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Call key data

Advancing Large AI Models: Integration of New Data Modalities and Expansion of Capabilities (AI, Data and Robotics Partnership) (RIA)

Funding Program

Horizon Europe - Cluster 4 - Destination 6: A Human-centred and Ethical Development of Digital and Industrial Technologies

Call number

HORIZON-CL4-2024-HUMAN-03-01

deadlines

Opening
23.04.2024

Deadline
18.09.2024 17:00

Funding rate

100%

Call budget

€ 50,000,000.00

Estimated EU contribution per project

€ 25,000,000.00

Link to the call

ec.europa.eu

Link to the submission

ec.europa.eu

Call content

short description

This topic centres around the development of innovative multimodal large AI models, covering both the training of foundation models and their subsequent fine-tuning. These models should show superior capabilities across a wide array of down-stream tasks. The emphasis is both on integrating new input data modalities into large AI models and on developing multimodal large AI models with either significantly higher capabilities and/or the ability to handle a greater number of modalities.

Call objectives

Large artificial intelligence (AI) models refer to a new generation of general-purpose AI models (i.e., generative AI) capable of adapting to diverse domains and tasks without significant modification. Notable examples, such as OpenAI's GPT-4V and META’s Llama 2 or DinoV2, have demonstrated a wide and growing variety of capabilities.

The swift progression of large AI models in recent years holds immense potential to revolutionize various industries, due to their ability to adapt to diverse tasks and domains. For them to achieve their potential, access to vast data repositories, significant computing resources, and skilled engineers is required. A promising avenue of research is the development of multi-modal large AI models that can seamlessly integrate multiple modalities, including text, structured data, computer code, visual or audio media, robotics or IoT sensors, and remote sensing data.

Projects should contribute to reinforcing Europe's research excellence in the field of large AI models by driving substantial scientific progress and innovation in key large AI areas. This includes the development of novel methods for pretraining multimodal foundation models. Additionally, novel approaches to effective and efficient fine-tuning of such models should be pursued.

Research activities should explore innovative methodologies for enhancing the representation, alignment, and interaction among the different data modalities, thereby substantially improving the overall performance and trustworthiness of these models. Advances in efficient computation for the pre-training, execution and fine-tuning of foundation models to reduce their computational and environmental impact, and increasing the safety of models are also topics of interest.

Proposals should outline how the models will incorporate trustworthiness, considering factors such as explainability, security, and privacy in line with provisions in the upcoming Artificial Intelligence Act. Additionally, the models should incorporate characteristics that align with European values, and provide improved multilingual capabilities, where relevant.

Proposals should address at least one of the following focus areas:

  • the integration of innovative modalities of data for large AI models during training and inference. Examples of innovative modalities include event streams, structured data and sensor measurements. The incorporation of such new modalities could potentially bring unforeseen enhancements to model performance and enable their application in new domains like weather forecasting, robotics, and manufacturing.
  • enhanced multimodal models that exceed the current state of the art, with either significantly improved capabilities or the ability to handle a larger number of modalities. This focus area also encompasses models capable of multi-modal output generation. Current large-scale multimodal models most commonly engage with only vision and language.

Each proposal is expected to address all of the following:

  • Data Collection, Processing and Cross-modal Alignment. The proposal should describe convincingly the characteristics and availability of the large, trustworthy data sources, as well as the trustworthy data processing to be utilised within the project, detailing the data processing steps to ensure reliability, accountability and transparency, and the alignment of data among the different modalities. A modest portion (up to 10%) of the budget may be allocated to data collection activities; proposals may involve relevant data owners in this task, if necessary. Importantly, the proposal should delineate how potential privacy and IPR issues associated with the data will be managed and mitigated.
  • Multimodal Foundation Model Pretraining. The pretrained multimodal foundation model is expected to demonstrate high capabilities across a wide range of tasks. The pretraining tasks used should be agnostic of down-stream tasks. These activities also cover the development of the codebase and implementation of small-scale experiments. A minor portion (up to 10%) of the budget may be allocated for the acquisition of computing resources for codebase development and small-scale experiments, though 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.
  • Fine-Tuning of Multimodal Foundation Models: The proposal should clearly detail the activities pursued to fine-tune the model for diverse downstream tasks demonstrating illustrative potential use-cases. The tasks' output may either be of a single modality or multimodality. Research activities should investigate innovative methodologies designed to bolster the interplay between different data modalities, thereby enhancing the overall performance of these models.
  • Testing and Evaluation: The proposal should detail the development of workflows, benchmarks, testing procedures, and pertinent tools for evaluating both foundation and fine-tuned models. Attention should be paid to the performance, transparency, bias, robustness, accuracy, and security of the models, through appropriate testing procedures (e.g., red teaming for safety and security), in compliance with the future AI Act.

Proposals should adopt a multidisciplinary research team, as appropriate, to cover all the above issues.

Proposals should adhere to Horizon Europe's guidelines regarding Open Science practices as well as the FAIR data principles. Open access should be provided to research outputs - including training datasets, software tools, model architecture and hyperparameters, as well as model weights - unless a legitimate interest or constraint applies. Additionally, proposals are encouraged to deliver results under open-source licenses.

All proposals are expected to embed mechanisms to assess and demonstrate progress (with qualitative and quantitative KPIs, benchmarking and progress monitoring, including participation to international evaluation contests, as well as illustrative application use-cases demonstrating concrete potential added value), and share communicable results with the European R&D community, through the AI-on-demand platform, and Common European data spaces, and if necessary other relevant digital resource platforms in order to enhance the European AI, Data and Robotics ecosystem through the sharing of results and best practice.

Proposals are also expected to dedicate tasks and resources to collaborate with and provide input to the open innovation challenge under HORIZON-CL4-2023-HUMAN-01-04. Research teams involved in the proposals are expected to participate in the respective Innovation Challenges.

This topic implements the co-programmed European Partnership on AI, data and robotics.

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Expected results

Projects are expected to contribute to one or more of the following outcomes:

  • Enhanced applicability of large AI systems to new domains through the integration of innovative data modalities, such as sensor measurements (e.g. in robotics, IoT) or remote sensing (e.g. earth observation), as input.
  • Improvement of current multimodal large AI systems capabilities and expansion of the number of data modalities jointly handed by one AI system, leading to broader application potential and improved AI performance.

Eligibility Criteria

Regions / countries for funding

EU Member States, Overseas Countries and Territories (OCT)
Moldova (Moldova), Albania (Shqipëria), Armenia (Հայաստան), Azerbaijan (Azərbaycan), Belarus (Беларусь), Bosnia and Herzegovina (Bosna i Hercegovina / Босна и Херцеговина), Faeroes (Føroyar / Færøerne), Georgia (საქართველო), Iceland (Ísland), Israel (ישראל / إِسْرَائِيل), Kosovo (Kosova/Kosovë / Косово), Montenegro (Црна Гора), Morocco (المغرب), New Zealand (Aotearoa), North Macedonia (Северна Македонија), Norway (Norge), Serbia (Srbija/Сpбија), Tunisia (تونس /Tūnis), Türkiye, Ukraine (Україна), United Kingdom

eligible entities

Education and training institution, International organization, Non-Profit Organisation (NPO) / Non-Governmental Organisation (NGO), Other, Private institution, incl. private company (private for profit), Public Body (national, regional and local; incl. EGTCs), Research Institution incl. University, Small and medium-sized enterprise (SME)

Mandatory partnership

Yes

Project Partnership

To be eligible for funding, applicants must be established in one of the following countries:

  • the Member States of the European Union, including their outermost regions
  • the Overseas Countries and Territories (OCTs) linked to the Member States
  • third countries associated to Horizon Europe - see list of particpating countries

Only legal entities forming a consortium are eligible to participate in actions provided that the consortium includes, as beneficiaries, three legal entities independent from each other and each established in a different country as follows:

  • at least one independent legal entity established in a Member State; and
  • at least two other independent legal entities, each established in different Member States or Associated Countries.

Any legal entity, regardless of its place of establishment, including legal entities from non-associated third countries or international organisations (including international European research organisations) is eligible to participate (whether it is eligible for funding or not), provided that the conditions laid down in the Horizon Europe Regulation have been met, along with any other conditions laid down in the specific call topic.

A ‘legal entity’ means any natural or legal person created and recognised as such under national law, EU law or international law, which has legal personality and which may, acting in its own name, exercise rights and be subject to obligations, or an entity without legal personality.

Specific cases:

  • Affiliated entities — Affiliated entities (i.e. entities with a legal or capital link to a beneficiary which participate in the action with similar rights and obligations to the beneficiaries, but which do not sign the grant agreement and therefore do not become beneficiaries themselves) are allowed, if they are eligible for participation and funding.
  • Associated partners — Associated partners (i.e. entities which participate in the action without signing the grant agreement, and without the right to charge costs or claim contributions) are allowed, subject to any conditions regarding associated partners set out in the specific call conditions.
  • Entities without legal personality — Entities which do not have legal personality under their national law may exceptionally participate, provided that their representatives have the capacity to undertake legal obligations on their behalf, and offer guarantees to protect the EU’s financial interests equivalent to those offered by legal persons.
  • EU bodies — Legal entities created under EU law including decentralised agencies may be part of the consortium, unless provided for otherwise in their basic act.
  • Joint Research Centre (‘JRC’)— Where provided for in the specific call conditions, applicants may include in their proposals the possible contribution of the JRC but the JRC will not participate in the preparation and submission of the proposal. Applicants will indicate the contribution that the JRC could bring to the project based on the scope of the topic text. After the evaluation process, the JRC and the consortium selected for funding may come to an agreement on the specific terms of the participation of the JRC. If an agreement is found, the JRC may accede to the grant agreement as beneficiary requesting zero funding or participate as an associated partner, and would accede to the consortium as a member.
  • Associations and interest groupings — Entities composed of members (e.g. European research infrastructure consortia (ERICs)) may participate as ‘sole beneficiaries’ or ‘beneficiaries without legal personality’. However, if the action is in practice implemented by the individual members, those members should also participate (either as beneficiaries or as affiliated entities, otherwise their costs will NOT be eligible.

other eligibility criteria

If projects use satellite-based earth observation, positioning, navigation and/or related timing data and services, beneficiaries must make use of Copernicus and/or Galileo/EGNOS (other data and services may additionally be used). 

In order to achieve the expected outcomes, and safeguard the Union’s strategic assets, interests, autonomy, and security, participation in this topic is limited to legal entities established in Member States, associated countries, OECD and Mercosur countries, countries with which the EU cooperates under a Trade and Technology Council, and countries with which the EU has a Digital Partnership. Proposals including legal entities which are not established in these countries will be ineligible. 

This decision has been taken on the grounds that, in the area of research covered by this topic, EU open strategic autonomy is particularly at stake. It is important to avoid a situation of technological dependency on a non EU source, in a global context that requires the EU to take action to build on its strengths, and to carefully assess and address any strategic weaknesses, vulnerabilities and high-risk dependencies which put at risk the attainment of its ambitions. 

For the duly justified and exceptional reasons listed in the paragraph above, in order to guarantee the protection of the strategic interests of the Union and its Member States, entities established in an eligible country listed above, but which are directly or indirectly controlled by a non eligible country or by a non-eligible country entity, may not participate in the action unless it can be demonstrated, by means of guarantees provided by their eligible country of establishment, that their participation to the action would not negatively impact the Union’s strategic, assets, interests, autonomy, or security.

The participants directly subject to this eligibility condition are not only beneficiaries, affiliated entities and associated partners but also subcontractors. Their participation is therefore subject to an ex-ante ownership control assessment by the EC and, if relevant, the EC acceptance of a guarantee approved by an eligible country. 

Activities are expected to start at TRL 2-3 and achieve TRL 4-5 by the end of the project.

Additional information

Topics

Digitalisation, Digital Society, ICT

Relevance for EU Macro-Region

EUSAIR - EU Strategy for the Adriatic and Ionian Region, EUSALP - EU Strategy for the Alpine Space, EUSBSR - EU Strategy for the Baltic Sea Region, EUSDR - EU Strategy for the Danube Region

UN Sustainable Development Goals (UN-SDGs)

Additional Information

All proposals must be submitted electronically via the Funders & Tenders Portal electronic submission system (accessible via the topic page in the Search Funding & Tenders section). Paper submissions are NOT possible.

Proposals must be complete and contain all parts and mandatory annexes and supporting documents, e.g. plan for the exploitation and dissemination of the results including communication activities, etc.

The application form will have two parts:

  • Part A (to be filled in directly online) contains administrative information about the applicant organisations (future coordinator and beneficiaries and affiliated entities), the summarised budget for the proposal and call-specific questions;
  • Part B (to be downloaded from the Portal submission system, completed and then assembled and re-uploaded as a PDF in the system) contains the technical description of the project.

Annexes and supporting documents will be directly available in the submission system and must be uploaded as PDF files (or other formats allowed by the system).

The limit for a full application (Part B) is 45 pages.

Call documents

Horizon Cluster 4 Work Programme 2024-2025Horizon Cluster 4 Work Programme 2024-2025(3756kB)

Contact

National Contact Points for Horizon Europe
Website

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