If you’ve been paying attention to the conversation around production rooms, “cloud” is everywhere, especially the benefits. But just because we talk about the benefits of going cloud, it doesn’t mean it’s a one-size-fits-all solution.
Different productions have different needs, from the size of what’s being captured to the size of the team working on it. Not only that but transitioning to cloud can sometimes entail changing from hardware to software and adapting to a new way of doing things.
To make a leap to cloud production and make it truly work for you, some considerations must be made.
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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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Streaming might be our favorite pastime, but beneath the surface, it’s a colossal energy-guzzling process that’s taking a toll on our planet.
Today, the average consumer worldwide spends about 19 hours a week streaming video – but this can be much, much higher for some. And with a population of more than 742,200,000, Europeans could have streamed more than 735 billion hours – or 83 million years – of content in 2022 alone!
To put this into perspective, every hour of video streamed emits roughly 55g of CO2e. This would mean that Europeans streaming habits account to roughly 40.4 million metric tons of CO2e in just one year – the equivalent of driving 210 billion km, given the average gas-powered car emits 192g of CO2e per km.
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In the fast-paced landscape of the broadcast and media industries, staying ahead of the technology curve requires adaptability and agility. To overcome the limitations of hardware-specific devices and embrace the future, broadcasters, content providers and distribution and delivery service providers are turning to cloud-based solutions. By transitioning to the cloud, they can unlock new levels of flexibility, efficiency, and scalability. In this article, we will explore the advantages of cloud and cloud-based solutions, overcoming migration challenges, the importance of becoming more agile, cost efficiency and scalability, security and regulatory considerations, and the rapid adoption of IP workflows in the industry.
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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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Build vs. buy might not be the oldest dilemma in the streaming technology book, but it’s close. And when it comes to complex live streaming, the horns of that dilemma are particularly pointed.
The streaming technology market is typified by off-the-shelf, line-of-business applications that do a few things very well, but are extremely difficult or impossible to extend if they don’t do exactly what you want. That lack of customization can be a dealbreaker.
On the other hand, for a broadcaster (or large enterprise, or betting company, or …) to build its own streaming platform from scratch requires a daunting investment of time and resources—resources that would be much better spent on their core business proposition.
So let’s dig a little deeper into both buying and building, as well as look at a middle path that offers media companies the best of both worlds.
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Why is it so important to communicate the value of technology solutions to potential buyers? How will this improve their decision-making or outcomes? Because beyond the ever-present sales and marketing imperative is a more important driver: media businesses can’t fully benefit from the ecosystem of the future without understanding its significance.
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While the shift from ground to cloud playout is well under way, there are several roadblocks on the path to a fully cloud-based infrastructure that will leave the broadcast industry in a transitional phase for years to come. Here, we delve into those obstacles and propose a hybrid approach for this interim period that allows broadcasters to continue utilizing their existing on-premises equipment, while reaping the benefits of cloud technology.
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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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