Brief

Researchers have proposed a new framework called FactoryFlow to improve the reliability of Large Language Model (LLM)-assisted digital twin creation. The framework introduces three core principles: separating structural modeling from parameter fitting, using a restricted intermediate representation (IR) of pre-validated components, and employing a density-preserving IR. The study highlights Python as a suitable density-preserving IR, detailing how its structure can compactly represent complex systems and reduce LLM-induced errors. AI

Researchers have developed a new browser-native GPU architecture for creating interactive MRI digital twins. This decentralized approach bypasses traditional server-side rendering, executing complex 3D simulations directly on low-cost edge GPUs. The system achieves rapid rendering times and stable interactivity, making high-fidelity anatomical models accessible even in resource-constrained environments without relying on deep learning. AI