Advancements in Artificial Intelligence for Science

·      Scientific programming and scientific-knowledge-management systems;

·      Federated and privacy-preserving training for foundation and other AI models for science; and

·      Energy-efficient AI algorithms and hardware for science.

The development of new AI techniques applicable to multiple scientific domains can accelerate progress, increase transparency, and open new areas of exploration across the scientific enterprise.

SUPPLEMENTARY INFORMATION

AI is one of the most powerful technologies of our time[1] and DOE is at the forefront of research and development in AI technologies for enabling scientific discovery and innovation. Core components of the scientific method remain unchanged: Observation, Hypothesis, Experiments, and Analysis. However, DOE recognizes that abundant sources of data, high-performance computing (HPC) and networking, energy-efficient algorithms, and AI-related technologies can be harnessed to significantly accelerate and expand the impact of scientific research. The breadth of applications spans climate science, cybersecurity and electric grid resilience, biotechnology, microelectronics, disaster response, and beyond. Research to address national priorities will require advances and AI innovations in high-level capabilities such as: monitoring and predicting the onset of real-world anomalies and extreme events; adaptive strategies to control the real-time behavior of complex systems, infrastructure, and processes; approaches for the optimal development and design of physical systems; decision-support for planning, risk, and policy formulation; and tools that synthesize scientific knowledge and accelerate the design, manufacturing, testing, and optimization of new technologies. The focus of ASCR research and development investments is on the underlying approaches for AI-enhanced scientific and engineering capabilities and to significantly transform the scientific method for accelerated discovery and innovation.

Realizing the next generation of AI for science will require innovations in both hardware and algorithms. Future AI-enabled scientific workflows are expected to use Machine Learning (ML) to enhance numerical modeling and data analysis along with technologies that process natural and computer-programming languages. DOE’s exascale supercomputers[2] are some of the Nation’s most powerful systems for large-scale AI training and for tasks integrating AI, modeling, simulation, and data analysis. These exascale and future systems complement the vast array of other AI-enabled HPC and edge systems, including automated laboratories and facilities, that will significantly accelerate scientific progress in the coming decades.

DOE’s scientific community has collectively articulated important research directions toward

realizing the promise of AI for science and other DOE missions in the recently-released AI For Science, Energy, and Security report [1], building on the preceding AI for Science report [2], and complementing the report on Opportunities and Challenges from Artificial Intelligence and Machine Learning for the Advancement of Science, Technology, and the Office of Science Missions [3]. The research directions highlighted in these reports, and others, appear prominently in the National Artificial Intelligence Research and Development Strategic Plan [4]. This FOA addresses a broad spectrum of research priorities described in these documents that are critical to enabling trustworthy AI for scientific applications advancing human understanding and addressing national needs.

[1] For additional background on the promise and importance of AI R&D, see the OMB/OSTP Memorandum on Multi-Agency Research and Development Priorities for the FY 2025 Budget (August 2023) https://www.whitehouse.gov/wp-content/uploads/2023/08/FY2025-OMB-OSTP-RD-Budget-Priorities-Memo.pdf, and the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (October 2023) https://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/

[2] For more information on ASCR’s exascale supercomputers, and other HPC resources, available as national user facilities, see https://science.osti.gov/ascr/Facilities/User-Facilities