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.
Ateme – Reducing streaming’s carbon footprint through innovation
The video streaming industry, which now accounts for 60-80% of global internet traffic, is facing increasing scrutiny due to its significant contribution to carbon emissions. According to a report from The Shift Project, internet activity is responsible for approximately 4% of global greenhouse gas emissions, a figure that is expected to rise as demand for streaming services grows. This surge in video consumption has driven the expansion of data centers, network infrastructure, and consumer devices, all of which add to the industry’s environmental impact. In response, companies like Ateme and other video processing vendors are focusing on innovations such as advanced video codecs, efficient compute platforms, and AI-driven optimizations to reduce data size, energy consumption, and overall carbon footprint in the streaming ecosystem.
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!
Unveiling the future: dive deep into AI at IBC2024
The media and entertainment landscape is undergoing a seismic shift. Artificial intelligence (AI) is shaping every aspect of content creation, production, and delivery, streamlining workflows, adding efficiencies and delivering better experiences for viewers. At IBC2024, the all-new AI Tech Zone in Hall 14, powered by the EBU, promises to be the place to cut through the hype and discover the impact AI can have now and in the future.
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.
Caton – Beyond the Cloud: Intelligent IP Broadcasting
The content delivery landscape is undergoing a seismic shift. Audience demand for high-quality content explodes while traditional IP methods struggle to keep pace. They face limitations in scalability, flexibility, and reliance on the unpredictable nature of the public internet.
The good news is that a revolutionary approach is emerging, driven by the exciting convergence of cutting-edge technologies. This approach leverages distributed cloud architecture and the power of Artificial Intelligence to completely reshape content transmission. In this article, we will delve into this future of intelligent IP broadcasting and explore how it empowers broadcasters not only to overcome these challenges but also to deliver exceptional experiences for their audiences.
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.
Signiant – How AI is becoming a vital part of the intelligent transport workflow
The use of AI at all levels in the broadcast chain increased with dizzying speed throughout 2023 and into 2024. But while the likes of ChatGPT and its generative AI cousins have stolen much of the limelight when it comes to assessing the technology’s impact on the industry, in truth there is likely more work being done in other areas. AI has been part of the fabric of the industry for several years now, and at Signiant, this has become a vital component of what can be referred to as an intelligent transport workflow.
RT Software – Why AI won’t steal our broadcast graphics jobs – but it might change them…
We have all seen the consternation in the media about the rising challenge of AI in a wide range of industries and the potential for mass job losses as a result. Should we be concerned that the same could happen to workers in the broadcast graphics sector? The trouble with these kinds of sweeping statements is that they cover such a broad set of roles that it becomes meaningless. To make informed comments we really need to address each niche within ‘broadcast graphics’ separately and look at what AI could do, or is already doing, to see how it affects the users involved. What is true for some areas may be very different for others.