Language Model Option Selection for Transaction Instrument Comparison
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Solution Overview
Problem
Existing web services and applications that comply with standards such as those set by the World Wide Web Consortium (W3C) are limited to features supported by these standards, often requiring users to manually scroll through numerous transaction options and navigate between tabs to compare terms and conditions, which is inefficient, especially on mobile devices with limited screen area and processing power.
Innovation Solution
Implementing a client-side language model-based option selection framework that leverages locally stored transaction data and histories to seamlessly provide optimized transaction instrument suggestions, overriding the typical sequence of events triggered by standards-compliant transaction handlers, using models like GPT-3 or GPT-4 to predict user preferences and reduce fraudulent transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a standards-compliant transaction handler provides all registered transaction instruments, then users have access to complete transaction options, but users must manually scroll through numerous options and navigate between tabs to compare terms, increasing operation time and complexity
Solution Approach 1:
The system employs an option selection language model that automatically analyzes transaction data and transaction instrument terms to select optimal instruments without requiring manual user comparison. The model self-serves by processing the information and presenting recommended options, eliminating the need for users to manually scroll through and compare numerous transaction instruments.
Solution Approach 2:
The patent replaces the manual mechanical process of scrolling through options and comparing terms with an automated language model-based system. The language model processes transaction data and instrument terms computationally to identify optimal options, substituting human cognitive effort with automated AI-based analysis.
2Adaptability or versatility
If a standards-compliant transaction handler provides all registered transaction instruments, then users have access to complete transaction options, but the interface becomes complex and requires navigation between multiple tabs
Solution Approach 1:
The system extracts and presents only the most relevant transaction instrument options based on the language model's analysis of transaction data and instrument terms. Instead of displaying all registered transaction instruments, the model selectively extracts and highlights the optimal options, simplifying the interface while maintaining access to complete options behind the scenes.
Solution Approach 2:
The patent segments the transaction instrument selection process into two parts: complete options remain available in the background system, while the foreground interface displays only the model-recommended optimal options. This segmentation allows the system to maintain full versatility while presenting a simplified, less complex user interface.
3Reliability
If client-side processing is used for option selection, then user privacy and security are enhanced, but processing power requirements increase on mobile devices
Solution Approach 1:
The system implements partial client-side processing where the language model runs locally on the mobile device to enhance security and privacy. However, the model is designed to process only the essential transaction data and instrument terms needed for option selection, rather than performing exhaustive analysis, thus balancing local processing benefits with energy consumption constraints.
Data Source
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AI summary
Disclosed are various approaches for language model based options selections. In one example, a service (122) can generate a user interface (167) that identifies user interactions received from a client device (106) to register transaction instruments. Transaction facilitation websites (152) can be scraped to identify transaction instrument terms for the registered transaction instruments (173). An option selection language model (126) can be generated and trained to select a subset of the registered transaction instruments (173). The option selection language model (126), the transaction instrument data (172), and the transaction instrument terms (156) can be transmitted to the client device (106).