Trillion Parameter Consortium (TPC) Accelerating AI for Science

Realizing the promise of large-scale, 'foundation' models for scientific discovery, supporting activities ranging from self-driving laboratories to hypothesis generation, will require unprecedented scale of computation to train large-scale AI models, coupled with an enormous, inherently multidisciplinary task of preparing diverse scientific data for use in model training. Simply put, only a relatively small number of organizations have the resources to build models at state-of-the-art scales (e.g., trillions of parameters, trained using tens of trillions of tokens). This is already motivating the formation of multi-institutional teams, whose efforts can be accelerated through sharing strategies such as for model architecture, evaluation, and training as well as through collaboratively building and sharing high-quality training data sets. This workshop will highlight such collaborations, which are being catalyzed by the international Trillion Parameter Consortium (TPC). This workshop will highlight progress in various aspects of generative AI for science and engineering with presentations from academics, national laboratories, HPC centers, industry, institutes, and leaders from funding agencies. The workshop will also introduce the structure and strategies of the TPC, with an overview of high-priority areas in which new collaborators can contribute and benefit from joining the consortium.