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AI Summary: MIT engineers have developed a deep-learning model capable of predicting the minute-by-minute changes in the arrangement and behavior of individual cells during the early development of fruit fly embryos. The model achieved 90 percent accuracy in forecasting how approximately 5,000 cells would fold and shift during the critical hour of gastrulation. By employing a dual-graph structure that integrates point cloud and foam modeling approaches, the researchers aim to enhance the understanding of tissue development and identify early patterns associated with diseases such as asthma and cancer. Future applications may extend to predicting cell development in other species, including zebrafish and mice.