AI4ES

Objectives

Strategic Objectives

• Collaborate: Strengthen collaboration among network members to build critical mass and maximize the impact of the activities carried out.
• Increase visibility: Give visibility to the AI4ES network to enhance its impact in attracting talent, fostering research careers, and increasing international presence and recognition.
• Define a roadmap: Define and keep updated the technological challenges that Spain faces in the field of Data Value Chain Enabling Technologies.
• Provide infrastructure: Facilitate the launch of new research and experimentation infrastructures for data processing, analysis, and access.
• Transform the economy: Contribute to the transformation of the Spanish economy through the development of projects focused on the implementation and transfer of data-based technologies.
• Energize: Conduct diagnostic, forecasting, training, promotion, dissemination, and communication activities with nationwide reach.

Technological Objectives

• Data Analytics: Research, develop, and experiment with learning models for heterogeneous data (multimodal, from various sources), degraded or low-quality data (missing, insufficient, non-significant, erroneous, anomalous data, etc.).
• AI Development: Explore new continuous learning models and develop new systems and architectures that support their life cycle, enabling the incremental incorporation of new knowledge automatically or with minimal supervision, and that can autonomously adapt to changes in data.
• Cloud and HPC: Research new specialized computing paradigms for developing Artificial Intelligence-based solutions that increase computational efficiency of machine learning algorithms, support real-time computation, and/or distribute computation across nodes, exploring connections with GAIA-X.
• Data Spaces: Research, develop, and experiment with architectures that support the creation of Data Spaces, defining appropriate governance models, and engaging data owners in a trusted environment.