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Synopsis

This program will advance scientific community datasets to enable scientific discovery and innovation using artificial intelligence (AI) and other methods. Its goal is to increase the value that can be derived from existing scientific datasets by leveraging novel methods and artificial intelligence (AI).  This will unlock new AI-driven insights. It can enable interdisciplinary research. It also enables investigations outside of the original motivation for data collection and analysis.

The program seeks to 1) apply AI-based capabilities to feature extraction and metadata generation, and the integration of multiple datasets.  2) Develop robust data pipelines necessary for automated analysis of existing datasets and similar use-cases by AI tools and systems. 3) Augment and/or harmonize existing datasets to better enable use by AI data pipelines and automated analysis. 

Proposals should address dataset security and integrity.  Governance and the process for scientific communities to contribute to the datasets should

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Synopsis

The U.S. NSF Directorate for Technology, Innovation and Partnerships (NSF TIP) partners across sectors to advance three primary focus areas – accelerating technology translation and development, fostering regional innovation and economic growth, and preparing the American workforce for future high-wage jobs in STEM fields.

The translation of research to practice ensures that the insights and innovations developed through scientific study and experimentation have tangible, positive impacts for the Nation. These impacts include improving the quality of life, promoting economic and job growth, ensuring national security, and maintaining global competitiveness. Indeed, scientific and engineering breakthroughs have the potential to address critical societal challenges in industries such as aerospace, agriculture, communications, education, energy, healthcare, national security, and transportation – but the translation of discoveries and innovations from the laboratory to society often takes many forms including non-linear pathways.  

The NSF TTP program was developed with

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RSS feed source: National Science Foundation

Synopsis

The NSF FINDERS FOUNDRY program supports collaboration among K-12 educators, technologists, and researchers to develop innovative solutions to persistent challenges in learning and workforce development. These challenges are identified by K-12 students, families, and educators. The program aims to create and scale evidence-based practices, tools, and technologies that improve learning outcomes and prepare students for a digital, Artificial Intelligence (AI)-driven future.

A key focus is early exposure to AI to build curiosity, understanding, and readiness for future careers. The program encourages partnerships across sectors – schools, universities, industry, government, and nonprofits – to co-design responsive, technology-based solutions.

NSF FINDERS FOUNDRY program includes two phases: Planning and Development. Planning proposals help teams explore one of several focus areas. Only teams awarded Planning grants may submit Development proposals, which support the growth and implementation of promising ideas.

The program aligns with national priorities, including the

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