Horizon Europe: Robust and Trustworthy Generative AI for Robotics and Industrial Automation

Horizon Europe: Robust and Trustworthy Generative AI for Robotics and Industrial Automation is sponsored by European Commission. This opportunity supports mission-aligned projects and measurable outcomes.

Robust and trustworthy GenerativeAI for Robotics and industrial automation (AI/Data/Robotics & Made in Europe Partnerships) Find EU-funding for your projects now! Search for Funding Search for programs Reset all filters Select the type of organisation that you are interested in to implement projects. The role of an organisation involved could by lead partner, regular project partner, associate partner, and observers.

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Selection of eligible entities Reset all EU Body An institution, body, office or agency established by or based on the Treaty on European Union and the Treaties establishing the European Communities. Education and training institution All education and training facilities for people of different age groups.

International organization An intergovernmental organization having legal personality under public international law or a specialized agency established by such an international organization. An international organization, the majority of whose members are Member States or Associated Countries and whose main objective is to promote scientific and technological cooperation in Europe, is an International Organization of European Interest.

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A college/university is a legal entity recognized by its national education system as a university or college or secondary school. It may be a public or private institution. Small and medium-sized enterprise (SME) A microenterprise, a small or medium-sized enterprise (business) as defined in EU Recommendation 2003/361 .

To qualify as an SME for EU funding, an enterprise must meet certain conditions, including (a) fewer than 250 employees and (b) an annual turnover not exceeding EUR 50 million and/or an annual balance sheet total not exceeding EUR 43 million. These ceilings apply only to the figures for individual companies.

Selection of eligible countries Reset all Belgium (Belgique/België) Bonaire, Saba, Sint Eustatius Bosnia and Herzegovina (Bosna i Hercegovina / Босна и Херцеговина) Faeroes (Føroyar / Færøerne) French Polynesia (Polynésie française/Pōrīnetia Farāni) French Southern and Antarctic Lands (Terres australes et antarctiques françaises) Greenland (Kalaallit Nunaat/Grønland) Israel (ישראל / إِسْرَائِيل) Kosovo (Kosova/Kosovë / Косово) New Caledonia (Nouvelle-Calédonie) North Macedonia (Северна Македонија) Saint Barthélemy (Saint-Barthélemy) Saint Pierre and Miquelon (Saint-Pierre et Miquelon) Switzerland (Schweiz/Suisse/Svizzera) Wallis and Futuna (Wallis-et-Futuna) Selection of topics Reset all Administration & Governance, Institutional Capacity & Cooperation Administration & Governance, Institutional Capacity & Cooperation This topic focuses on strengthening governance, fostering institutional capacity, and enhancing cross-border cooperation.

It includes promoting multilevel, transnational, and cross-border governance by designing and testing effective structures and mechanisms, as well as encouraging collaboration between public institutions on various themes. Innovation capacity and awareness are also key, with actions aimed at increasing the ability of individuals and organizations to adopt and apply innovative practices.

This involves empowering innovation networks and stimulating innovation across different sectors. Institutional cooperation and network-building play a crucial role, supporting long-term partnerships to improve administrative processes, share regional knowledge, and promote intercultural understanding.

This also includes cooperation between universities, healthcare facilities, schools, sports organizations, and efforts in management and capacity building. Agriculture & Forestry, Fishery, Food, Soil quality This topic focuses on strengthening the agricultural, forestry, and fisheries sectors while ensuring sustainable development and environmental protection.

It covers agricultural products (e.g., fruits, meat, olives), organic farming, horticulture, and innovative approaches to sustainable agriculture. It also addresses forest management, wood products, and the promotion of biodiversity and climate resilience in forestry practices.

In the food sector, the focus lies on developing sustainable and resilient food chains, promoting organic food production, enhancing seafood products, and ensuring food security and safety. Projects also target the development of the agro-food industry, including innovative methods for production, processing, and distribution.

Fisheries and animal management are essential aspects, with an emphasis on sustainable fishery practices, aquaculture, and animal health and welfare. This also includes efforts to promote responsible fishing, marine conservation, and the development of efficient resource management systems. Soil and air quality initiatives play a crucial role in environmental protection and public health.

This includes projects aimed at combating soil and air pollution, implementing pollution management systems, and preventing soil erosion. Additionally, innovative approaches to improving air quality—both outdoors and indoors—are supported, alongside advancing knowledge and best practices in soil and air management.

Air Quality, Biodiversity & Environment, Climate & Climate Change, Water quality & management This topic focuses on protecting the environment, promoting biodiversity, and addressing the challenges of climate change and resource management. It includes efforts to mitigate and adapt to climate change, develop low-carbon technologies, and reduce GHG emissions. Biodiversity promotion and natural protection are key aspects.

It also covers improving soil and air quality by reducing pollution, managing contamination, preventing soil erosion, and enhancing air quality both outdoors and indoors. Water management plays an essential role, including sustainable water distribution, monitoring systems, innovative wastewater treatment technologies, and water reuse policies.

Additionally, it addresses the protection and development of waterways, lakes, and rivers, as well as sustainable wetland management. Arts & Culture, Cultural Heritage, Tourism This topic focuses on preserving, promoting, and enhancing cultural and natural heritage in a sustainable way.

It includes efforts to increase the attractiveness of cultural and natural sites through preservation, valorisation, and the development of heritage objects, services, and products. Cultural heritage management, arts, and culture play a key role, including maritime heritage routes, access to cultural sites, and cultural services like festivals, concerts, and art workshops.

Tourism development is also central, with actions aimed at promoting natural assets, protecting and developing natural heritage, and increasing touristic appeal through the better use of cultural, natural, and historical heritage. It also covers the improvement of tourist services and products, the creation of ecotourism models, and the development of sustainable tourism strategies.

Circular Economy, Natural Resources This topic focuses on the sustainable management, protection, and valorisation of natural resources and areas, such as habitats, geo parks, and protected zones. It also includes preserving and enhancing cultural and natural heritage, landscapes, and protecting marine environments.

Circular economy initiatives play a key role, with actions aimed at innovative waste management, ecological treatment techniques, and advanced recycling systems. Projects may focus on improving recycling technologies, organic waste recovery, and establishing repair and re-use networks. Additionally, pollution prevention and control efforts address ecological economy practices, marine litter reduction, and sustainable resource use.

Competitiveness of Enterprises, Employment/Labour Market, SME & entrepreneurship This topic covers labour market development and employment, focusing on creating job opportunities, optimizing existing jobs, and addressing academic (un)employment and job mobility. It also includes attracting a skilled workforce and improving working conditions for various groups.

Strengthening small and medium-sized enterprises (SMEs) and boosting entrepreneurship are key priorities. This includes enhancing SME capacities, supporting social entrepreneurship, and promoting innovative business models.

Activities may focus on creating advisory systems for start-ups, spin-offs, and incubators, fostering business networks, and improving the competitiveness of SMEs through knowledge and technology transfer, digital transformation, and sustainable business practices.

Demographic Change, European Citizenship, Migration This topic focuses on fostering community integration and strengthening a common identity by promoting social cohesion, positive relations, and the development of shared spaces and services. It supports initiatives that enhance intercultural understanding and cooperation between different societal groups.

Digitalisation, Digital Society, ICT All projects where ICT has a significant role, including tailor-made ICT solutions in different fields, as well as digital innovation hubs, open data, Internet of Things; ICT access and connecting (remote) areas with digital infrastructure and services; services and applications for citizens (e-health, e-government, e-learning, e-inclusion, etc.); services and applications for companies (e-commerce, networking, digital transformation, etc.).

Disaster Prevention, Resilience, Risk Management This is about the mitigation and management of risks and disasters, and the anticipation and response capacity towards the actors regarding specific risks and management of natural disasters, for example, prevention of flood and drought hazards, forest fire, strong weather conditions, etc.. It is also about risk assessment and safety.

Education & Training, Children & Youth, Media This topic focuses on enhancing education, training, and opportunities for children, youth, and adults. It covers the expansion of educational access, reduction of barriers to education, and improvement of higher education and lifelong learning. It also includes vocational education, common learning programs, and initiatives supporting labour mobility and educational networks.

Additionally, it addresses the promotion of media literacy, digital learning tools, and the development of innovative educational approaches to strengthen knowledge, skills, and societal participation. This topic emphasizes the role of culture and media in education and social development. It supports initiatives that foster creativity, cultural awareness, and artistic expression among children and youth.

Activities include promoting cross-border cooperation in the audiovisual sector, enhancing digital content creation skills, and boosting the distribution of educational and cultural media products. Furthermore, it encourages the development of media literacy initiatives, helping young audiences critically engage with digital and media content.

By connecting education, creativity, and media, this topic strengthens cultural identity and supports inclusive, knowledge-based societies. Energy Efficiency, Renewable Energy This topic covers actions aimed at improving energy efficiency and promoting the use of renewable energy sources. It includes energy management, energy-saving methods, and evaluating energy efficiency measures.

Projects may focus on the energy rehabilitation and efficiency of buildings and public infrastructure, as well as promoting energy efficiency through cooperation among experienced firms, institutions, and local administrations. In the field of renewable energy, this encompasses the development and expansion of wind, solar, biomass, hydroelectric, geothermal, and other sustainable energy sources.

Activities include increasing renewable energy production, enhancing research capacities, and developing innovative technologies for energy storage and management. Projects may also address sustainable regional bioenergy policies, financial instruments for renewable energy investments, and the establishment of cooperative frameworks for advancing renewable energy initiatives.

Equal Rights, Human Rights, People with Disabilities, Social Inclusion This topic focuses on promoting equal rights and strengthening social inclusion, particularly for marginalized and vulnerable groups. It covers activities enhancing the capacity and participation of children, young people, women, elderly people, and socially excluded groups.

Activities can address the creation of inclusive infrastructure, improving access and opportunities for people with disabilities, and fostering social cohesion through innovative care services. It also includes initiatives supporting victims of gender-based violence, promoting human rights, and developing policies and tools for social integration and equal participation in society.

Health, Social Services, Sports This area focuses on improving health and social services, enhancing accessibility and efficiency for diverse groups such as the elderly, children, and people with disabilities. It includes the development of new healthcare models, innovative medical diagnostics and treatments (e.g., dementia, cancer, diabetes), and the management of hospitals and care facilities.

Additionally, activities addressing rare diseases, promoting overall wellbeing, and fostering preventive health measures fall under this theme. It also covers sports promotion, encouraging physical activity as a means to improve public health and social inclusion. Justice, Safety & Security This area focuses on strengthening justice, safety, and security through cross-border cooperation and institutional capacity-building.

It includes initiatives aimed at improving the efficiency and effectiveness of police, fire, and rescue services, enhancing civil protection systems, and rapid response capabilities for emergencies like chemical, biological, radiological, and nuclear incidents. Activities also target the prevention and combatting of organized crime, drug-related crimes, and human trafficking, as well as ensuring secure and efficient border management.

Furthermore, it covers initiatives promoting the protection of citizens, community safety, and the development of innovative security services and technologies. Mobility & Transport This area focuses on the development and improvement of transport and mobility systems, covering all modes of transport, including urban mobility and public transportation.

Actions aiming at improving transport connections through traffic and transport planning, rehabilitation and modernisation of infrastructure, better connectivity, and enhanced accessibility. Projects promoting multimodal transport and logistics, optimising intermodal transport chains, offering sustainable and efficient logistics solutions, and developing multimodal mobility strategies.

Also, initiatives establishing cooperation among logistic centres and providing access to clean, efficient, and multimodal transport corridors and hubs. Please leave this field blank The deadline for this call has expired.

Robust and trustworthy GenerativeAI for Robotics and industrial automation (AI/Data/Robotics & Made in Europe Partnerships) Horizon Europe: Cluster 4 - Digital, Industry and Space HORIZON-CL4-2025-03-DIGITAL-EMERGING-07 Estimated EU contribution per project between € 40,000,000. 00 and € 45,000,000.

00 Funding Program Horizon Europe: Cluster 4 - Digital, Industry and Space Call number HORIZON-CL4-2025-03-DIGITAL-EMERGING-07 deadlines Opening 02. 10. 2025 17:00 Funding rate 100% Call budget € 85,000,000.

00 Estimated EU contribution per project between € 40,000,000. 00 and € 45,000,000. 00 Link to the call ec.

europa. eu Link to the submission ec. europa.

eu Proposals integrating Generative AI in robotics and industrial automation are expected to substantially contribute to productivity gains, including for instance in engineering industries, the automotive sector, food production or other sectors related to manufacturing industries. All proposals will have to demonstrate their expected impact on the competitiveness of the selected application sector.

The budget will be split in a balanced way between area Type A and Type B defined below. Proposals should clearly identify the area they are addressing. Proposals aiming for Type A outcomes should adhere to the Type A scope, while proposals aiming for Type B outcomes should follow the Type B scope.

While it is widely acknowledged that current use of generative AI has the potential to impact certain tasks in robotics such as improving user interaction or providing explanations about why a robot system made a particular decision, these are, in general, not within the critical operating flow of a robot.

To reach next level of autonomy, generative AI must also enable robots to learn from their experiences, simulate realistic environments for training in challenging conditions, and enhance planning, decision making and control while considering the physical constraints imposed both by the environment and by the physical construction of the robot.

This includes integrating 'Human-in-the-loop' mechanisms, where AI systems collaborate with human operators to enhance decision-making processes and adaptability, particularly in dynamic environments. This represents a significant advancement in robotics, requiring the development of AI models that can effectively navigate the complexities of the physical world while ensuring safety.

Generative AI is expecting to bring such a step-change in robots precision, adaptability, versatility and robustness, enabling them to efficiently achieve real world tasks such as complex moves (navigation, manipulations, etc.) with higher level of autonomy and precision.

In the context of advancing robotics capabilities, the use of generative AI stands as a transformative force, amplifying robots’ learning, interaction, and operational abilities. By enabling robots to learn from experiences, simulate diverse environments for training, and enhance human-robot interaction, it drives adaptability and efficiency.

Additionally, generative AI facilitates the augmentation of robot situational awareness and planning capabilities, empowering them to predict outcomes of various actions, thereby elevating their autonomy and decision-making prowess. Training current generative AI models, in particular Large AI models, requires high volumes of data to achieve effective levels of performance.

The vast amount of data required present a significant challenge when it comes to robotics. Further research is necessary to find the appropriate balance between the quality, adequacy, and volume of data with regards to the performance of the AI model. Moreover, model distillation techniques may play a key role for the portability of the generative AI solution at the edge, in power-limited devices.

The training data should come from the real world or from physical aware simulations of the real world. Where relevant, in particular in the context of human interaction, training data should encompass diverse individual characteristics, such as gender, age, racial and ethnical background, to mitigate potential bias and discriminations.

Proposals should detail strategies to leverage cutting-edge generative AI techniques to enhance the adaptability and reliability of these models across complex and dynamic scenarios, as well as how to ensure human-centricity and environmental considerations. The goal is to train and fine-tune generative AI models that meet the necessary standards for ensuring the safe operation of robotics hardware.

These models should empower robots to autonomously plan and execute actions while maintaining high levels of performance and generalization capabilities. Research activities should explore the training methodologies for these foundation models, emphasizing their ability to process multimodal data and derive actionable insights to inform robotic decision-making processes.

The proposals are also expected to include the validation of the trained models through applications. Proposals should detail methodologies for conducting rigorous testing procedures, incorporating both simulation-based evaluations and physical experiments. These tests aim to evaluate the performance and scalability of developed foundation models.

The research will be driven by impactful scenarios defined by major manufacturing industry players who should be well integrated in the consortium. They should be deeply involved in the proposed work in order to provide the use-case, the corresponding data and they will play an important role to accompany the validation process.

They will define a number of representative real-world use-cases with gradually increased level of complexity to drive the technology development. They will provide existing relevant data and collect further data necessary to train and fine-tune the models, but also to validate the solutions.

Given the sensitivity of sharing industrial data, manufacturers present in the consortium have to define upfront mechanisms to collectively provide and pool a sufficiently large dataset for training the models (this might involve a trusted third party as intermediary), ensuring sufficient quality and quantity of data needed to train the models.

If necessary, they will have to put in place mechanisms to acquire data from sources outside the consortium. Proposals should address both the safety of robotic operations, ensuring protection against physical risks, and cybersecurity measures to safeguard against digital threats and ensure system integrity.

The emphasis lies in creating and disseminating general-purpose models and tools rather than being limited to narrowly focused solutions.

Projects should also build on or seek collaboration with existing and upcoming projects and develop synergies and ensure complementarities with other relevant European (e.g. projects funded under HORIZON-CL4-2024-HUMAN-03-01: Advancing Large AI Models: Integration of New Data Modalities and Expansion of Capabilities), national or regional initiatives, funding programmes and platforms.

The objective is to enhance productivity and provide a competitive advantage to EU industry in the transition towards more sustainable, zero-carbon production, addressing the uncertainties and tensions on supply chains and the lack of highly-skilled workers.

A new generation of digital technologies will integrate generative Artificial Intelligence, robotics, and advanced human interfaces in industry-grade applications with a high degree of autonomy.

This will enable the development, production, and operation of complex and advanced high-tech products at lower cost while improving sustainability and flexibility, ultimately becoming a powerful tool for accelerating innovation in both processes and products.

The manufacturing sector should strongly benefit from increased levels of automation made possible by breakthroughs provided by AI, in particular by the family of technologies know as generative AI, including (e.g.) AI foundation models, large language models, transformers, multimodal generative AI.

The main objective of this Type B is the development of Generative AI solutions dedicated to the manufacturing sector and making use of manufacturing data available in production lines.

Proposals should address at least one of the following use-cases: Robustness and trustworthiness of digital technologies and data management at industry-grade quality, to raise the automation levels on production sites and across industry and supply chains; Enhanced product and process qualification/certification and compliance assessment through higher levels of automation, digitalisation and data management, taking into account related requirements; Automation of manufacturing processes to achieve higher reliability, efficiency and sustainability; Automated tools for fast and large-scale deployment and reconfiguration of production assets and for rapid innovation cycles.

Proposals should accomplish these objectives exploiting the most suitable approach(es) among the ones described below: The integration of applications exhibiting advanced developments of generative AI model(s) specifically designed for manufacturing, providing measurable advantages in one of more of these key areas: manufacturing cost, increased productivity, quality, flexibility, resilience, sustainability, circularity, time to market and usability.

Applications can target factory-floor operations and/or management of data, knowledge and documentation associated to products and production (for use-case 1 or 2); Development and integration of digital production systems capable of significantly increasing productivity and managing high-mix production with close to zero time needed for re-purposing and capability to manage different mixes of materials and components (for use-case 3); Development of deployment tools to automate the management of production lines, namely through automatic configuration, integration with legacy systems, placement of data translators and connectors, and deployment of machines and sensors on the shop floor (for use-case 4).

Proposals should indicate which approach they are targeting. Proposals may combine several approaches above, indicating which is the main approach, provided there is added value in such a combined approach; arbitrary combinations without integration are excluded. The use of generative AI techniques is encouraged for all the approaches.

The applicants will specifically describe how they will secure the acquisition of quality manufacturing data from real-world industrial use cases of industry partners or companies outside the consortium in the context of the data volume necessary to train and finetune the models used in the proposal. For both Type A and Type B projects, proposal should allocate up to EUR 30 million towards the development of the foundation model.

Each project is anticipated to focus on up to six use cases. A minimum of EUR 10 million of the proposal budget must be allocated via FSTP for the fine-tuning phase. This phase aims to create Generative AI applications tailored to impactful industry-driven use cases.

FSTP may be foreseen for up to EUR 2 million per use case, either for a single company (including SME/Start-up), user industry providing their data and use-case, or to a small consortium complementing such user industry company with one or two additional partners, such as AI developer/integrator.

Such FSTP initiatives will develop mini-projects, working in close collaboration with the consortium partners, that will dedicate sufficient resources to support such FSTP projects, in order to develop advanced applications and demonstrate with quantitative KPIs the power of Generative AI solutions.

These mini-projects will include data preparation, fine-tuning, validation of the Generative AI solution in the selected impactful use-cases. Where relevant, interoperability for data sharing should be addressed, focusing on open specifications and standards, enabling effective cross-domain data communities, and new data-driven markets.

If high computing resources are necessary, for both Type A and Type B proposals the primary source of computing resources for pretraining should be sought from external high-performance computing facilities such as EuroHPC or National centres. The proposal should describe convincingly the strategy to access these computing resources. When possible, proposals should build on and reuse public results from relevant previous funded actions.

Additionally, proposals should leverage the tools available for the AI and robotics community on the AI on demand platform. Communicable results should be shared with the European R&D community through the AI-on-demand platform, and if necessary, other relevant digital resource platforms to bolster the European AI, Data, and Robotics ecosystem by disseminating results and best practices.

This topic implements the co-programmed European Partnerships on AI, Data, and Robotic (ADRA) and Made in Europe and all proposals are expected to allocate tasks for cohesion activities with ADRA and the CSA HORIZON-CL4-2025-03-HUMAN-18: GenAI4EU central Hub. Proposals should also build on or seek collaboration with existing projects and develop synergies with other relevant International, European, national or regional initiatives.

Expected effects and impacts Type A: Proposals are expected to enhance the accuracy and robustness of generative AI systems in robotics, ensuring that the solutions developed are trustworthy and reliable in their applications, hence in line with the AI Act requirements. Type B: Proposed projects should aim to develop models that align with European values and principles and regulation, including the AI Act.

Research should build on existing standards or contribute to standardisation, particularly addressing the needs and requirements of the industry. Proposals are expected to address one area of the expected outcomes, either Type A or Type B. The type should be clearly identified within the proposal.

Type A GenAI4EU : Generative AI for Robotics for industrial automation.

Project results are expected to contribute to all the following expected outcomes: Development of advanced foundation models for robotics, fostering increased autonomy and generalization capabilities, thus enabling robots to dynamically learn and comprehend their physical surroundings in real-time, ensuring adaptability and reliability across diverse and complex scenarios.

Validation of the model through fine-tuning and downstream application to address industrial automation use-cases Type B Trustworthy and robust generative AI for improved manufacturing.

Project results are expected to further advance foundation models and reliable industrial solutions and to contribute to some of the following expected outcomes, depending on the use-cases addressed in the proposals: Increased productivity by high quality, flexible and resource-efficient industrial automation, both on the shop floor and in engineering/business processes; Significantly improved facilitation of product and process certification and compliance assessment, as well as reliability, efficiency and sustainability of manufacturing processes, supporting easier high-mix production and manufacturing of products based on sustainable and advanced technologies; and Significantly facilitated installation, commissioning and decommissioning of production facilities, through tools that enable faster industrialisation of factory automation well beyond the pilot phase, while reducing the need for manual on-site interventions.

Applicants will justify their selection by the expected business dimension of their use cases, while ensuring a critical mass of resources in the project to ensure significant outcomes in these.

short description Proposals integrating Generative AI in robotics and industrial automation are expected to substantially contribute to productivity gains, including for instance in engineering industries, the automotive sector, food production or other sectors related to manufacturing industries. All proposals will have to demonstrate their expected impact on the competitiveness of the selected application sector.

Call objectives The budget will be split in a balanced way between area Type A and Type B defined below. Proposals should clearly identify the area they are addressing. Proposals aiming for Type A outcomes should adhere to the Type A scope, while proposals aiming for Type B outcomes should follow the Type B scope.

While it is widely acknowledged that current use of generative AI has the potential to impact certain tasks in robotics such as improving user interaction or providing explanations about why a robot system made a particular decision, these are, in general, not within the critical operating flow of a robot.

To reach next level of autonomy, generative AI must also enable robots to learn from their experiences, simulate realistic environments for training in challenging conditions, and enhance planning, decision making and control while considering the physical constraints imposed both by the environment and by the physical construction of the robot.

This includes integrating 'Human-in-the-loop' mechanisms, where AI systems collaborate with human operators to enhance decision-making processes and adaptability, particularly in dynamic environments. This represents a significant advancement in robotics, requiring the development of AI models that can effectively navigate the complexities of the physical world while ensuring safety.

Generative AI is expecting to bring such a step-change in robots precision, adaptability, versatility and robustness, enabling them to efficiently achieve real world tasks such as complex moves (navigation, manipulations, etc.) with higher level of autonomy and precision.

In the context of advancing robotics capabilities, the use of generative AI stands as a transformative force, amplifying robots’ learning, interaction, and operational abilities. By enabling robots to learn from experiences, simulate diverse environments for training, and enhance human-robot interaction, it drives adaptability and efficiency.

Additionally, generative AI facilitates the augmentation of robot situational awareness and planning capabilities, empowering them to predict outcomes of various actions, thereby elevating their autonomy and decision-making prowess. Training current generative AI models, in particular Large AI models, requires high volumes of data to achieve effective levels of performance.

The vast amount of data required present a significant challenge when it comes to robotics. Further research is necessary to find the appropriate balance between the quality, adequacy, and volume of data with regards to the performance of the AI model. Moreover, model distillation techniques may play a key role for the portability of the generative AI solution at the edge, in power-limited devices.

The training data should come from the real