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NSF’s $20 million investment in AI for geosciences: The U.S. National Science Foundation (NSF) has announced funding for 25 projects totaling over $20 million through the Collaborations in Artificial Intelligence and Geosciences (CAIG) program, aiming to advance AI techniques in geosciences research.

  • The CAIG program seeks to foster transdisciplinary partnerships between geoscientists, computer scientists, mathematicians, and other experts to drive innovative discoveries and solutions in Earth sciences.
  • This investment will support the development and implementation of cutting-edge AI techniques while expanding access to education and training opportunities for using AI in geosciences research.
  • The funded projects align with key technology areas highlighted in the “CHIPS and Science Act of 2022,” including AI, cyberinfrastructure, and advanced computing.

Research focus and innovative AI techniques: The funded projects will employ various AI approaches to tackle complex challenges in Earth systems understanding and analysis.

  • Researchers will utilize generative AI, surrogate models, causal AI, and other advanced techniques to improve geoscience models, enhance natural hazard forecasting, and deepen our understanding of earthquake dynamics.
  • The projects aim to improve natural resource management, enhance decision-making in response to climate change, and elucidate the drivers of physical and biological processes in oceans.
  • Many of the funded initiatives will contribute to the NSF National Discovery Cloud for Climate initiative, a pilot effort to build an integrated national-scale cyberinfrastructure for climate research and education.

Broader impact and alignment with national initiatives: The CAIG program’s funding decisions reflect a commitment to advancing both AI and geosciences while supporting key national priorities.

  • Several projects align with the interagency National AI Research Resource Pilot by making AI resources more accessible and providing education and training for geoscientists at all career stages.
  • The program supports the development of technical capacity in AI and geosciences, addressing the growing need for interdisciplinary expertise in these fields.
  • By fostering collaborations between AI experts and geoscientists, the program aims to accelerate innovations that can address critical challenges in climate change, natural hazards, and Earth system dynamics.

Diverse range of funded projects: The 25 funded projects cover a wide spectrum of geoscience topics and AI applications, showcasing the breadth of potential advancements in the field.

  • Projects include developing AI-driven approaches for understanding earthquake cycles, advancing wildfire science and prediction, and creating large foundational models for earthquake understanding.
  • Researchers will also work on AI-based methods for quantifying uncertainty and inequity in geoscience, empowering AI to reveal phytoplankton community dynamics in coastal oceans, and leveraging AI to observe and predict drivers of mixed layer heat inventory variability.
  • Other notable projects focus on using deep learning to elucidate drivers of global biogeochemical cycles, developing AI emulator tools for extreme weather events, and creating AI research assistants for paleoclimatology.

Implications for future geoscience research: The CAIG program’s investment in AI-driven geoscience research has the potential to revolutionize our understanding of Earth systems and improve our ability to address global challenges.

  • By combining the expertise of geoscientists and AI specialists, these projects may lead to more accurate predictions of natural hazards, improved climate models, and better management of natural resources.
  • The emphasis on education and training will help build a workforce capable of leveraging AI technologies in geoscience research, potentially accelerating future discoveries and innovations in the field.
  • As these projects progress, they may pave the way for new methodologies and tools that could become standard practice in geoscience research, enhancing our ability to study and respond to complex Earth system phenomena.

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