Norma Pushes Quantum Tech-Based AI Lightweighting Strategy Into Full Swing

According to AI TIMES, Norma said on October 12 that it had unveiled its 'QC4AI' strategy to reduce the computational burden of large-scale AI neural networks with quantum technology, and that in its core research it cut an indicator estimating optimization computation burden by 94.5%. The company plans to package together a technology that reduces the repeated calculations of quantum optimization algorithms and a development environment that helps with writing and running quantum programs with AI, with the goal of leading that into neural network lightweighting. The technology it has disclosed at this stage places more weight on laying the groundwork for reducing inefficiencies in quantum computation and the development process than on directly compressing large models themselves. The article also notes that overseas research is continuing into model compression, predictive performance improvements, and training efficiency gains using techniques inspired by quantum mechanics or actual quantum computers. It adds that because each approach differs in its goals and implementation level, they are difficult to compare simply as part of the same trend. Norma aims to expand the scope of these foundational technologies to computationally constrained environments such as physical AI in the future.