This $299,889 federal Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences supports research to develop more efficient and environmentally-friendly artificial intelligence (AI) technologies. The University of California, San Diego (UCSD) is the primary awardee and will focus on creating algorithms to compress and quantize neural networks, which are critical components of modern AI applications, in order to reduce their computational demands and environmental impact. The research will explore quantization, pruning, and low-rank approximation techniques underpinned by rigorous mathematical theories to produce compressed neural network models without sacrificing performance. The project aims to enable the broader use of advanced AI on devices with limited resources and in real-time applications. Additionally, the research findings will be integrated into university coursework to help prepare the next generation of mathematicians and engineers in this important field.