Fleet and asset management for edge computing of machine learning and artificial intelligence workloads deployed from cloud to edge
US12131242B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 5, 2023 |
| Grant date | Oct 29, 2024 |
| Priority date | — |
| Expiry date | Sep 5, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L41/16
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A process can include transmitting a pre-trained machine learning model to an edge compute unit associated with a request. The edge compute unit can perform inference using the pre-trained machine learning model and one or more sensor data streams obtained at an edge location. One or more batch uploads of information can be received, associated with inference performed by the edge compute unit and using the pre-trained machine learning model. One or more updated machine learning models can be generated, based on using the batch uploads of information from the edge compute unit to retrain or finetune the pre-trained machine learning model. The one or more updated machine learning models can be transmitted to the edge compute unit, wherein transmission of the updated machine learning model is responsive to receiving the one or more batch uploads of information.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.