In progress
Any project, supported or not by a committee, that is currently being worked on or is considered active, and will have an end date.
Topics
Foundation models are Artificial Intelligence (AI) models designed to produce a wide variety of outputs. They are capable of a range of possible tasks and applications, such as text, image or audio generation. Foundation models can be standalone systems or can be used as a 'base' for many other applications (i.e. text and image generation).
This project explores the state of the art of foundation models, especially pertaining to their use within the Department of Energy—and how to support the field as it expands.
Description
A National Academies of Sciences, Engineering, and Medicine consensus study will assess the state of the art in foundation models and their use across science research domains relevant to the Department of Energy mission. The study will address the following questions:
- What are some exemplar use cases where foundation models could impact scientific discovery and innovation?
- How can foundation models be used in conjunction with traditional modeling, computational, and data science approaches?
- How can challenges such as verification, validation, uncertainty quantification, and reproducibility best be addressed to advance trustworthy foundation models?
- What are priority research areas for investments to advance the development and use of foundation models in scientific applications? What are the tradeoffs in investing in foundation models versus other mathematical and computational approaches?
Collaborators
Committee
Chair
Member
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Blake Reichmuth
Staff Officer
Sponsors
Department of Energy
Staff
Blake Reichmuth
Lead
