Overview
PSMs are facing the need to raise the quantity and the quality of content they create to address linear and non-linear channels. To do so, they are adopting agile technologies to accelerate the production and the management of massive amounts of data. The three pillars of these evolutions are data management, computing architectures, and machine learning. EBU groups are addressing these three pillars by providing:
- Development of open-source Tools - Machine Learning - Metadata
- Defining best practices and standards
- Outreach and dissemination
AI-Sandbox
AI is reshaping the media industry. The AI Sandbox brings together broadcasters and technology partners to test, learn, and scale responsible AI together. By harnessing collective intelligence, we’re driving innovation across the media sector.
Join the Sandbox !
Groups
AIM is the umbrella group that oversees the DATA, METADATA and AI domain works, maximizing knowledge sharing and collaboration. This group meets monthly.
The AI-Benchmarking Group has developed a toolset for benchmarking machine learning–based applications. After designing and publishing tools to benchmark Speech-to-Text (STT) systems and creating a dataset for evaluating face recognition applications, the group has extended its work to Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
It recently published the report Evaluating RAG Technologies for News (EBU Tech Report 093) and is now focusing on Agentic AI for production use cases.
The main activity of this group is to support EBU Members in the area of metadata. To achieve this, the group develops specifications and promotes innovation, notably through the development of EBUCorePlus, an open source ontology for media enterprises.
AI and Automatic Metadata Extraction (suspended)
The group has been suspended, and the presentations are still available in the workspace. Work addressed in this group includes metadata schemas, the capabilities and performance of automatic metadata extraction tools, and the development of machine learning algorithms and related tools.
Event
Data Technology Seminar - DTS is your ticket to staying ahead in the ever-evolving media landscape. Learn from the best in the industry, and actively contribute to the future of media with AI at its core.
Currently, the following deliverables are planned (green indicates the deliverable has already been delivered). Note that deliverables are dependent on enough participation in the work and that the planning is subject to change. New deliverables are added regularly.
2026
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Launch of the AI Sandbox - a collaborative platform where EBU members can showcase and evaluate custom AI models designed for media applications. -
Organise the DataTech Seminar 2025 -
Knowledge sharing on metadata/data/AI technology - AIM monthly meetings -
Development of a POC and publication of a TR report on AI to share R&D expertise among EBU Members - key topic being Agentic AI -
Release the full documentation for EBUCorePlus 2.0. -
TEMS (EU project ) - design and maintenance of the TEMSCore - the Media Data Space Ontology - develop data gathering and mapping tools and an embeddings generator -
SMPTE: Chairing the DG on the AI Systems Registry and releasing a standard for the identification and registry of AI systems performing media.
2025
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Launch of the AI Sandbox - a collaborative platform where EBU members can showcase and evaluate custom AI models designed for media applications. -
Organise the DataTech Seminar 2025 -
Knowledge sharing on metadata/data/AI technology - AIM monthly meetings -
Publication of a TR report on AI to share R&D expertise among EBU Members - key topic being Agentic AI -
AI benchmarking group: Develop a Proof of Concept on Retrieval-Augmented Generation (RAG) to explore state-of-the-art applications in news production. Write report of findings and recommendations for the News and Technical Committees -
Release of EBUCorePlus 2.0 -
SMPTE - Update Engineering Report on AI for Media - Write a standard proposal on AI model registration -
TEMS (EU project ) - design and maintenance of the TEMSCore - the Media Data Space Ontology -
VeraAI (EU project) - Design of ML algorithms for news authorship attribution and audience profile prediction
2024
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Knowledge sharing on metadata/data/AI technology - AIM monthly meetings -
DataTech Seminar 2024 -
Development and deployment of the meta-radio application on the AI HUB -
SMPTE task force on AI - One report published - 3 standard proposals -
Development of the cloud-hosted AI-HUB to evaluate, expose, and exchange AI applications -
Development and deployment of a face recognition system for TV programme on the AI HUB -
Develop a demo for IBC - Technical Paper accepted -
Research project with the EPFL - One master's thesis successfully completed -
Specification of the Metadata model forTEMS - first version published -
MCMA - update the Libraries and publish a SMPTE standard - ST 2126 -
AI Benchmarking Group: POC on RAG/LLM/Agents for News - deliverable in 2025 -
Update of the EBUCorePlus - v2.0 -
Development of AI models for analysing editorial content for VeraAI
2023
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Development of datasets to evaluate facial recognition systems: the biggest for AV content! -
Publication of the first release of the EBUCorePlus : the EBU ontology for media -
DataTech Seminar 2023 -
ETC/SMPTE task force on AI: engineering report AI for Media -
Development of the cloud-hosted AIM platform to evaluate, expose, and exchange AI applications -
Development of an open-source Facial Recognition Framework for Video -
Knowledge sharing on metadata/data/AI technology -
Maintenance of the MCMA libraries and MAM -
Advanced Studies on Machine Learning for Members
2022
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Open source demo MAM based on serverless MCMA framework (Q2 2022) -
MDN Workshop 2022 ( Q2 2022) -
Fake News detector for English text: API open to Members (Q2 2022) -
EBUCore+ Demonstrator Kit: a cloud-hosted demo (Q3 2022) -
Cloud-hosted Metadata Exchange Platform for archive (Q3 2022) -
Knowledge Sharing on MetaData and AI (Q4 2022) -
Organisation of DataTech Seminar 2023 -
Development of an open-source Facial Recognition Framework for Video (Q1 2023)