EMERALD is a 30-month IA to develop and demonstrate exemplary tools for the digital entertainment and media industries using AI Machine Learning and Big Data technologies, to automate and speed processing, increase production efficiency, use less energy and increase the quality of content. There is a massive increase in the volume of video-based and extended reality content, with an unsustainable demand for skilled human resources, data processing and energy. EMERALD aims to meet the challenge by developing process automation for sustainable media creation; creating a testbed for measuring the energy used in media computation; developing more efficient data use for AI/ML in entertainment and media applications; reducing the power demands for large-scale media data processing; and creating acceptance and demand for AI and sustainable production technologies in the entertainment and media industries. The interdisciplinary Consortium of seven partners includes leading companies from the movie, broadcast, streaming and live entertainment technology sectors, supported by two major European universities.

The EU strategic autonomy in the digital economy requires more and more data to be processed in the Cloud-Edge-IoT computing continuum, instead of only the central cloud. This requires advanced automation and intelligence of the continuum. At the same time, recent breakthroughs in AI research have shown unprecedented intelligence to handle creative tasks. Such human-like intelligence will eventually disrupt how people use the cloud and continuum. INTEND aims at bringing such human-like intelligence into the cognitive continuum, to achieve the novel concept of intent-based data operation, which is capable of: (1) continually learning how to manage and adapt heterogeneous cloud/edge resources for more efficient data processing, (2) strategic decision making across the decentralized continuum for end-to-end data security and sustainability, and (3) human-friendly interaction with data stakeholders in natural language, for effective and trustworthy human-entric data operation. To achieve this ambitious objective, INTEND builds a strong consortium of world-class AI researchers and leading companies that cover the complete supply chain of the computing continuum. The project will deliver 11 novel software tools, which integrate into an INTEND toolbox. The approach and the tools will be tested and validated on 5 vertical domains, to achieve the novel intent-based data operation for video streaming pipelines, machine data platform, 5G data infrastructure, urban data space, and robotic AI applications. An open platform will be provided to support the extension with new hardware, management tools and AI models into the cognitive continuum. The outputs pave the way of migrating EU's data industry from cloud to the continuum, and implements EC's strategy of human-centric AI in the domain of data processing and computing continuum.

ENACT develops cutting-edge techniques and technology solutions to realise a Cognitive Computing Continuum (CCC) that can address the needs for optimal (edge and Cloud) resource management and dynamic scaling, elasticity, and portability of hyper-distributed data-intensive applications. At infrastructure level, the project brings visibility to distributed edge and Cloud resources by developing Dynamic Graph Models capable of capturing and visualising the real-time and historic status information, connectivity types, dependencies, energy consumption etc. from diverse edge and Cloud resources. The graph models are used by AI (Graph Neural Networks - GNN) models and Deep Reinforcement Learning (DRL) agents to suggest the optimal deployment configurations for hyper distributed applications considering their specific needs. The AI (GNN and DRL) models are packaged as an intelligent decision-making engine that can replace the scheduling component of open-source solutions such as KubeEdge. This will enable real-time and predictive management of distributed infrastructure and applications. To take full advantage of the potential (compute, storage, energy efficiency etc) opportunities in the CCC, ENACT will develop an innovative Application Programming Model (APM). The APM will support the development of distributed platform agnostic applications, capable of self-determining their optimal deployment and optimal execution configurations while taking advantage of diverse resources in the CCC. An SDK to develop APM-based distributed applications will be developed. Moreover, services for automatic (zero-touch provisioning-based) resource configuration and (telemetry) data collections are developed to help design and update dynamic graph models. ENACT CCC solutions will be validated in 3 use-cases with challenging resource and application requirements. International collaboration is planned as Japan Productivity Center has committed to support with knowledge sharing.

While media organisations increasingly support non-linear experiences for the consumer, those are still limited to single channels and media domains. Although several media organisations have recently succeeded in breaking data silos, data sharing is mostly limited to the organisation. Thus, there are challenges for producing content feeding multiple channels with different granularities and structures, mainly related to data discovery, management and (re-)use. XRECO will create a new data-driven ecosystem for the media industry, focusing on facilitating data sharing, search and discovery and supporting creation of news and entertainment content, in particular, the creation and (re-)use of location-related 2D and 3D assets and the creation of XR experiences. The ecosystem core, represented by a Neural Media Repository (NMR), will foster inter-organisation content sharing and provide increased access to content for media creators, considering novel data monetization and rights management policies. A set of AI-based media transformation services are built around the NMR to produce novel media- and XR experiences, including 3D neural reconstructions, neural based device localisation, image stitching, de-/re-lighting and holoportation. The developed technology will be validated in use case scenarios for (i) the news media for XR-based broadcasting and automatic and customized multitarget news publishing, and for (ii) location-based information and entertainment content, with applications in tourism and the automotive industry.

DataPACT develops novel tools and methodologies that enable efficient, compliant, ethical, and sustainable data/AI operations and pipelines. DataPACT delivers a transformative approach where compliance, ethics, and environmental sustainability are not afterthoughts but foundational elements of data/AI operations and pipelines. DataPACT contributes to the design, implementation, and management of data/AI operations and pipelines by embedding compliance, privacy, and environmental sustainability at their core design. It delivers compliance by design for data/AI operations and pipelines by developing innovative technical tools (DataPACT Compliance Toolbox) and tool-supported methodologies (DataPACT Compliance Framework) for compliance assessment and realization of data/AI pipelines designed, deployed and executed through a set of pipeline management tools and techniques (DataPACT Compliance-aware Data/AI Pipeline Toolbox). DataPACT validates its core results through a strong selection of seven complementary use cases offered by SMEs, large companies, and public sector organizations in relevant areas, including media and entertainment, healthcare, smart cities, law enforcement and security, customer relationship management, manufacturing, and public data. DataPACT helps them ensure straightforward and cost-effective compliance with existing and emerging regulations and guidelines, shorter time-to-market for compliant data solutions, fair and unbiased data-driven systems, respect for privacy and other fundamental rights, and lower and transparent environmental impact for intensive data/AI pipeline operations. DataPACT gathers a balanced consortium of 18 partners from 16 countries, consisting of two large companies, two public sector organizations, four SMEs, two research centers, and seven universities, covering relevant aspects related to legal, ethical, social, environmental, and technical compliance of data/AI operations and pipelines.