Encoded Resource Request Weighting for Secure AI Transmission
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Solution Overview
Problem
Individuals and groups face the risk of misappropriation or loss of essential resources, such as information and cryptographic keys, which can be detrimental to their survival in today's society.
Innovation Solution
A resource transmission management tool utilizing a large-language model (LLM) and machine learning (ML) model processes resource transmissions by encoding requests, determining weights, and generating responses to prevent loss, employing sparse one-hot encoding and attention mechanisms to manage resource transmissions effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are transmitted in traditional environments, then resource transmission can occur, but resources risk being misappropriated or lost
Solution Approach 1:
The patent introduces a resource transmission management tool as an intermediary system between resource senders and receivers. This tool encodes resource transmission requests into standardized formats, manages the transmission process, and generates automated responses, thereby preventing resource misappropriation while maintaining manageable system complexity through abstraction
Solution Approach 2:
The patent segments the resource transmission process into distinct components: request encoding, feature extraction, weight assignment based on topology, and automated response generation. This segmentation allows each component to handle specific aspects of security and management independently, improving overall reliability without proportionally increasing complexity
2Reliability
If AI/ML models are used to analyze resource transmissions, then transmission security improves, but processing time increases
Solution Approach 1:
The patent performs preliminary encoding of resource transmission requests into standardized formats and extracts features in advance of the actual transmission and analysis phases. This preliminary processing organizes data in a way that enables faster AI/ML model analysis, reducing processing time while maintaining authentication reliability
Solution Approach 2:
The patent transforms resource transmission requests by encoding them into different parameter representations (features and weights) that are optimized for AI/ML model processing. This parameter transformation enables the models to analyze transmissions efficiently while maintaining high security standards
Data Source
AI summary
A system for implementing a resource transmission management tool that processes resource transmissions, the system comprising a processor that is configured to: obtain a first set of requests that comprises a first resource transmission request; transform the first resource transmission request into a first corresponding encoded resource request; generate, by organizing an arrangement of at least the first corresponding encoded resource request, a pre-processed set of requests that comprises the first corresponding encoded resource request; assign, based on a topology of the pre-processed set of requests, a respectively corresponding weight to each transmission request field; analyze the first corresponding encoded resource request according to associated instructions; and generate a response to the associated instructions based on the analysis.