Trillion Parameter Consortium Workshop: Synthetic Data, Trust, and Scale When Advancing Reliable AI Models for Science

This workshop explores the technical, ethical, and accessibility challenges of using synthetic data for training and evaluating AI models in scientific and engineering applications. It emphasizes building trustworthy and reliable systems while addressing barriers to equitable access, ensuring synthetic data workflows can benefit a global, multilingual community of researchers across diverse domains. A special focus will be on the role of HPC in generating, processing, and validating synthetic data at scale.

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Organizers:

• Javier Aula-Blasco
• Charles Catlett
• Fabrizio Gagliardi
• Laura Morselli
• Per Öster
• Miguel Vazquez