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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Adopting real-time streaming experiences such as live events, interactive video, cloud gaming, video communications, and virtual worlds is soaring. Meeting this demand with CPU-based codecs can often be expensive and inefficient, unnecessarily boosting CAPEX, OPEX, and carbon emissions generated by CPU-based encoding. In a breakthrough for the video processing sector, Tony speaks to us about how organizations can tap into GPU-based solutions that substantially trim down operating costs, capital expenditure, and energy usage.
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Judging by the number of trade publication articles and speaking sessions that focus on the topic, you’d think that the entire media and entertainment industry is focussed on cutting carbon costs. But is that really the case? True, broadcasters have set ambitious targets to reach net zero, the streaming giants are following suit, and they’re putting pressure on production companies to reduce their environmental impact and include sustainability messaging in the content they produce. Carbon emissions have even become a critical consideration in planning new studio builds. But not every part of the production chain is putting the environment first.
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In an era of unprecedented technological advancement, the media and broadcast industry plays a significant role in shaping how we perceive the world. However, this sector, like many others, faces a pressing challenge: the threat to our planet’s delicate ecological balance. As concerns about environmental sustainability escalate, our industry needs to take bold steps to minimize its own impact on the environment and pave the way for a greener future.
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As we approach the end of the summer, marked as the warmest ever recorded, it’s clear that focusing on the environment and sustainability is crucial for all organizations and businesses. The TV and media industry has a dual responsibility. On one hand, it’s crucial to provide the public with accurate information about the situation, and on the other hand, it’s equally important to address the sustainability impact of producing and distributing TV and video content.
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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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Asia used to be called the Far East by some Europeans, but that was largely referring to the northern part of APAC. APAC actually refers to about one third of the world’s land mass if we include all the Pacific countries, which are around eight hours ahead of Greenwich Mean Time (UK), and China, Singapore, South Korea and Japan (nine hours ahead) – and more for Australia and New Zealand. Of course, the differences are not only represented in the time zones, but much more importantly in those between peoples and cultures.
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Access to great training resources is a must in live broadcast production, where — thanks to both historical factors and modern pressures — it can be difficult to attract, maintain, and retain talent.
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In recent years, the emergence of new distribution models such as AVOD, SVOD, and FAST channels have disrupted the traditional television market. These newer platforms offer viewers greater flexibility and choice and are rapidly gaining popularity among younger audiences. To stay ahead of the curve, broadcasters need to diversify their channels by developing content specifically tailored to these new platforms and consumers, whilst simultaneously meeting the needs of existing audiences.
But is the current mix of talent behind the scenes diverse enough to cover all perspectives, when creating and managing next generation channels?
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Despite the continuing growth in audiences for streaming content, the established broadcasters remain popular. Indeed, market predictions are that, while streaming services will gain viewers and revenue, traditional linear television will remain stable; Statista even suggests a slight rise in daily viewing hours.
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