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!
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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.
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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.
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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.
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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.
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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.
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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.
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“The new reality of content creation centers on three C’s: Connection, Collaboration and Communication. All done remotely. Octopus Newsroom is the best solution for that reality.”
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In the “streaming wars” era, retaining subscribers has emerged as the ultimate battleground. As streaming companies navigate through a maze of subscription models, the challenge – or battle plan as it were – is not just to attract viewers but to retain them amidst fierce market competition and tightening consumer budgets. It’s no wonder recent research by Parks Associates revealed that the average annualized subscriber churn rate stands at 47%.
In the face of these challenges, media companies are redefining the playbook on subscriber engagement, leveraging a mix of cutting-edge technologies to forge deeper, more enduring connections with their audiences.
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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.
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