Dynamic, resource-sensitive model selection and output generation and methods and systems of the same
US12106205B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 10, 2024 |
| Grant date | Oct 1, 2024 |
| Priority date | — |
| Expiry date | May 10, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosed data generation platform enables selection of particular machine learning models on the basis of a predicted resource allocation requirement associated with a given prompt. For example, the model validation platform can evaluate the resource use (e.g., cost) associated with processing a user's prompt with a given type of model. Based on this estimated resource use, the model validation platform can route the prompt to a suitable model to optimize a performance metric value, thereby improving the efficiency of the system. In some implementations, the data generation platform trains a model to accurately estimate resource usage based on ground-truth model-related costs, thereby improving the effectiveness of model selection for efficiency improvements.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.