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.
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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.
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Media content delivery generates a lot of logs. This is a fact well understood at G&L, since we facilitate the distribution of audio and video content, live and on-demand, for some major broadcasters and official bodies to end users. We know well that log data has no lesser commercial value than the content itself. Log misdelivery can lead to short-term profit losses for streaming and broadcasting service providers. These issues can affect advertising exposure assessment, long-term planning, and more. Providing accurate data and analytics alongside our core services is our dedication, duty, bread and butter.
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Unless you are a hermit, you cannot fail to have noticed all the talk about AI at the moment. It is everywhere.
If you believe the hype, then we are all doomed. The machines are ready to take over, and there will be no need for any human to do any work ever again. We are all rather more cynical than that, and we know deep down that we can probably hang on to our jobs at least for a while.
For a long time now, we have known one fundamental thing about computers. They are good at dull, repetitive tasks, while people are good at creative tasks. And, despite the reports in the popular press, AI largely conforms to that rule.
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Media is now a global business. Audiences anywhere are clamoring for content from everywhere.
The K-Pop phenomenon means that a concert taking place in Seoul can attract a huge audience in Seattle and Sienna. In recent weeks sports fans globally have been gripped by world championships: cycling in Scotland; netball in South Africa and football in Australia and New Zealand.
Media connectivity is more than just television coverage of sports or concert relays to theaters.
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“It was the best of times, it was the worst of times…”
What a glorious decade for global media distribution. Content consumption is higher than it’s ever been, borders have been stretched, pushed or removed entirely, “foreign” content is captivating “foreign” audiences and the inaccessible is finally becoming accessible to all.
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Technology is set to play a crucial role in the fight against climate change by helping us to reduce greenhouse gas emissions, enhance energy efficiency, and promote sustainable practices. Is there potential for AI to also play a part in this? Google DeepMind certainly thinks so and is using the latest AI developments to help fight climate change and build a more sustainable, low-carbon world. But although AI has received a lot of attention since the launch of the large language model, ChatGPT, last year, AI and machine learning (ML) are not new concepts. Content creators, technology vendors, and service providers in the video industry have been using ML for some time. The difference now is that generative AI models have become more advanced, and are now being used by a wider audience. If organizations like Google DeepMind aim to use generative AI to fight climate change, can the video industry also use generative AI to optimize systems, create more sustainable consumption habits, and reduce the industry’s carbon impact?
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Have you thought about how tremendously the media and entertainment industry has changed in the past 20 years? Over-the-top (OTT) platforms and services first appeared in the early 2000s and challenged existing market players to move their business emphasis to online streaming. Netflix was the first game-changer that took the decision to transform traditional cable and satellite TV broadcasting models by offering consumers films and TV series on demand. This shift forced the global expansion of OTT services and the adaptation of traditional TV networks by launching their own OTT platforms. But that’s just a start for ongoing shifts in the industry.
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At the most recent NAB Show, Veritone Generative AI earned the IABM BaM Award® in the Monetize category. The platform also earned the NAB Show Product of the Year—the fourth year Veritone has won this award—this year in the AI and machine learning category.
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The media industry is experiencing the transformative impact of AI and ML technologies. These innovations have revolutionised various aspects of content creation, distribution, marketing, and monetization.
AI on entertainment platforms has led to a host of benefits, including data-driven enhanced efficiency, better personalization, and more informed program and content decision-making capabilities. AI in media production and post production has enhanced light ray rendering capabilities and can even edit the production using prescribed user preferences. In sports, AI editing can go as far as making whole game highlight reels. In archive semantic AI can discover scenes with car chases or even romantic scenes. There is no longer a debate about whether AI will happen; it is here, and it is here to stay.
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