Opendoor Technologies has been granted a patent for systems and methods utilizing a machine learning model registry. The system deploys and re-trains machine learning models, performs acceptance tests, and automatically deploys updated versions to server machines for prediction services. GlobalData’s report on Opendoor Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Opendoor Technologies, was a key innovation area identified from patents. Opendoor Technologies's grant share as of May 2024 was 20%. Grant share is based on the ratio of number of grants to total number of patents.
Machine learning model registry for prediction service deployment
A recently granted patent (Publication Number: US11972337B2) discloses a system for providing a prediction service using machine learning models. The system includes a processor and memory that execute instructions to train a first version of a machine learning model to generate a second version. The second version is automatically identified as interoperable with an access module and deployed to multiple machines for providing the prediction service. The system validates the deployability of the second version based on predetermined criteria, such as model evaluation metrics like mean squared error, and ensures common features are utilized by the access module and machine learning model.
Furthermore, the patent also covers a method and a non-transitory machine-readable medium for providing the prediction service using similar processes. The method involves training, validating, and deploying machine learning models and access modules, while the non-transitory machine-readable medium stores instructions for executing these operations. The second version of the machine learning model is specified as a linear regression model in both the method and the medium. Additionally, a user interface is presented to compare the second version with the first version based on model evaluation metrics, and an identifier is received to distinguish the second version of the machine learning model. This patent highlights a systematic approach to deploying machine learning models for prediction services, ensuring compatibility and efficiency across multiple machines.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
