EU Frontier AI Initiative: Advanced Scaling Frameworks for High-Performance AI Models (RIA) - Apply AI
Horyzont Europa · Temat konkursu
Podsumowanie
Polska firma może skorzystać z tego naboru na B+R.
Funds research into predictive scaling methods and efficient training and inference for European frontier AI labs.
- Kto może złożyć wniosek
- Źródło nie przesądza.
- Kwota
- 15 mln € na projektBudżet całkowity 15 000 000 €
- Termin
- 16.02.2027 01:00 CETza 115 dni
- Status
- Nadchodzącyotwarcie 20 paź 2026
Ocena maszynowa na podstawie tekstu naboru; warunki sprawdź u źródła.
Opis
Expected Outcome:
This topic aims to advance the scientific and technical foundations for the scaling of AI models, enhancing the performance of training and inference processes and providing European AI labs with the methodologies required to compete at the global frontier. Project results are expected to contribute to some of the following outcomes:
• Establishment of robust scaling laws and predictive frameworks that allow for the reliable estimation of model performance before large-scale compute investment.
• Enhanced competitiveness of European advanced AI models through optimised dataset mixtures, refined architectures, and superior hyperparameter configurations.
• Optimised development for frontier AI models, achieved via automated and scientifically grounded scaling methodologies.
Scope:
To maintain a leading position in AI, Europe must master the methodologies required to scale AI models’ performance, training and inference processes. Establishing a predictive methodology for AI model development ensures that limited computational resources are deployed with maximum efficiency, thereby bolstering the EU and AC’s technological sovereignty.
While previous actions have focused on training High-Performance AI models, this topic addresses the research gap in the underlying theoretical basis, methodologies and tools for predictable scaling of AI models and inference. By providing the technical foundations for high-performance systems without the costs of unguided experimentation, this action complements training-centric efforts. In this light, proposals should deliver, as an outcome of the research, a toolset designed to support the scaling of AI models.
Potential research areas include, but are not limited to:
• Automated Scaling Law Derivation: Research into scaling laws to predict performance across diverse modalities and tasks, moving beyond simple power laws.
• Exploratory Architecture Search: Developing automated methods to discover and refine model architectures that maintain performance while scaling both in training and inference, including innovations in sparsity, memory efficiency, and long-context handling.
• Dataset Mixture Optimisation: Research into the systematic selection, weighting, and sequencing of datasets. This includes developing tools for automated data quality assessment.
• Advanced Hyperparameter Tuning and Stability: Developing methodologies for stable training at large scales, including automated tuning of optimisers and learning rate schedules that remain effective as models grow.
Proposals should ensure that the developed frameworks and scaling methodologies are compatible with diverse hardware architectures, demonstrating that scaling is studied across different systems to avoid optimisation for specific proprietary hardware.
The selected project should actively support Advanced AI labs and High-performance Computing Centres already engaged in the development of frontier AI, ensuring that methodological advances are immediately validated in high-stakes environments. Proposals should describe how these scaling methodologies would benefit the development of models adapted to the specific requirements of particular strategic sectors, such as Public Administration, Manufacturing, Energy, Healthcare, Cultural and Creative Industries, or Physical AI.
Part of the Frontier AI Initiative, this topic complements HORIZON-CL4-2027-04-DIGITAL-EMERGING-11 “EU Frontier AI Initiative: Developing frontier AI solutions that are safe and computationally efficient within Apply AI” by establishing the underlying methodologies required for the large-scale training and inference of High-Performance AI models. Proposals should, therefore, describe the link between their planned activities and the objectives of topic HORIZON-CL4-2027-04-DIGITAL-EMERGING-11.
All proposals are expected to incorporate mechanisms for assessing and demonstrating progress, including qualitative and quantitative KPIs, benchmarking, and progress monitoring. When possible, proposals should build on and reuse public results from relevant previous funded actions. Communicable results should be shared with the European R&D community through the AI-on-demand platform.
The project selected in this topic should link to the resources offered by the AI Factories and the Data Labs. Where relevant, links could be established to European companies developing frontier AI models to foster a pre-competitive exchange of expertise and explore ways to mobilise the wider developer community for the efficient reuse of results.
All proposals are expected to allocate tasks for cohesion activities with the European Partnership on AI, data, and robotics (ADRA) and the CSA HORIZON-CL4-2025-03-HUMAN-18: GenAI4EU central Hub.
Technology Readiness Level - Technology readiness level expected from completed projects
Activities are expected to achieve TRL 4-5 by the end of the project – see General Annex B.
Kto może złożyć wniosek – szczegóły
- Cel
- Badania i innowacje
- Znaczenie dla B+R
- 3 z 3
- Polska kwalifikuje się
- Tak
- Ograniczenie krajów
- —
- Region
- Dowolny
- Konsorcjum
- Niejasne
- Poziom gotowości (TRL)
- 5+ at completion
- Tematy
- Frontier AI models
- Scaling laws
- Training and inference optimisation
- Model architectures
Ocena maszynowa na podstawie tekstu naboru; warunki sprawdź u źródła. 23 paź 2026
Warunki
Fakty wyodrębnione z dokumentów źródłowych w przeglądzie danych Scindu. Każda wartość ma własne warunki. Brak danych oznacza, że źródło nie podaje wartości, a nie zero ani brak limitu.
- Ograniczenie wniosku
- As of the exact SEDIA topic-record notice last changed 2026-10-21T08:56:46.605 and API response captured 2026-10-23T12:31:37Z, submission links for HORIZON-BRIDGING-2027-01 topics were described as not yet available; the Portal said it would publish an update when they become available. This establishes the captured notice only and does not establish availability after the capture.
Applies to this exact topic record and the shared HORIZON-BRIDGING-2027-01 submission-link notice. Planned opening date 2026-10-20 is a separate scheduled date; do not infer that the system opened, closed, or remains unavailable from the date alone. As of 2026-10-23T12:31:37Z only.
- Inny warunek
- Exact action code HORIZON-RIA (Research and Innovation Actions).
- Inny warunek
- Horizon Europe General Annexes describe personnel as actual costs unless declared as a unit cost; they separately list SME-owner/natural-person personnel unit costs, subcontracting as actual costs, purchases as actual costs unless unit cost, and FSTP only if provided by the specific call. Therefore these personnel categories do not turn an external service purchase or subcontract into a hire, and no specific FSTP entitlement is asserted for this topic.
- Inny warunek
- For A.1 employees/equivalent, the HE MGA states annual personnel costs divided by 215 as the daily-rate basis; declared day-equivalents must be identifiable and verifiable. The total declared day-equivalents per person across EU grants in a year cannot exceed 215, minus parental leave time where applicable.
- Inny warunek
- The topic funds research and tool development for predictable scaling of AI models but does not prescribe named staff roles, qualifications, headcount, FTE, employment duration or salaries.
- Poziom gotowości technologicznej na koniec, minimum
- 5
Expected end-project TRL range 4–5; the source does not state staff roles or hiring requirements.
Kwoty i koszty
- Budżet orientacyjny
- 15 000 000 €
Budżet tematu z tabeli budżetowej portalu. Limity na projekt i ryczałty są w warunkach konkursu.
- Koszt kwalifikowalny
- The HE MGA allows nonsalaried SME owners and natural-person beneficiaries to claim personnel costs as unit costs under Annex 2a, subject to general eligibility conditions; the AGA gives a daily-rate formula of EUR 8,745.4 divided by 18 days, multiplied by the applicable country-specific correction coefficient for calls opened on or after 30 July 2024. This is a unit-cost calculation, not an employee salary cap or rate guaranteed for every country.
- Intensywność wsparcia, maksimum
- 100
General maximum for exact HORIZON-RIA action code; call/topic conditions and grant agreement govern; not a staff pay rate.
- Oczekiwane dofinansowanie projektu, do
- 15 000 000 €
Same approximate expected contribution reference; not a guaranteed award, hard minimum, or award cap. The call explicitly allows different requested amounts.
- Oczekiwane dofinansowanie projektu, od
- 15 000 000 €
Approximate expected EU contribution per project; not a guaranteed award, hard minimum, or award cap. The call explicitly allows different requested amounts.
- Alokacja tematu
- 15 000 000 €
Indicative 2027 topic allocation; distinct from expected project contribution and staff budget.
Personel i usługi
Inna rola
Koszt personelu, który grant może sfinansować
Potential fundable personnel category only when the grant conditions and Article 6.2.A.2 apply; assigned to the action, work under conditions similar to an employee, result belongs to beneficiary unless agreed otherwise, and actual direct-contract costs are not significantly different from comparable employees. It is a contractor engagement category, not employee payroll; no qualification, headcount, FTE, duration or rate is set by this topic.
Inna rola
Koszt personelu, który grant może sfinansować
Potential fundable personnel category under the applicable Horizon Europe General MGA, conditional on actual action assignment and all eligibility rules. This is not a call-specific required team, named job, or promise of award. Qualification, headcount, FTE, duration and salary are not stated by the topic. Employee remuneration must be actual and linked to national law/employment terms; daily-rate and reporting rules are described in the cited MGA.
Inna rola
Koszt personelu, który grant może sfinansować
Potential personnel unit-cost category where the applicable grant agreement includes Article 6.2.A.4. Applies only to an SME owner not receiving a salary or a natural-person beneficiary not receiving a salary, with work assigned to the action and general unit-cost conditions met. The daily unit rate is country-adjusted; it is not a salary and this packet does not assert a per-person EUR rate without the recipient country coefficient. No required headcount, FTE, duration or qualification is named in this topic.
Inna rola
Koszt personelu, który grant może sfinansować
Potential fundable personnel category only when the grant conditions and Article 6.2.A.3 apply; assigned to the action, works under conditions similar to an employee and actual costs are not significantly different from comparable beneficiary employees. This is a paid secondment, not a new employment contract with the beneficiary. No call-specific qualification, headcount, FTE, duration or pay rate is stated.
Dokumenty źródłowe
Dane naboru
- Otwarcie
- 20 paź 2026
- Tryb terminów
- Single-stage
- Program
- Horyzont Europa · 2021 - 2027
- Konkurs
- HORIZON-BRIDGING-2027-01 · Bridging actions 2027
- Rodzaje działań
- HORIZON Research and Innovation Actions
- Źródło
- ec.europa.eu
- Sprawdzono
- 23 paź 2026
- Aktualizacja portalu
- 21 paź 2026
- Status przeglądu
- Przegląd częściowy
- Przejrzano
- 23 paź 2026
To skrót ze strony źródłowej, nie tekst urzędowy. Kwalifikowalność, warunki i system składania wniosków są u źródła.