Validating vector constraints of outputs generated by machine learning models
US12361334B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 10, 2025 |
| Grant date | Jul 15, 2025 |
| Priority date | — |
| Expiry date | Jan 10, 2045 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The technology evaluates the compliance of an AI application with predefined vector constraints. The technology employs multiple specialized models trained to identify specific types of non-compliance with the vector constraints within AI-generated responses. One or more models evaluate the existence of certain patterns within responses generated by an AI model by analyzing the representation of the attributes within the responses. Additionally, one or more models can identify vector representations of alphanumeric characters in the AI model's response by assessing the alphanumeric character's proximate locations, frequency, and/or associations with other alphanumeric characters. Moreover, one or more models can determine indicators of vector alignment between the vector representations of the AI model's response and the vector representations of the predetermined characters by measuring differences in the direction or magnitude of the vector representations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.