services is run together with companion services on user-owned devices like connected TVs, phones and laptops – alongside value-added services, such as catch-up and start-over, live together with PVR, third-party AVOD, as well as targeted advertising.
Accedo – Can AI support the transition towards a more sustainable video ecosystem?
The OTT industry has undergone some major changes over the past few years. Market growth slowed somewhat compared to previous years and video providers have broadened their monetization strategies and shifted focus from subscriber growth to profitability. Despite this, the OTT video industry remains buoyant; according to analysis by Statista, the industry is projected to show an annual growth rate of 6.30% between 2024 and 2029, to reach US$429.40bn by 2029. This change of focus towards profitability is driving service providers to provide a better experience for viewers and optimize their services. However, there is a need to balance this drive for profitability with the industry-wide need to transition towards a sustainable video ecosystem.
Viaccess-Orca – Mastering TV monetization with AI-driven solutions
In the television world, generating new revenue can be a significant battle. Broadcasters and video service providers face growing competition for eyeballs, changing viewer demands, cost pressures, and an array of regulations, amongst other challenges. As the television industry evolves, broadcasters and service providers need to find new ways to attract viewers, engage audiences, and increase revenue.
This article will highlight some of the key challenges that broadcasters and video service providers face when monetizing content and offer innovative solutions for generating new TV revenue, including personalized FAST channels, targeted TV advertising, tailored content packages, and shoppable TV.
Veritone – So, Your Content Is Finished…Now What?
Media has come a long way from its traditional production journey. The advent of artificial intelligence (AI) has revolutionized the previously linear path of content production, transforming the process by creating new efficiencies and allowing content to have a second life beyond its initial creation and broadcast.
With AI’s robust capabilities in tagging, managing, and preparing content, production teams can now maximize content usage while optimizing resources, creating a more reliable flow of content even in times of high demand or disruption. In this article, I’ll delve into the evolving media ecosystem, highlighting the role of AI in content management, monetization, and the industry’s future.
Simplestream – Needle in a haystack: the challenge of normalizing metadata
The world of video content moves quickly. It’s in ceaseless motion, and this goes hand in hand with technological advancement. In this scenario, it becomes paramount for operators and distributors in the streaming space to create seamlessly functioning architectures. It’s all about tech stacks that must normalize workflows and bring together data from multiple existing services. Of course, this is far easier said than done as content owners wish to enhance their offering with a feed of growing requirements which platform operators have for their own streaming services. Progress is perpetual, think of ratings for movies and series, specific categories for niche programming, or even broadcast identifiers.
