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公开(公告)号：US20240169221A1
公开(公告)日：2024-05-23
申请号：US18426325
申请日：2024-01-29
申请人： GOOGLE LLC
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing actionable suggestions are disclosed. In one aspect, a method includes receiving (i) an indication that an event detection module has determined that a shared event of a particular type is presently occurring or has occurred, and (ii) data referencing an attribute associated with the shared event. The method includes selecting, from among multiple output templates that are each associated with a different type of shared event, a particular output template associated with the particular type of shared event detected by the module. The method generates a notification for output using at least (i) the selected particular output template, and (ii) the data referencing the attribute associated with the shared event. The method then provides, for output to a user device, the notification that is generated.
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公开(公告)号：US11915115B2
公开(公告)日：2024-02-27
申请号：US17138866
申请日：2020-12-30
申请人： GOOGLE LLC
发明人： Thomas Deselaers , Victor Carbune
IPC分类号： G06N3/00 , G06N20/00 , G06N3/006 , B60W30/18 , G06V20/56 , G06F18/21 , G06V10/764 , G06V10/82 , G06V20/58
CPC分类号： G06N3/006 , B60W30/18163 , G06F18/217 , G06N20/00 , G06V10/764 , G06V10/82 , G06V20/58 , G06V20/588 , B60W2420/42 , B60W2520/10 , B60W2552/10 , B60W2555/20
摘要： To selecting a lane in a multi-lane road segment for a vehicle travelling on the road segment, a system determines current traffic information for the road segment including a plurality of lanes and applies the current traffic information to a machine learning (ML) model to generate an indication of one of the plurality of lanes in which the vehicle is to travel. Subsequently to the vehicle selecting the indicated lane, the system determines an amount of time the vehicle took to travel a certain distance following the selection, and provides the determined amount of time to the ML model as a feedback signal.
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公开(公告)号：US11831804B2
公开(公告)日：2023-11-28
申请号：US17340768
申请日：2021-06-07
申请人： GOOGLE LLC
发明人： Sandro Feuz , Thomas Deselaers
CPC分类号： H04M3/4365 , G06F3/017 , G06N20/00 , H04M3/42042 , H04M2203/25
摘要： Implementations set forth herein relate to generating a pre-call analysis for one or more users that are receiving and/or initializing a call with one or more other users, and/or prioritizing pre-call content according to whether security-related value was gleaned from provisioning certain pre-call content. One or more machine learning models can be employed for determining the pre-call content to be cached and/or presented prior to a user accepting a call from another user. Feedback provided before, during, and/or after the call can be used as a basis from which to prioritize certain content and/or sources of content when generating pre-call content for a subsequent call. Other information, such as contextual data (e.g., calendar entries, available peripheral devices, location, etc.) corresponding to the previous call and/or the subsequent call, can also be used as a basis from which to provide a pre-call analysis.
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公开(公告)号：US20230237312A1
公开(公告)日：2023-07-27
申请号：US18128092
申请日：2023-03-29
申请人： GOOGLE LLC
发明人： Victor Carbune , Thomas Deselaers
CPC分类号： G06N3/045 , G06N3/00 , G06N3/02 , G10L15/00 , G10L15/22 , G10L15/222 , G10L15/20 , G10L2015/223
摘要： Techniques are disclosed that enable automating user interface input by generating a sequence of actions to perform a task utilizing a multi-agent reinforcement learning framework. Various implementations process an intent associated with received user interface input using a holistic reinforcement policy network to select a software reinforcement learning policy network. The sequence of actions can be generated by processing the intent, as well as a sequence of software client state data, using the selected software reinforcement learning policy network. The sequence of actions are utilized to control the software client corresponding to the selected software reinforcement learning policy network.
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公开(公告)号：US11494667B2
公开(公告)日：2022-11-08
申请号：US15874121
申请日：2018-01-18
申请人： Google LLC
发明人： Victor Carbune , Thomas Deselaers
摘要： Example aspects of the present disclosure are directed to systems and methods that enable improved adversarial training of machine-learned models. An adversarial training system can generate improved adversarial training examples by optimizing or otherwise tuning one or hyperparameters that guide the process of generating of the adversarial examples. The adversarial training system can determine, solicit, or otherwise obtain a realism score for an adversarial example generated by the system. The realism score can indicate whether the adversarial example appears realistic. The adversarial training system can adjust or otherwise tune the hyperparameters to produce improved adversarial examples (e.g., adversarial examples that are still high-quality and effective while also appearing more realistic). Through creation and use of such improved adversarial examples, a machine-learned model can be trained to be more robust against (e.g., less susceptible to) various adversarial techniques, thereby improving model, device, network, and user security and privacy.
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公开(公告)号：US11483170B1
公开(公告)日：2022-10-25
申请号：US16730484
申请日：2019-12-30
申请人： GOOGLE LLC
发明人： Victor Carbune , Daniel Keysers , Thomas Deselaers
摘要： Systems and methods for video conference content auto-retrieval and focus based on learned relevance is provided. In accordance with the systems and methods, audio streams and video streams from client devices participating in a video conference are received. Based on the audio streams, a subject being discussed during the video conference at a point in time is determined. A video stream that is most relevant to the subject being discussed during the video conference at the point in time is determined from the video streams. The determined video stream is provided to the client devices for presentation on the client devices while the subject is being discussed during the video conference.
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公开(公告)号：US20220036216A1
公开(公告)日：2022-02-03
申请号：US17280034
申请日：2018-11-20
申请人： Google LLC
摘要： The present disclosure is directed to a new framework the enables the combination of symbolic programming with machine learning, where the programmer maintains control of the overall architecture of the functional mapping and the ability to inject domain knowledge while allowing their program to evolve by learning from examples. In some instances, the framework provided herein can be referred to as “predictive programming.”
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公开(公告)号：US20210243200A1
公开(公告)日：2021-08-05
申请号：US17237573
申请日：2021-04-22
申请人： Google LLC
发明人： Victor Carbune , Thomas Deselaers , Sandro Feuz
IPC分类号： H04L29/06 , G10L15/22 , H04L29/08 , G06F16/635 , G06F3/16 , G10L17/00 , G06F21/32 , G06F9/50
摘要： The present disclosure is generally directed to a data processing system for customizing content in a voice activated computer network environment. With user consent, the data processing system can improve the efficiency and effectiveness of auditory data packet transmission over one or more computer networks by, for example, increasing the accuracy of the voice identification process used in the generation of customized content. The present solution can make accurate identifications while generating fewer audio identification models, which are computationally intensive to generate.
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9.发明申请公开(公告)号：US20200329140A1
公开(公告)日：2020-10-15
申请号：US16339235
申请日：2019-01-16
申请人： Google LLC
发明人： Sandro Feuz , Thomas Deselaers
摘要： Implementations set forth herein relate to generating a pre-call analysis for one or more users that are receiving and/or initializing a call with one or more other users, and/or prioritizing pre-call content according to whether security-related value was gleaned from provisioning certain pre-call content. One or more machine learning models can be employed for determining the pre-call content to be cached and/or presented prior to a user accepting a call from another user. Feedback provided before, during, and/or after the call can be used as a basis from which to prioritize certain content and/or sources of content when generating pre-call content for a subsequent call. Other information, such as contextual data (e.g., calendar entries, available peripheral devices, location, etc.) corresponding to the previous call and/or the subsequent call, can also be used as a basis from which to provide a pre-call analysis.
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公开(公告)号：US20190342282A1
公开(公告)日：2019-11-07
申请号：US16477062
申请日：2017-01-20
申请人： Google LLC
发明人： Victor Carbune , Daniel Keysers , Thomas Deselaers
IPC分类号： H04L29/06
摘要： An example method includes establishing a single-user login session associated with a first user-account such that the single-user login session has read and/or write access to first user data associated with the first user-account. The method further includes accepting, within the single-user login session, a further login associated with a second user-account to convert the single-user login session to a multi-user login session having read and/or write access to second user data associated with the second user-account in addition to having read and/or write access to the first user data. Computer readable media and computing devices related to the example method are disclosed herein as well.
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