Abstract: At least one aspect of the present disclosure is directed to systems and methods of secure and privacy preserving device classification. A server can maintain a plurality of data records, each including an indication of a request and a known classification value. The server can train a context obfuscation model using each of the plurality of requests and known classification values. The server can train a classification model using resources and category information from a data structure in the memory of the client device. The server can transmit the context obfuscation model to a different plurality of client devices. The server can receive a request for classification including a classification vector and request metadata. The server can determine the classification of the device responsible for the request using the classification model. The server can transmit the device classification to the device responsible for the request.

Abstract: Methods and apparatus related to receiving a request that includes robot instructions and/or environmental parameters, operating each of a plurality of robots based on the robot instructions and/or in an environment configured based on the environmental parameters, and storing data generated by the robots during the operating. In some implementations, at least part of the stored data that is generated by the robots is provided in response to the request and/or additional data that is generated based on the stored data is provided in response to the request.

Abstract: Systems and methods for providing time-delimited action suggestions are provided. In one example embodiment, a method includes receiving, by one or more computing devices from a user device, data indicative of a user-requested time-bound activity. The time-bound activity is associated with a time period. The method includes identifying, by the one or more computing devices, one or more parameters associated with a user that requested the time-bound activity. The method includes determining, by the one or more computing devices, a suggested action based at least in part on the one or more parameters associated with the user and the time period associated with the time-bound activity. The method includes providing, by the one or more computing devices, an output indicative of the suggested action to the user device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for ranking query completions based on activity session data. One of the methods includes receiving a query prefix from a user. A reference parameter for the user is obtained. One or more likely queries that are likely to co-occur with the reference parameter in user activity sessions are identified, wherein each likely query has an associated prediction score. A ranking of the one or more likely queries is provided in response to receiving the query prefix.

Abstract: Implementations set forth herein relate to an automated assistant that can control a camera according to one or more conditions specified by a user. A condition can be satisfied when, for example, the automated assistant detects a particular environment feature is apparent. In this way, the user can rely on the automated assistant to identify and capture certain moments without necessarily requiring the user to constantly monitor a viewing window of the camera. In some implementations, a condition for the automated assistant to capture media data can be based on application data and/or other contextual data that is associated with the automated assistant. For instance, a relationship between content in a camera viewing window and other content of an application interface can be a condition upon which the automated assistant captures certain media data using a camera.

Abstract: Implementations described herein relate to reducing latency in automated assistant interactions. In some implementations, a client device can receive audio data that captures a spoken utterance of a user. The audio data can be processed to determine an assistant command to be performed by an automated assistant. The assistant command can be processed, using a latency prediction model, to generate a predicted latency to fulfill the assistant command. Further, the client device (or the automated assistant) can determine, based on the predicted latency, whether to audibly render pre-cached content for presentation to the user prior to audibly rendering content that is responsive to the spoken utterance. The pre-cached content can be tailored to the assistant command and audibly rendered for presentation to the user while the content is being obtained, and the content can be audibly rendered for presentation to the user subsequent to the pre-cached content.

Abstract: The present disclosure provides systems and methods that generate new architectures for artificial neural networks based on connectomics data that describes connections between biological neurons of a biological organism. In particular, in some implementations, a computing system can identify one or more new artificial neural network architectures by performing a neural architecture search over a search space that is constrained based at least in part on the connectomics data.

Abstract: A first computing device can implement a method for providing navigation instructions. The method includes initiating a first navigation session for providing a first set of navigation instructions to a user from a starting location to a destination location along a first route. The method also includes detecting a second computing device in proximity to the first computing device, and determining that the second computing device is implementing a second navigation session for providing a second set of navigation instructions to the destination location along a second route. Further, the method includes adjusting the first navigation session in accordance with the second navigation session.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for list accumulation and reminder triggering. In one aspect, a method includes receiving, at a data processing apparatus, a first input comprising a plurality of terms; determining, by the data processing apparatus, that one or more of the terms in the first input specify an item that belongs to a reminder category, the reminder category being associated with a collection of items that belong to the category and for which reminders may be generated; and in response to the determination, storing data that associates a reminder type with the item specified by the one or more terms.

Abstract: The present disclosure provides systems and methods to measure quantum gate fidelity through swap spectroscopy. In particular, aspects of the present disclosure are directed to the derivation and use of a physical model that models non-Markovian quantum dynamics of interactions between one or more qubits of a quantum gate and one or more two-level-system (TLS) defects during operation of the quantum gate.

Abstract: Systems and methods are shown for providing private local sponsored content selection and improving intelligence models through distribution among mobile devices. This allows greater data gathering capabilities through the use of the sensors of the mobile devices as well as data stored on data storage components of the mobile devices to create predicted models while offering better opportunities to preserve privacy. Locally stored profiles comprising machine intelligence models may also be used to determine the relevance of the data gathered and in improving an aggregated model for identifying the relevance of data and the selection of sponsored content items. Distributed optimization is used in conjunction with privacy techniques to create the improved machine intelligence models. Publishers may also benefit from the improved privacy by protecting the statistics of type or volume of sponsored content items shown with publisher content.

Abstract: A method for a hard reset of a target electronic device includes establishing a near field communications (NFC) channel to the target electronic device, receiving a wireless signal at the target electronic device over the NFC channel, and comparing a signature of the received wireless signal with a predefined characteristic signature of a reset command signal. Responsive to the comparing, the method includes generating a reset signal resetting the target electronic device.

Abstract: The present disclosure provides systems and methods for customized programming through “virtual zoning”, not based on network architecture or geographic region, via a modified electronic programming guide (EPG) provided to devices assigned to virtual zones. Broadcasters may thus provide virtual zone-based “localized” programming to devices regardless of location. The virtual zone-based EPG may be functionally identical to conventional EPGs, and thus fully compatible with existing recipient devices, without requiring custom programming or manufacturer resources. Content may be broadcast to virtual zones via multicast IP streams, with primary content provided to a plurality of virtual zones and custom content provided on a stream-by-stream basis.

Abstract: Systems and methods for providing a multi-step identification process using a hybrid edge/server infrastructure to generate machine learned inferences are provided. One example method includes obtaining sensor data of an environment including one or more user. The method includes selecting at least a portion of the sensor data that is associated with the one or more users. The method includes generating, using one or more machine learning models, an intermediate representation of the selected portion of the sensor data that represents the face of the one or more users. The method includes transmitting the intermediate representation and a request for a user identification based on the intermediate representation, the remote computing system configured to perform additional steps of the multi-step identification process using the intermediate representation and the machine-learned system. The method includes receiving a user identifier for the one or more users.

Abstract: A computing system and method that can be used for a video conferencing system including a graphical user interface having a virtual whiteboard user interface that is responsive to inputs from multiple attendees of a video conference. In particular, the state of an application tool such as a camera, visual note indicator, web link, pen/pencil tool, highlighter tool, or other application tool executing or otherwise represented within the multi-user interaction whiteboard can respond and change in real-time as multiple attendees of the video conference interact with the virtual whiteboard user interface. The systems and methods of the present disclosure allow for a multi-user interaction whiteboard to offer various tools for the video conferencing system to facilitate interactions by multiple attendees within the graphical user interface.

Abstract: The technology involves providing haptic feedback to a user of a computing device. For instance, user input associated with a program of the computing device is received by a user interface module of the computing device. One or more processors of the computing device determine a kind of interaction corresponding to the user input. The one or more processors identify whether the kind of interaction is associated with one or more haptic feedback effects of a curated suite of haptic effects. Upon identifying that the kind of interaction is associated with one or more haptic feedback effect, the one or more processors select a particular haptic feedback effect from the curated suite of haptic effects. And the one or more processors are able to cause a haptic feedback module of the computing device to provide the particular haptic feedback effect for sensation by the user.

Abstract: Methods, and systems, including computer programs encoded on computer storage media for generating machine learning models. A method includes receiving, through a GUI, user selection of a mode button displayed in the GUI, wherein the mode button, when selected, causes the GUI to display a first set of user-selectable buttons that correspond to respective machine learning routines, and when not selected, causes the GUI to display a second set of user-selectable buttons that correspond to respective machine learning sub-routines; in response to receiving user selection of the mode button, displaying the first set of user-selectable buttons; receiving user selection of one or more of the first set of user-selectable buttons; displaying a graphical representation of a machine learning model defined by machine learning routines corresponding to the user selected one or more of the first set of user-selectable buttons and generating a file representing the machine learning model.

Abstract: A memory device includes at least one memory cell array block and a control logic. The memory cell array block includes multiple layers of memory cells and word line layers provided corresponding to individual layers of memory cells. The memory cell array block is divided into at least two memory cell array subblocks, each subblock comprising a number of layers of memory cells and word line layers provided corresponding to individual layers of memory cells. The control logic is coupled to the memory cell array block, and configured to: erase, read or program the memory cell array block using a block mode or a subblock mode, and when the memory cell array block is erased, read, or programmed under the subblock mode, determine, at least based on a state of one of the two memory cell array subblocks, an operation strategy of the other memory cell array subblock.

Abstract: Determining a language for speech recognition of a spoken utterance received via an automated assistant interface for interacting with an automated assistant. Implementations can enable multilingual interaction with the automated assistant, without necessitating a user explicitly designate a language to be utilized for each interaction. Implementations determine a user profile that corresponds to audio data that captures a spoken utterance, and utilize language(s), and optionally corresponding probabilities, assigned to the user profile in determining a language for speech recognition of the spoken utterance. Some implementations select only a subset of languages, assigned to the user profile, to utilize in speech recognition of a given spoken utterance of the user.