Horizon Europe Avrupa Birliği
Neutral-Atom Platform Technologies
This action aims to establish European leadership in neutral-atom quantum simulation and digital quantum computing by delivering: • Fully programmable industry-ready quan…
Horizon Europe · Avrupa Birliği
EU Frontier AI Initiative: Advanced Scaling Frameworks for High-Performance AI Models (RIA) - Apply AI
Açık
AB Ufuk Avrupa programı tarafından 1 hibe bekleniyor; proje başına €15 milyon; toplam bütçe €15 milyon. Başvurular 16 Şubat 2027 tarihinde kapanıyor (AB çağrıları genellikle Brüksel saatiyle 17:00’de kapanır). AB üye ülkelerindeki ve Türkiye gibi ortak ülkelerdeki kuruluşlar genellikle katılabilir; konu koşulları belirleyicidir.
- Son başvuru
- 16 Şubat 2027 (93 gün kaldı)
- Hibe tutarı
- Proje başına €15 milyon
- Destek oranı
- Uygun maliyetlerin %100’ü Bu program için standart kural; çağrı farklı olabilir.
- Toplam bütçe
- €15 milyon
- Beklenen hibe sayısı
- 1
- Faaliyet türü
- HORIZON Research and Innovation Actions · HORIZON Action Grant Budget-Based
- Olası başvuru sahipleri
- Şirketler, KOBİ’ler / girişimler, Kâr amacı gütmeyenler, Üniversiteler ve araştırma, Kamu kurumları Kaynak kategorilerinden veya program kurallarından; uygunluğa çağrı karar verir.
- Fon sağlayıcı
- Horizon Europe (HORIZON)
- Referans
- HORIZON-BRIDGING-2027-01-13
- Çağrı
- HORIZON-BRIDGING-2027-01
- Son kontrol
- 14 Kasım 2026
Resmi açıklamalar fon sağlayıcının dilindedir (çoğunlukla İngilizce); bu sayfadaki özet ve temel bilgiler Türkçedir.
Beklenen sonuçlar
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.
Kapsam
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:
Tam metni oku
• 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…
Kimler başvurabilir
Consortium of at least 3 independent legal entities from 3 different EU Member States or associated countries, at least one in a Member State (Horizon Europe standard rule). Country restriction: participation is limited to legal entities established in Member States, Iceland and Norway and the following additional associated countries : Canada, Israel, Republic of Korea, New-Zealand, United Kingdom, Switzerland and Japan.
Başvuru sahibi kategorileri yalnızca bir başlangıç noktasıdır. Uygunluğa resmi çağrı karar verir.
Konular
Algorithms, distributed, parallel and network algorithms, algorithmic game theory Artificial intelligence, intelligent systems, multi agent systems High performance computing Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
Zamanlama
Single-stage call. Next deadline 2027-02-16. The portal states the exact cut-off time (EU calls usually close at 17:00 Brussels time).
Nasıl başvurulur
- Portaldaki konunun tamamını okuyun: beklenen sonuçlar, kapsam, faaliyet türü ve ülke veya konsorsiyum kısıtlamaları dahil uygunluk koşulları.
- Kuruluşunuzu AB Funding & Tenders Portalına kaydederek her ortak için bir PIC numarası alın.
- İşbirliğine dayalı araştırma ve yenilik projeleri genellikle üç farklı AB üye ülkesi veya ortak ülkeden en az üç bağımsız ortak gerektirir (Türkiye Ufuk Avrupa’ya ortak ülkedir). Bu konudaki kuralı doğrulayın.
- Bölüm A’yı (portalda doldurulan idari formlar ve bütçe) ve Bölüm B’yi (bu faaliyet türü için resmi şablondaki teknik açıklama) hazırlayın.
- Son başvuru günü kapanış saatinden önce portal üzerinden gönderin. Geç başvurular kabul edilmez.
From the call text
- Who can apply
- Not stated in the call text we hold — check the official page
- Company stage
- Not stated in the call text we hold — check the official page
- Single applicant or consortium
- Read the topic conditions on the EU Funding & Tenders Portal for eligible countries, consortium requirements, budget and the application route.
- Where applicants must be based
- Read the topic conditions on the EU Funding & Tenders Portal for eligible countries, consortium requirements, budget and the application route.
- Where to apply
- Read the topic conditions on the EU Funding & Tenders Portal for eligible countries, consortium requirements, budget and the application route.
Resmi kaynaklar
Bu sayfadaki bilgiler resmi kaynaktan alınmıştır ve en son 14 Kasım 2026 tarihinde kontrol edilmiştir. Sonraki değişiklikler dahil, fon sağlayıcının kendi belgeleri her zaman önceliklidir.
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