The recent advancements in quantum computing have significantly influenced various research areas, particularly in the fields of quantum AI and financial modeling. Researchers are increasingly exploring the potential of quantum circuits to handle complex computational tasks that are traditionally challenging for classical systems. One notable trend is the application of the transferable belief model within quantum circuits, which offers a more effective approach to uncertainty management compared to traditional Bayesian methods. This shift is driven by the unique capabilities of quantum computing, which can simplify the representation and processing of belief functions. Additionally, quantum computing is being leveraged to tackle complex financial problems, such as multi-period asset allocation, where it demonstrates superior computational efficiency and scalability. The development of quantum programming languages is also progressing, with a focus on creating more intuitive and efficient tools for programming quantum algorithms. These developments collectively suggest a paradigm shift towards integrating quantum computing into mainstream research and applications, particularly in areas requiring high computational power and precision.