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公开(公告)号：US11847576B2
公开(公告)日：2023-12-19
申请号：US16538706
申请日：2019-08-12
Applicant: Apple Inc.
Inventor： Binu K. Mathew , Kit-Man Wan , Gaurav Kapoor
Abstract: Disclosed herein is a technique for implementing a framework that enables application developers to enhance their applications with dynamic adjustment capabilities. Specifically, the framework, when utilized by an application on a mobile computing device that implements the framework, can enable the application to establish predictive models that can be used to identify meaningful behavioral patterns of an individual who uses the application. In turn, the predictive models can be used to preempt the individual's actions and provide an enhanced overall user experience. The framework is configured to interface with other software entities on the mobile computing device that conduct various analyses to identify appropriate times for the application to manage and update its predictive models. Such appropriate times can include, for example, identified periods of time where the individual is not operating the mobile computing device, as well as recognized conditions where power consumption is not a concern.
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公开(公告)号：US11520629B2
公开(公告)日：2022-12-06
申请号：US16776338
申请日：2020-01-29
Applicant: Apple Inc.
Inventor： Francesco Rossi , Gaurav Kapoor , Michael R. Siracusa , William B. March
Abstract: The subject technology provides for dynamic task allocation for neural network models. The subject technology determines an operation performed at a node of a neural network model. The subject technology assigns an annotation to indicate whether the operation is better performed on a CPU or a GPU based at least in part on hardware capabilities of a target platform. The subject technology determines whether the neural network model includes a second layer. The subject technology, in response to determining that the neural network model includes a second layer, for each node of the second layer of the neural network model, determines a second operation performed at the node. Further the subject technology assigns a second annotation to indicate whether the second operation is better performed on the CPU or the GPU based at least in part on the hardware capabilities of the target platform.
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公开(公告)号：US11116425B2
公开(公告)日：2021-09-14
申请号：US16180483
申请日：2018-11-05
Applicant: APPLE INC.
Inventor： Daniel S. Keen , Jay C. Blahnik , Gaurav Kapoor , Michael R. Siracusa
Abstract: Pacer activity data of a user may be managed. For example, historical activity data of a user corresponding to a particular time of a day prior to a current day may be received. Additionally, a user interface configured to display an activity goal of the user may be generated and the user interface may be provided for presentation. In some aspects, the user interface may be configured to display a first indicator that identifies cumulative progress towards the activity goal and a second indicator that identifies predicted cumulative progress towards the activity goal. The cumulative progress may be calculated based on monitored activity from a start of the current day to the particular time of the current day and the predicted cumulative progress may be calculated based on the received historical activity data corresponding to the particular time of the day prior to the current day.
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公开(公告)号：US10885039B2
公开(公告)日：2021-01-05
申请号：US14721945
申请日：2015-05-26
Applicant: Apple Inc.
Inventor： John M. Hornkvist , Gaurav Kapoor
IPC: G06F16/2457 , G06F16/9535 , G06F16/9537 , G06N20/00
Abstract: Systems and methods are disclosed for improving search results returned to a user from one or more search domains, utilizing query features learned locally on the user's device. A search engine can receive, analyze and forward query results from multiple search domains and pass the query results to a client device. A search engine can determine a feature by analyzing query results, generate a predictor for the feature, instruct a client device to use the predictor to train on the feature, and report back to the search engine on training progress. A search engine can instruct a first and second set of client devices to train on set A and B of predictors, respectively, and report back training progress to the search engine. A client device can store search session context and share the context with a search engine between sessions with one or more search engines. A synchronization system can synchronize local predictors between multiple client devices of a user.
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公开(公告)号：US10310821B2
公开(公告)日：2019-06-04
申请号：US15721712
申请日：2017-09-29
Applicant: Apple Inc.
Inventor： Alexander B. Brown , Michael R. Siracusa , Gaurav Kapoor , Elizabeth Ottens , Christopher M. Hanson , Zachary A. Nation , Vrushali Mundhe , Srikrishna Sridhar
Abstract: The subject technology provides for determining that a machine learning model in a first format includes sufficient data to conform to a particular model specification in a second format, the second format corresponding to an object oriented programming language. The subject technology transforms the machine learning model into a transformed machine learning model that is compatible with the particular model specification. The subject technology generates a code interface and code for the transformed machine learning model, the code interface including code statements in the object oriented programming language, the code statements corresponding to an object representing the transformed machine learning model. Further, the subject technology provides the generated code interface and the code for display in an integrated development environment (IDE), the IDE enabling modifying of the generated code interface and the code.
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Patent Agency Ranking
公开(公告)号：US20190068628A1
公开(公告)日：2019-02-28
申请号：US16159481
申请日：2018-10-12
Applicant: Apple Inc.
Inventor： Abhradeep Guha Thakurta , Andrew H. Vyrros , Umesh S. Vaishampayan , Gaurav Kapoor , Julien Freudiger , Vipul Ved Prakash , Arnaud Legendre , Steven Duplinsky
CPC classification number: H04L63/1425 , G06F17/2235 , G06F17/2735 , G06F17/276 , G06F21/6254 , G06N20/00 , H04L63/0421
Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.
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公开(公告)号：US20180349189A1
公开(公告)日：2018-12-06
申请号：US15721716
申请日：2017-09-29
Applicant: Apple Inc.
Inventor： Francesco Rossi , Gaurav Kapoor , Michael R. Siracusa , William B. March
Abstract: The subject technology provides for dynamic task allocation for neural network models. The subject technology determines an operation performed at a node of a neural network model. The subject technology assigns an annotation to indicate whether the operation is better performed on a CPU or a GPU based at least in part on hardware capabilities of a target platform. The subject technology determines whether the neural network model includes a second layer. The subject technology, in response to determining that the neural network model includes a second layer, for each node of the second layer of the neural network model, determines a second operation performed at the node. Further the subject technology assigns a second annotation to indicate whether the second operation is better performed on the CPU or the GPU based at least in part on the hardware capabilities of the target platform.
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公开(公告)号：US09894089B2
公开(公告)日：2018-02-13
申请号：US15627269
申请日：2017-06-19
Applicant: Apple Inc.
Inventor： Abhradeep Guha Thakurta , Andrew H. Vyrros , Umesh S. Vaishampayan , Gaurav Kapoor , Julien Freudinger , Vipul Ved Prakash , Arnaud Legendre , Steven Duplinsky
CPC classification number: H04L63/1425 , G06F17/2235 , G06F17/2735 , G06F17/276 , G06F21/6254 , G06N99/005 , H04L63/0421
Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.
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公开(公告)号：US20170359363A1
公开(公告)日：2017-12-14
申请号：US15627269
申请日：2017-06-19
Applicant: Apple Inc.
Inventor： Abhradeep Guha Thakurta , Andrew H. Vyrros , Umesh S. Vaishampayan , Gaurav Kapoor , Julien Freudinger , Vipul Ved Prakash , Arnaud Legendre , Steven Duplinsky
CPC classification number: H04L63/1425 , G06F17/2235 , G06F17/2735 , G06F17/276 , G06F21/6254 , G06N99/005 , H04L63/0421
Abstract: Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.
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公开(公告)号：US20170102750A1
公开(公告)日：2017-04-13
申请号：US15389311
申请日：2016-12-22
Applicant: Apple Inc.
Inventor： Keith Cox , Gaurav Kapoor , Vaughn T. Arnold
Abstract: Methods and apparatuses are disclosed to estimate temperature at one or more critical points in a data processing system comprising modeling a steady state temperature portion of a thermal model at the one or more critical points using regression analysis; modeling the transient temperature portion of the thermal model at the one or more critical points using a filtering algorithm; and generating a thermal model at the one or more critical points by combining the steady state temperature portion of the thermal model with the transient temperature portion of the thermal model. The thermal model may then be used to estimate an instantaneous temperature at the one or more critical points or to predict a future temperature at the one or more critical points.
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