"artificial intelligence"

User Stories

• Materials Science Artificial Intelligence (AI) Project Supports Data Service Initiative

  Argonne National Lab

  Data Science and Learning Division (DSL) scientists have undertaken a project to develop a lab service for interactive, scalable, reproducible data science, leveraging machine learning methods to reduce simulation costs and increase data quality and value for researchers.

• DLHub: Supporting Machine Learning in Materials Science

  University of Chicago, Argonne National Laboratory

  The Data and Learning Hub for Science (DLHub) serves as an automated facilitator and interconnection point for ML models and associated data transformation and analysis tools. It allows researchers to describe and publish such tools in ways that support discovery and reuse; run published tools over the network (with tools executed on a scalable hosted infrastructure); and link models, other tools, and data sources into complete ML/AI pipelines that can themselves be published, discovered, and run. DLHub relies on Globus services for data management.

• End-end AI Frameworks for Scientific Discovery at Scale

  Argonne National Lab

  Scientists wanted to study gravitational waves, and as a result of the exponential growth of data, days of supercomputing time were needed to keep up with all the data. Models were trained using supercomputers and were then shared and accessed through DLHub. Users then were able to reuse and refine the existing models combined with funcX .

• Global Collaborations Using Machine Learning with MRI Images

  University of Queensland, Australia's Academic and Research Network (AARNet)

  The University collaborates globally on the use of machine learning in an effort to speed up the reconstruction and affordability of Magnetic Resonance Images (MRI). The secure and fast data sharing enabled by Globus allowed for the rapid transfer of large data sets which made collaborations easier and faster.