Google Inc Patent Portfolio Statistics

Google Inc.

Profile Summary

This article summarizes the perfomance of the assignee in the recent years. The overall statistics for this portfolio help to analyze the areas where the assignee is performing well. The filing trend, perfomance across the tech centers and the perfomance of the recent applications has been mentioned below. All the stats are calculated based on the perfomance in USPTO.

How does the overall patent portfolio of Google Inc. look like?

Total Applications: 32,480
Granted Patents: 27,048
Grant Index 86.57 %
Abandoned/Rejected Applications: 4,196 (13.43%)
In-Process Applications: 1,206
Average Grant Time: 2.89 Years
Average Office Actions: 1.8

Which Technology Area Google Inc. is filing most patents in? (Last 10 years)

Art Unit Definition Total Applications
2161 Data Bases & File Management 419
2162 Data Bases & File Management 377
2665 Digital Cameras 370
2163 Data Bases & File Management 365
2159 Data Bases & File Management 362

How many patents are Google Inc. filing every year?

Year Total Applications
2022 0*
2021 281*
2020 523
2019 916
2018 812

*The drop in the number of applications filed in last two years compared to previous years is because applications can take up to 18 months to get published

Recently filed patent applications of Google Inc. in USPTO?

Publication number:
Application number: 17/538,574

Abstract:
None

Publication date:
Applicant: Google Inc.
Inventors: Drew Eugene Ulrich


Publication number: US20220004929A1
Application number: 17/479,364

Abstract:
The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.

Publication date: 2022-01-06
Applicant: Google Inc.
Inventors: Daniel Ramage


Publication number: US20210203560A1
Application number: 17/183,667

Abstract:
This disclosure provides systems and methods for routing and topology management of computer networks with steerable beam antennas. A network controller can generate an input graph for a first time period. The input graph can have a plurality of vertices each representing a respective moving node and a plurality of edges each representing a possible link between a pair of moving nodes. The input graph also can include corresponding location information for each of the moving nodes during the first time period. A solver module can receive information corresponding to the input graph, a maximum degree for each vertex in the input graph, and a set of provisioned network flows. The solver module can determine a subgraph representing a network topology based on the input graph, the maximum degree for each vertex in the input graph, and the set of provisioned network flows, such that a number of edges associated with each vertex in the subgraph does not exceed the maximum degree for each vertex.

Publication date: 2021-07-01
Applicant: Google Inc.
Inventors: Barritt Brian


How are Google Inc.’s applications performing in USPTO?

Application Number Title Status Art Unit Examiner
17/538,574 Devices And Methods For A Rotating Lidar Platform With A Shared Transmit/Receive Path Docketed New Case – Ready for Examination 3993 Lillis, Eileen Dunn
17/479,364 On-Device Machine Learning Platform Docketed New Case – Ready for Examination OPAP Central, Docket
17/183,667 Systems And Methods For Routing And Topology Management Of Computer Networks With Steerable Beam Antennas Docketed New Case – Ready for Examination OPAP Central, Docket
16/825,402 Systems And Methods For Improving Tolerance Of Delay And Disruption Of A Control-To-Data-Plane Interface In A Software-Defined Network Docketed New Case – Ready for Examination 3992 Corsaro, Nick
16/825,467 Systems And Methods For Improving Tolerance Of Delay And Disruption Of A Control-To-Data-Plane Interface In A Software-Defined Network Docketed New Case – Ready for Examination 3992 Corsaro, Nick