TALP Platform Reversing Payment Flow for Idle Mobile Compute
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Solution Overview
Problem
Current software applications lack a conventional method to transmit value from the application to the user through the platform, resulting in developers losing up to thirty percent of their potential earnings to platform owners, with users typically paying for computational resources rather than being compensated for using their mobile devices.
Innovation Solution
The system utilizes time-affecting linear pathways (TALPs) to execute commercial-grade computations on mobile devices, allowing developers to pay users for the use of their devices' computational capacity, incentivizing device owners through chances to win cash or prizes based on earned processing value, reversing the payment direction and creating a new income stream.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If users pay for computational resources through the platform, then the platform can generate revenue, but developers lose up to thirty percent of their potential earnings to platform fees
Solution Approach 1:
The patent inverts the traditional payment direction by allowing applications to transmit value from the application to the user through the platform. Instead of users paying platform fees that reduce developer earnings, the system enables developers to pay users for computational capacity, with the platform facilitating this reverse payment flow. This inversion resolves the contradiction by eliminating the platform fee burden on developers while still generating platform revenue through the new payment mechanism.
Solution Approach 2:
The platform acts as an intermediary that enables the reverse payment flow from applications to users. The platform's payment transmission mechanism mediates between developers who want to compensate users and users who provide computational resources, allowing value to flow in the opposite direction of traditional platform economics. This intermediary role resolves the contradiction by creating a new revenue stream that doesn't rely on taking cuts from developer earnings.
2Productivity
If mobile devices are used for commercial-grade computation, then computational capacity is utilized, but device owners receive no compensation for using their devices
Solution Approach 1:
The system enables device owners to self-serve by allowing applications to directly compensate them for using their computational capacity. Device owners can specify their availability and compensation preferences, and the system automatically matches them with appropriate computational tasks. This self-service mechanism resolves the contradiction by ensuring device owners receive compensation while maintaining high computational capacity utilization.
Solution Approach 2:
The patent implements a feedback mechanism where device owners receive compensation based on the computational work their devices perform. The system continuously monitors computational capacity usage and provides feedback in the form of payments to device owners, creating a positive reinforcement loop that incentivizes continued participation. This feedback mechanism resolves the contradiction by ensuring device owners are compensated for their computational contributions.
3Adaptability or versatility
If developers pay users for computational capacity, then a new income stream is created, but the payment structure and cost management become complex
Solution Approach 1:
The patent creates a universal payment transmission mechanism that can handle multiple types of value transfers between applications and users through the platform. This multi-functional system supports various payment structures, compensation models, and transaction types within a single framework. The universal mechanism resolves the contradiction by providing a versatile payment infrastructure that manages complexity through standardization rather than requiring separate systems for different payment scenarios.
Data Source
AI summary
System, methods, and computer programs for executing time-affecting linear pathways (TALPs) using distributed mobile applications as platforms. The systems, methods, and computer programs can use currently unused mobile device compute cycles for commercial-grade computation based on TALPs. TALPs can take the place of software functions, modules, and software applications that are provided for the analysis of customer data. TALPs can be used to perform strong parallel processing.


