National Artificial Intelligence Research Resource (NAIRR ) Software Workshop

America/Chicago
TCS Conference Center (Argonne National Laboratory)

TCS Conference Center

Argonne National Laboratory

Building 240 9700 S. Cass Avenue Lemont, IL 60439
Dhabaleswar (DK) Panda (Ohio State University), Michael Papka (University of Illinois Chicago / Argonne National Laboratory), NAIRR Workshop
Description

Workshop Charge: The National AI Research Resource (NAIRR) Task Force has called for democratizing access to artificial intelligence, emphasizing the urgent need to break down barriers to AI capabilities. With the backing of the National Science Foundation’s Office of Advanced Cyberinfrastructure and the Department of Energy’s Advanced Scientific Research Computing program, we are organizing a workshop to help define an AI software stack that supports the following NAIRR goals:

  1. Spurring Innovation: Facilitating cutting-edge AI developments that foster scientific advancements.
  2. Increasing Diversity of Talent: Broadening participation across various demographics enriches the AI community with diverse perspectives.
  3. Improving Capacity: Enhancing the ability of individuals and organizations to utilize AI effectively and efficiently.
  4. Advancing Trustworthy AI: Promoting AI systems that are ethical, transparent, and trustworthy.

Workshop Objectives: The workshop aims to define a comprehensive AI software stack that includes computer programs, training and inference frameworks, libraries, user interfaces, debuggers, and performance tools. This stack should be accessible to a broad audience and adaptable to the evolving needs of the scientific community over a 2-5-year timescale. Key areas of focus will include:

  • Real-Time Data Analysis: Addressing the needs for real-time processing and decision-making using AI in scientific applications.
  • Privacy and Security: Ensuring AI applications meet rigorous privacy and security standards.
  • Foundation Models and Libraries: Incorporating cutting-edge models and libraries, including mixed precision and emerging AI hardware platforms.
  • Software Portability: Enabling software to be portable across diverse hardware platforms, considering variability in hosting needs, data formats, standards, and privacy policies.
  • Data and Model Curation: Integrating robust protocols for the collection, validation, annotation, and maintenance of datasets and models within the software stack to ensure high-quality, relevant, and up-to-date resources for AI research and development.

The workshop will:

  • Identify AI Software Needs: Provide a detailed understanding of AI software requirements across various domains and user groups.
  • Leverage Existing Software Stacks: Incorporate proven solutions from academia, laboratories, and industry to enhance the NAIRR stack’s robustness.
  • Set Priorities for Development: Establish clear priorities for developing and deploying the software stack, focusing on critical components and functionalities.
  • Define Integration Processes: Outline procedures for integrating new software into the NAIRR stack, ensuring its continued relevance and effectiveness.
  • Promote Ethical AI Practices: Emphasize the importance of ethical, transparent, and trustworthy AI systems in scientific research.

 

 

Administrative Contact: Julie Smagacz