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May 8, 2024
In the ever-evolving landscape of machine learning and artificial intelligence, data is the fuel that drives innovation and advancement. However, acquiring labeled datasets for training models often poses significant challenges, particularly in domains where data is scarce, expensive, or sensitive. Synthetic datageneration emerges as a powerful solution, offering new possibilities and accelerating progress across various industries, including architecture and development.