An IBC Accelerators first, the 2024 Programme will feature very special Challenge under an umbrella theme of ‘AI Media Production Lab', which will set out to explore a series of specific AI concepts in various guises of production. This encompasses researching and developing learnings around the various AI tools and techniques in terms of how to improve creativity, bias and efficiency in this fast-moving, disruptive area of media and technology.  

In this Accelerator project, three specific use case studies have been spawned out of three unique Challenge Proposals some key industry thought leaders, all of which will deep dive into the best practice and ethical use cases of AI within media production and storytelling pipelines, non-bias audience validation and personas towards new IP developments, as well as looking into breakthrough workflows using predictive, generative AI, bespoke language LLM, modelling and AI-enabled camera tracking to enhance live sports and events. 

The three Case Studies within IBC's AI MEDIA PRODUCTION LAB include: 

8a) Generative AI in Action  

Project Challenge Proposed by: RAI, EBU

Generative AI will revolutionise broadcasters' workflows by automating content creation, enhancing real-time customisation and streamlining production processes, thereby driving efficiency and innovation in the dynamic media broadcasting industry. This challenge is about using Generative AI for content production and explore the integration and impact of Generative Artificial Intelligence (Generative AI) in a production centre environment.  

As the M&E industries strive for increased efficiency, automation, and innovation, Generative AI emerges as a powerful tool with the potential to transform traditional production workflows, so the project will also aim to deliver an in-depth analysis of existing tools on Generative AI and its best applications in the creation of scene, script and virtual character. In addition, the R&D will explore the qualitative aspects of the human-machine collaboration within the production centre, and investigate the interaction dynamics, employee skill adaptation, and the overall organizational culture in the context of introducing Generative AI into the production workflow. The POC results will aim to provide a synthesis of findings, offering insights into the transformative potential of Generative AI in a production centre setting. Watch Kickstart Pitch HERE.

8b) AI Audience Validation Assistant (AAVA) 

Project Challenge Proposed by: Zwart, Evangelische Omroep EO 

Understanding and engaging the target audience is paramount for media organizations, so they can produce content that resonates with all parts of that audience. Traditionally, success was only visible post publication or through costly and time-consuming methods like focus groups. In an age where data is key, this project leads in innovation by combining extensive audience data with advanced AI to blend and transform content creation, involving the audience in the development process. The project will explore solutions to turn passive viewers into active contributors through AI-driven personas that reflect society's complexity. This unique approach accelerates content development, infusing it with genuine societal insights. Essentially, the POC results will showcase a vibrant, interactive platform where the public not only consumes media but also plays a role in its creation, heralding a new era of public-engaged media. Watch Kickstart Pitch HERE.

8c) Changing the Game: Predictive Generative AI  

Project Challenge Proposed by: Verizon Business 

Leveraging LLMs, tailored datasets and computer vision housed in a Private 5G network, this Challenge aims to create the ability to generate predictive video and audio that is authentic and as close to what actually happens during a live-action event such as sports or live broadcasts. The project would aim to evaluate the efficacy of which datasets are needed to accurately predict live video outcomes and how far into the future the predictive video and audio can remain authentic to the actual video and audio, to help enable real-time enhanced experiences, such as personalized commentators and localization. 

This Challenge POC results will also be mix of new exploration in LLM and Modelling, Computer Vision and Generative Video (ie. Stability AI) to help the M&E industry envision new workflows to elevate live-to-air storytelling and broadcasting, and truly enhance the fan's experience. Watch Kickstart Pitch HERE.