The explosion in OTT platforms has created new opportunities for traditional media companies to reach larger audiences worldwide. As a worldwide distributor of Spanish-language content, this organization is no exception – and the company now offers its programming on virtually every major OTT outlet.
The initial euphoria over AL/ML seems to have died down in the M&E industry. Our research shows that many M&E players have run AI initiatives with different vendors but have not achieved anything substantial enough to solve their business problems. Though the demo was impressive, the project hit a wall at the Proof of Concept (PoC) stage because the AI solution did not work for their content! When the cycle was repeated with multiple vendors, they concluded that AI models are not available or mature enough to solve specific M&E business challenges.
Video consumption on OTT platforms has gathered rapid momentum in the last couple of years, peaking significantly in the past few months – thanks to the audience being locked down due to COVID19 pandemic. With so many platforms and so much of content available for consumption today, OTT players are hard pressed for time to create the buzz and differentiation for their shows across media.
While the impact of ML and AI have been discussed and debated for years, practical applications are fast accelerating across the media supply chain. The pace of innovation is moving quickly and with the cloud wars in full force, there are new services becoming available all the time that offer novel ways to automate tasks with ML and AI. Already, the big three cloud providers — AWS, Azure, and Google — have rolled out powerful capabilities that help with essential tasks including captioning, transcription, and even object/facial recognition to bolster compliance edits and to augment metadata. For media organizations, the implications of these solutions are vast, and we’ve already begun to see their power. With things moving so fast, though, it’s challenging to keep up and important to have the right architecture and structure in place to take advantage of these innovations.
World cups, league tournaments, Grand Slams and Super Bowl! It’s safe to say that the buzz around sports is never-ending. However, the prevailing situation is a challenging run for sports and fans, alike. There has been a steep slump in viewership over the last couple of months. ESPN’s viewership has dropped by 50%, while the NBA has seen a 14% decline in viewership contrasted to 2019.
The current pandemic has affected many sections of the sports media due to social distancing measures and government-imposed restrictions.
Nonetheless, sports fans across the world seem to be eagerly awaiting their next game. A study conducted by Forbes about sports fans showed that though there has been a lack of live games, fans are as hopeful as ever. For instance, the Green Bay Packers that compete in the NFL have a season-ticket waiting list with 137,000 people.
This brings up the inquiry – how can sporting leagues and broadcasters improvise to keep fans at the centre and what role can technology play when it comes to fan engagement?
In this webinar, we take a sneak peak at the recent IABM Buying Trends report, revealing what broadcast and media companies around the world need from technology vendors to do better business now and into the future – and where they will be investing.
Tim Claman (CTO and VP of Product Management, Avid) discusses new AI applications that are showing tremendous potential and are now being explored
Andreas Jacobi (CEO and co-founder, Make.TV) discusses how new advancements in smart cloud video technology and AI enable live production operations to automate and scale the tasks involved in acquiring, moderating, processing and producing video
Tommaso Cesano (Head of Business Development and Strategy, Meta Liquid) explains how AI video analysis can support broadcasters and media companies in empowering DAM and delivering more engaging and personalized user experiences to viewers.
Jérôme Wauthoz (VP, Products, Tedial) and Daniel McDonnell (MD, Timeline Television) explore how automation tools that leverage AI help production teams increase and personalize content for better storytelling