Peer-to-Peer Transmission Verification Using AI Intent Matching
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Solution Overview
Problem
Conventional peer-to-peer network transmissions lack assurance that resources are transferred to the intended recipient, leading to potential miscommunication and lack of recourse if the wrong entity receives the transmission.
Innovation Solution
Implementing an AI model to verify that the recipient's intent matches the sender's intent by capturing the transmission in a pending queue, requesting recipient input, and executing an AI model to determine a match before releasing the transmission for further processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If peer-to-peer network transmission is implemented for efficient resource sharing, then productivity and ease of operation are improved, but reliability deteriorates because there is no assurance that the transmission reaches the intended recipient
Solution Approach 1:
The system implements a feedback mechanism where the recipient peer node provides feedback about their perceived purpose of the transmission. This feedback is compared with the sender's stated purpose through an AI model to verify whether the transmission reached the intended recipient. The feedback loop ensures transmission accuracy without compromising the efficiency of peer-to-peer resource sharing.
Solution Approach 2:
The system performs preliminary verification actions before completing the transmission. The AI model compares the sender's purpose with the recipient's perceived purpose in advance, and only releases the transmission from the pending queue when a match is confirmed. This preliminary check ensures reliability while maintaining the overall efficiency of the peer-to-peer network.
2Reliability
If an AI model verification system is implemented to ensure transmission accuracy, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent introduces a transmission verification subsystem as an intermediary component that sits between the sender and recipient. This subsystem captures transmissions in a pending queue, coordinates the AI model comparison, and manages the verification process. By acting as an intermediary, it isolates the complexity of the verification mechanism from the core peer-to-peer transmission logic, making the overall system more manageable despite the added complexity.
Data Source
AI summary
Verification of peer-to-peer network transmission occurs implementing AI to determine a match between the purpose/intent of the peer-to-peer network transmission as defined by the sending entity/peer and the purpose/intent of the peer-to-peer network transmission as defined by the recipient entity/peer. The sending peer initiates communication of a peer-to-peer network transmission, which identifies the recipient peer and purpose of the transmission. The peer-to-peer network transmission is captured and held in a transmission pending queue. A push notification is communicated to the recipient entity/peer identified in the transmission, which requests input of their perceived purpose/intent of the transmission. Once the recipient entity/peer identified in the transmission responds with their purpose of the transmission, an AI model trained to determined matches between inputted purposes/intents is executed. Once the AI model determines a purpose/intent match, the transmission is released for the transmission pending queue, so that further communication and/or processing of the transmission occurs.