Globe Ce

Research on "GLOBE" (Global) systems focuses on developing and applying global models across diverse domains, addressing limitations of localized approaches. Current efforts involve creating large-scale datasets encompassing global variations (e.g., accents, solar power generation patterns, genealogical data), and developing deep learning models, including transformers and diffusion models, to leverage this data for improved performance in tasks such as text-to-speech synthesis, solar power forecasting, and question answering. These advancements have significant implications for various fields, improving the accuracy and generalizability of AI systems and enabling more comprehensive analyses of global phenomena.