18055558. Hybrid-Feedback Driven Transpiler System simplified abstract (Bank of America Corporation)
Contents
- 1 Hybrid-Feedback Driven Transpiler System
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Hybrid-Feedback Driven Transpiler System - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
Hybrid-Feedback Driven Transpiler System
Organization Name
Inventor(s)
Utkarsh Raj of Charlotte NC (US)
Paul Jacob Abernathy of Charlotte NC (US)
Vijaya Rudraraju of Charlotte NC (US)
William Cruise of Charlotte NC (US)
Hybrid-Feedback Driven Transpiler System - A simplified explanation of the abstract
This abstract first appeared for US patent application 18055558 titled 'Hybrid-Feedback Driven Transpiler System
Simplified Explanation
The patent application describes a bi-directional hybrid-feedback driven self-healing and self-scaling language transpiler system.
- Bi-directional hopping to support multi-language transpilation
- Automatic conversion of a mapping into a transformation specification
- Hybrid feedback mechanism to update the transformation mappings
- Automatic scaling and/or creation of enterprise-wide mapping and token vocabulary
- Self-healing and/or corrective translation capability for automatic correction of partial transpilations over time
Potential Applications
This technology could be applied in software development, data integration, and language translation industries.
Problems Solved
This technology solves the problem of manual mapping and translation errors in transpilation processes.
Benefits
The benefits of this technology include increased efficiency, accuracy, and scalability in language transpilation tasks.
Potential Commercial Applications
A potential commercial application of this technology could be in developing language translation software for businesses.
Possible Prior Art
Prior art in this field may include existing language transpilation tools and systems that lack the self-healing and self-scaling capabilities described in this patent application.
Unanswered Questions
1. How does the hybrid feedback mechanism work in updating transformation mappings? 2. What specific industries or sectors could benefit the most from this technology?
Original Abstract Submitted
Various aspects of the disclosure relate to bi-directional hybrid-feedback driven self-healing and self-scaling language transpiler system may include bi-directional hopping to support multi language transpilation, automatic conversion of a mapping into a transformation specification, a hybrid feedback mechanism to update the transformation mappings, automatic scaling and/or creation of enterprise wide mapping and token (e.g., grammar) vocabulary, and/or a self-healing and/or corrective translation capability to perform automatic correction of any partial transpilations over time from a learned mapping.
