FAIR (Findable, Accessible, Interoperable and Reusable) AI models

Ben Blaiszik, Argonne National Laboratory/UChicago
Ryan Chard, Argonne National Laboratory/UChicago
Murali Emani, Argonne National Laboratory
Avik Roy, University of Illinois at Urbana-Champaign
Misha Salim, Argonne National Laboratory
Aristana Scourtas Argonne National Laboratory/UChicago
Ruike Zhu, University of Illinois at Urbana-Champaign
Webinar Beginner
FAIR AI Models

Trainees will learn how to leverage modern computing environments and advanced scientific data infrastructure (DLHub, funcX and ThetaGPU) to create FAIR AI models.

Day and Time: February 27, 3-5 p.m. US CT

This session is a part of the ALCF AI for Science Training Series