Researchers have introduced SOMA, a unified parametric human body model that consolidates the strengths of existing models, including SMPL, SMPL-X, and MHR, by standardizing mesh topology, skeletal structure, and shape parameterization1. This unification enables the integration of complementary models within a single pipeline, facilitating more accurate and efficient human reconstruction, animation, and simulation. SOMA's unified framework allows for the exploitation of diverse model strengths, overcoming the limitations of individual models. By providing a standardized foundation, SOMA has the potential to advance various applications, including computer vision, robotics, and healthcare. The development of SOMA underscores the growing importance of standardization in AI-driven technologies, as it enables more seamless collaboration and innovation across disciplines. This matters to practitioners and researchers, as SOMA's unified framework can accelerate the development of more sophisticated and realistic human modeling applications, with implications for fields beyond technology, including policy, security, and workforce dynamics.