The next frontier in AI advancement isn’t just about algorithms—it’s about unlocking the wealth of hidden insights trapped within millions of files in HPC environments. While organizations focus on model architectures, the true bottleneck often lies in discovering and preparing relevant data buried in vast storage systems.
This presentation, featuring
MetadataHub and a live demonstration, will reveal how intelligent metadata extraction and management transforms unstructured data into AI-ready assets by:
- Uncovering Hidden Context: Live metadata extraction demonstrating how MetadataHubcaptures content and contextual value, revealing unexpected connections between research datasets and enabling new AI training opportunities that would otherwise remain hidden.
- Automating Data Discovery: Demonstrating how MetadataHub automates metadata tagging to identify valuable training data across petabyte-scale storage, reducing data preparation time by up to 90%.
- Enhancing Model Quality: Exploring how rich metadata captured by MetadataHub improves AI model performance by providing better context and enabling more relevant training data selection.
- Scaling Efficiently: Showcasing metadata-driven automation with MetadataHub that optimizes data pipeline efficiency and resource utilization, including GPU/CPU performance, across HPC environments.
The session will highlight a real-world success story from the
Zuse Institute Berlin, where
MetadataHub unlocked
200 PB of previously underutilized research data for cutting-edge Generative AI applications. A 15-minute live demonstration will guide attendees through their journey—from data discovery to AI-ready datasets—highlighting practical challenges and solutions.
Attendees will leave with actionable strategies for implementing metadata-driven approaches in their own HPC workflows. By showcasing
MetadataHub’s ability to extract content and contextual value, this session will demonstrate how metadata transforms unstructured data into a strategic advantage, accelerating AI initiatives and driving HPC innovation.
