“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.
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?
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.
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.
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.
Broadcasters and media companies continue to implement systems powered by Artificial Intelligence (AI) across different workflows. While there is increasing awareness for AI components to be trustworthy in terms of transparency, explainability or fairness – when it comes to trust, aspects such as security and resilience are also important.
Birgit Gray from DW Innovation provides insight into the concept of AI Robustness and her cooperated work in the AI4Media project to make an AI component for one of DW’s media tools more robust and therefore more trusted.
Media and entertainment is a well-established industry, with a heritage to be proud of. But maintaining a pivotal role in the consumer landscape for several decades comes with a unique set of challenges. As media and broadcast has evolved from a handful of linear channels through to a multi-platform ecosystem, more content needs to be reformatted and repurposed to reach an increasingly fragmented audience.
You don’t need to be Nostradamus to work out that linear TV will one day go the way of Monty Python’s parrot: it will cease to be. The timing, however, is less predictable. Because unlike Python’s Norwegian Blue, scheduled TV continues to provide meaningful company in our living rooms. It will inevitably fall from its perch, but with a sizeable audience still feeding it, there’s plenty of life in the old thing yet. As legacy media inches towards a digital-only world, the prolonged squawk of scheduled TV is a major complication. Companies need to deliver for today while planning for a different tomorrow.
The media industry has evolved over the past century, from inventions to disruptions in communication and new-age technologies. In the early 1900s, radio was the crucial link to information, followed by television which by the mid-1900s became the most potent medium for news and entertainment. The late 20th century introduced the internet, and service & media providers entered a new evolution of connectivity. Websites and social media platforms flood the market, providing more choices than ever before. In the 21st century, smartphones are standard, and content consumption requires anytime, to any device, and anywhere access. The traditional television model is disrupted with streaming services like Netflix and Hulu and social media becomes a primary source of news and entertainment with Facebook, Twitter, YouTube, etc.
Synthesized speech is nothing new. We’ve long been accustomed to hearing the robotic tones of computer-generated voices in messaging systems, access services and, more recently, in virtual assistant technologies like Siri and Alexa. But we’d never consider replacing the talent in our media productions with a synthesized voice. Or would we?