Google patents search system that combines local and cloud data
This patent describes a method for answering user search questions by looking through both data stored on the user's device and data stored on remote servers. It uses machine learning to break the question into specific instructions for searching these different locations and then uses a generative model to combine the findings into a single, natural language answer.
In the filing’s own words
Systems and methods for performing user data search can include obtaining a search query, processing the search query with one or more machine-learned planning model to generate one or more specialized queries and instructions to search one or more specific user datasets with the one or more specialized queries, and processing the obtained search results with a generative response model to generate a response to the search query. The systems and methods can search across local databases and server databases. An on-device generative response model can be utilized for device local search results, while a server generative response model may be utilized for server-based search results.
What exactly they claim (claim 1)
1. A computer-implemented method for personal data indexing and search, the method comprising: obtaining, by a computing system comprising one or more processors, a search query from a user computing device associated with a particular user; processing, by the computing system, the search query with one or more machine-learned planning models to generate one or more first application programming interface calls, wherein the one or more first programming interface calls comprise one or more first queries and instructions to interface with one or more first application-specific index datasets of a plurality of different server-side application-specific index datasets; performing, by the computing system, the one or more first application programming interface calls to obtain one or more first result sets; processing, by the computing system, the search query and the one or more first result sets with the one or more machine-learned planning models to generate one or more second application programming interface calls and to determine one or more on-device datasets to search, wherein the one or more second programming interface calls comprises one or more second queries and instructions to interface with one or more second application-specific index datasets of the plurality of different server-side application-specific index datasets; performing, by the computing system, the one or more second application programming interface calls to obtain one or more second result sets; processing, by the computing system, the search query, the one or more first result sets, and the one or more second result sets with one or more generative response models to generate one or more model-generated responses to the search query, wherein the one or more model-generated responses comprise details of the one or more first result sets and the one or more second result sets in a natural language response to one or more prompts of the search query; and transmitting, by the computing system, the one or more model-generated responses along with planning data descriptive of the one or more on-device datasets to search to the user computing device associated with the particular user.
Facts
- Company
- Google (Google LLC)
- Official title
- Search processing based on routing predictions for searching across local and server datasets
- Patent number
- US12748766B2
- Application number
- 18909548
- Filed
- Oct 8, 2024
- Granted
- Sep 29, 2026
- Inventors
- 3
- Claims
- 10
Classified under
G06F 16/248 Physics & computingG06F 9/547 Physics & computingMore from Google in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.