首页|Patent Application Titled "Systems And Methods For Hierarchical Multi-Label Mult i-Class Intent Classification" Published Online (USPTO 20240054298)
Patent Application Titled "Systems And Methods For Hierarchical Multi-Label Mult i-Class Intent Classification" Published Online (USPTO 20240054298)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting originatin g from Washington, D.C., by NewsRx journalists, a patent application by the inve ntor CHATURVEDI, Isha (Mountain View, CA, US), filed on August 9, 2022, was made available online on February 15, 2024. The assignee for this patent application is Capital One Services LLC (McLean, Vi rginia, United States). Reporters obtained the following quote from the background information supplied by the inventors: "In recent years, the use of artificial intelligence, includin g, but not limited to, machine learning, deep learning, etc. (referred to collec tively herein as artificial intelligence models, machine learning models, or sim ply models) has exponentially increased. Broadly described, artificial intellige nce refers to a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intellig ence. Key benefits of artificial intelligence are its ability to process data, f ind underlying patterns, and/or perform real-time determinations. However, despi te these benefits and despite the wide-ranging number of potential applications, practical implementations of artificial intelligence have been hindered by seve ral technical problems. First, artificial intelligence often relies on large amo unts of high-quality data. The process for obtaining this data and ensuring it i s high-quality is often complex and time-consuming. Second, despite the mainstre am popularity of artificial intelligence, practical implementations of artificia l intelligence require specialized knowledge to design, program, and integrate a rtificial intelligence-based solutions, which limits the amount of people and re sources available to create these practical implementations. Finally, results ba sed on artificial intelligence are notoriously difficult to review as the proces s by which the results are made may be unknown or obscured. This obscurity creat es hurdles for identifying errors in the results, as well as improving the model s providing the results. These technical problems present an inherent problem wi th attempting to use an artificial intelligence-based solution in efficiently la beling user actions in an interactive conversational system."
Artificial IntelligenceBusinessCapit al One Services LLCCyborgsEmerging TechnologiesMachine Learning
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