This three-year Research Experiences for Undergraduates (REU) site at the University of North Texas will support 10 students for 10 weeks each summer and train them to build artificial intelligence (AI) systems capable of sharing knowledge across domains through vector embeddings. Vector embeddings translate information (e.g., images, text or sound) into numerical data. These data are then converted into lists that allow the numbers to convey context and meaning. Current AI systems who are working in areas such as visual object recognition, speech recognition, and understanding natural language require extensive training, with much of the learned knowledge locked within the structure of the system, which is then difficult to reuse. However, students in this program will focus on creating and leveraging highly-trained AI systems to represent information in ways that preserve the nuanced understanding learned by these systems and make it accessible for other applications. This REU brings together an interdisciplinary team to support projects that showcase the benefits of AI systems that can exchange and reuse learned knowledge. Early in the program, each student will identify a project domain and a faculty advisor with whom they can work. Students will also participate in a long-standing AI summer research program integrating current university students and external REU students to facilitate collaboration across departments and student expertise. Specifically, the training