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November 29, 2023 | Tom Ballard

ORNL joins global consortium focused on advancing trustworthy and reliable AI for scientific discovery

The Trillion Parameter Consortium seeks to grow and improve large-scale generative AI models aimed at tackling complex scientific challenges.

Oak Ridge National Laboratory (ORNL) has joined a global consortium of scientists from 60 federal laboratories, research institutes, academia, and industry to address the challenges of building large-scale artificial intelligence (AI) systems and advancing trustworthy and reliable AI for scientific discovery.

The partnership, known as the Trillion Parameter Consortium (TPC), seeks to grow and improve large-scale generative AI models aimed at tackling complex scientific challenges. These include; (1) the development of scalable model architectures and related training strategies, as well as data organization and curation for the training of models; (2) the optimization of AI libraries for current and future exascale computing platforms; and (3) the assessment of progress on scientific task learning, reliability, and trust.

It’s a logical partnership, as ORNL’s documented mission of developing safe, trustworthy, and energy-efficient AI will strengthen the consortium’s goals for responsible AI. Further, the laboratory is home to more than 300 researchers who use AI to tackle challenges of importance to the Department of Energy, and it hosts the world’s most powerful supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.

ORNL’s AI research thrusts, when deployed alongside these resources, will be critical in assisting the consortium in tackling a number of challenges, including:

  • Building an open community of researchers interested in creating state-of-the-art, large-scale generative AI models aimed broadly at advancing progress on scientific and engineering problems by sharing methods, approaches, tools, insights and workflows.
  • Incubating, launching and coordinating projects voluntarily to avoid duplication of effort and to maximize the impact of the projects in the broader AI and scientific community.
  • Creating a global network of resources and expertise to facilitate the next generation of AI and bring together researchers interested in developing and using large-scale AI for science and engineering.

“An integrated and community approach focusing on security, trustworthiness and energy efficiency is crucial to leverage the full potential of AI for scientific discovery and national security,” said Prasanna Balaprakash, ORNL Distinguished R&D Staff Scientist and Director of its AI Initiative. “For this reason, ORNL expects to be a critical resource for the consortium going forward, and we look forward to ensuring the future of AI across the scientific spectrum.”

Specifically, TPC aims to provide the community with a venue in which multiple large model-building initiatives can collaborate to leverage global efforts, with flexibility to accommodate the diverse goals of individual initiatives. The consortium includes teams that are undertaking initiatives to leverage emerging exascale computing platforms to train LLMs — or alternative model architectures — on scientific research including papers, scientific codes and observational and experimental data to advance innovation and discoveries. Trillion-parameter models represent the next great milestone in large-scale scientific AI, as only the largest commercial AI tools currently approach this scale.

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