查看更多>>摘要:From Washington, D.C., NewsRx journalists report that a patent application by the inventors CHENG, Lin Ni Lisa (New York, NY, US); HUGHES, Sara Margaret (McLean, VA, US); SHANKER, Purva (Arlington, VA, US); TRAGER, Allison (Demarest, NJ, US); WEBB, Shaun Kieran (Oakland, CA, US), filed on July 13, 2022, was made available online on January 18, 2024. The patent’s assignee is Capital One Services LLC (McLean, Virginia, United States). News editors obtained the following quote from the background information supplied by the inventors: “In recent years, the use of artificial intelligence, including, but not limited to, machine learning, deep learning, etc. (referred to collectively herein as artificial intelligence models, machine learning models, or simply models) has exponentially increased. Broadly described, artificial intelligence refers to a wideranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. Key benefits of artificial intelligence are its ability to process data, find underlying patterns, and/or perform real-time determinations. However, despite these benefits and despite the wide-ranging number of potential applications, practical implementations of artificial intelligence have been hindered by several technical problems. First, artificial intelligence often relies on large amounts of high-quality data. The process for obtaining this data and ensuring it is high-quality is often complex and time-consuming. Second, despite the mainstream popularity of artificial intelligence, practical implementations of artificial intelligence require specialized knowledge to design, program, and integrate artificial intelligence-based solutions, which limits the amount of people and resources available to create these practical implementations. Finally, results based on artificial intelligence are notoriously difficult to review as the process by which the results are made may be unknown or obscured. This obscurity creates hurdles for identifying errors in the results, as well as improving the models providing the results. These technical problems present an inherent problem with attempting to use an artificial intelligence-based solution to generate customized user interfaces for users.”