Abstract: A foldable device may include a foldable layer and a hinge mechanism. The hinge mechanism may include at least one gear module that provides for synchronized movement of the hinge mechanism about a central plane of the hinge mechanism. A lock module may be coupled the hinge mechanism. The lock module may include a cam and a plate including a plurality of recesses. The lock module may selectively lock the hinge mechanism, and the foldable device, in one of a plurality of positions, based on a position of the cam in one of the recesses.

Abstract: A method includes receiving data indicative of an image of a face of an unknown user of the computing device while the computing device is in a reduced access mode locked state. The method also includes determining whether the unknown user is the known user by at least comparing the image of the face of the unknown user to one or more images of a plurality of images of a face of a known user of the computing device. The method further includes setting the computing device to an increased access mode in response to determining that the unknown user is the known user.

Abstract: A secondary node (SN) for requesting a master node (MN) to page a user equipment (UE) operating in dual connectivity (DC) with the MN and the SN receives, from a core network (CN), downlink traffic for the UE in an inactive state of a protocol for controlling radio resources, the inactive state being associated with a suspended radio connection between the UE and a radio access network (RAN) (802), and transmits, to the MN, a message that causes the MN to initiate RAN paging of the UE (804).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for restarting a query using a token. One of the methods includes receiving, by a computer from a requesting device, a query; determining, using a data storage system, a current result responsive to the query; generating, using the current result, a restart token that represents operations performed to determine a plurality of results responsive to the query including the current result responsive to the query and that can be used to determine a new result responsive to the query that was not included in the plurality of results responsive to the query; and providing, to the requesting device, a message that includes a) first data for the restart token that represents operations performed to determine the plurality of results responsive to the query and b) second data for the current result responsive to the query.

Abstract: Systems, methods, devices, and other techniques are described herein for determining dialog states that correspond to voice inputs and for biasing a language model based on the determined dialog states. In some implementations, a method includes receiving, at a computing system, audio data that indicates a voice input and determining a particular dialog state, from among a plurality of dialog states, which corresponds to the voice input. A set of n-grams can be identified that are associated with the particular dialog state that corresponds to the voice input. In response to identifying the set of n-grams that are associated with the particular dialog state that corresponds to the voice input, a language model can be biased by adjusting probability scores that the language model indicates for n-grams in the set of n-grams. The voice input can be transcribed using the adjusted language model.

Abstract: A method includes obtaining a set of training queries that each specify a corresponding operation to perform and include a corresponding plurality of speech recognition hypotheses that each represent a corresponding candidate transcription of the training query, and a corresponding ground-truth transcription of the training query. For each training query, the method includes processing, using an encoder of a neural semantic parsing (NSP) model, the corresponding plurality of speech recognition hypotheses to generate a corresponding NSP embedding, processing, using a transcription decoder, the corresponding NSP embedding to generate a corresponding predicted transcription, and determining a corresponding first loss based on the corresponding predicted transcription and the corresponding ground-truth transcription.

Abstract: A multimedia communication system for enabling an end user computing device to render a moving image on a display device. The system has an image render command generator that is arranged to provide an image rendering command that is executable by a web browser of the end user computing device to cause the end user computing device to render the moving image on a frame-by-frame basis from a still image in multimedia content by slicing the still image into a plurality of rows or columns of pixels and modifying a subset of the plurality of rows or columns of pixels between frames, and a multimedia content packager arranged to assemble a multimedia content package having the multimedia content, including the still image and the image rendering command.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing contextual grammar selection are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance. The actions include generating a word lattice that includes multiple candidate transcriptions of the utterance and that includes transcription confidence scores. The actions include determining a context of the computing device. The actions include based on the context of the computing device, identifying grammars that correspond to the multiple candidate transcriptions. The actions include determining, for each of the multiple candidate transcriptions, grammar confidence scores that reflect a likelihood that a respective grammar is a match for a respective candidate transcription. The actions include selecting, from among the candidate transcriptions, a candidate transcription.

Abstract: Implementations described herein relate to methods, devices, and computer-readable media to automatically modify a content item based on computer-mediated interaction with reference to a content item. The method includes programmatically analyzing the computer-mediated interaction between a user and a customer service agent to determine if the computer-mediated interaction is successful. The method further includes identifying information provided by the customer service agent during the computer-mediated interaction. The method further includes generating a content update based on the identified information. The method further includes modifying the content item based on the content update.

Abstract: This document describes methods and systems that use an undefined lifecycle state identifier to manage security of a system-on-chip (SoC) integrated circuit (IC) device. As part of the described techniques, the SoC IC device may include a first set of logic integrated circuitry that determines that a first combination of bit values fails to correspond to a known lifecycle state identifier. The first set of logic integrated circuitry may then provide, to a second set of logic integrated circuitry, a second combination of bit values that corresponds to the undefined lifecycle state identifier. The second set of logic integrated circuitry may then place the SoC IC device into an undefined lifecycle state.

Abstract: A method includes receiving a sequence of acoustic frames and generating, by a first encoder, a first higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames. The method also includes generating, by a first pass transducer decoder, a first pass speech recognition hypothesis for a corresponding first higher order feature representation and generating, by a text encoder, a text encoding for a corresponding first pass speech recognition hypothesis. The method also includes generating, by a second encoder, a second higher order feature representation for a corresponding first higher order feature representation. The method also includes generating, by a second pass transducer decoder, a second pass speech recognition hypothesis using a corresponding second higher order feature representation and a corresponding text encoding.

Abstract: Methods, systems, and apparatus for training quantum evolutions using sub-logical controls. In one aspect, a method includes the actions of accessing quantum hardware, wherein the quantum hardware includes a quantum system comprising one or more multi-level quantum subsystems; one or more control devices that operate on the one or more multi-level quantum subsystems according to one or more respective control parameters that relate to a parameter of a physical environment in which the multi-level quantum subsystems are located; initializing the quantum system in an initial quantum state, wherein an initial set of control parameters form a parameterization that defines the initial quantum state; obtaining one or more quantum system observables and one or more target quantum states; and iteratively training until an occurrence of a completion event.

Abstract: A head-mounted device (HMD) may be used to determine an access request for accessing a device. An identifier identifying the device may be received at the HMD and from the device. By verifying receipt of the identifier at the HMD, and that access rights associated with the HMD enable granting of the access request, the access request may be granted.

Abstract: Methods, apparatus, and computer readable media are described herein for allowing a first user to interface with an automated assistant to assign tasks to additional user(s), and/or for causing notification(s) of the assigned task to be rendered to the additional user(s) via corresponding automated assistant interface(s). In various implementations, one or more criteria can be utilized in selecting a group of client device(s), linked to the additional user, via which to provide the notification(s) for the task assigned to the additional user. Also, in various implementations condition(s) for providing the notification(s) for the task can be determined, and the notification(s) provided based on determining satisfaction of the condition(s).

Abstract: Implementations set forth herein relate to phasing-out of vehicle computing device versions while ensuring useful responsiveness of any vehicle computing device versions that are still in operation. Certain features of updated computing devices may not be available to prior versions of computing devices because of hardware limitations. The implementations set forth herein eliminate crashes and wasteful data transmissions caused by prior versions of computing devices that have not been, or cannot be, upgraded. A server device can be responsive to a particular intent request provided to a vehicle computing device, despite the intent request being associated with an action that a particular version of the vehicle computing device cannot execute. In response, the server device can elect to provide speech to text data, and/or natural language understanding data, in furtherance of allowing the vehicle computing device to continue leveraging resources at the server device.

Abstract: A heat exchanger includes a first manifold having an inlet opening and a second manifold having an outlet opening. A group of conduits fluidly connect the first manifold and the second manifold to one another such that a flow path is established for liquid to flow from the inlet opening to the outlet opening. The flow path includes a select portion that extends through all conduits within the group of conduits. Valves are located in the first manifold and the second manifold. The valves are operable to change the select portion of the flow path from between a first state, wherein the conduits within group of conduits are fluidly connected in parallel with one another, and a second state, wherein the conduits within the group of conduits are fluidly connected in series with one another.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating videos. In one aspect, a method comprises: receiving: (i) an input video comprising a sequence of video frames, and (ii) data indicating a target object type; processing the input video to generate tracking data that identifies and tracks visual locations of one or more instances of target objects of the target object type in the input video; generating a plurality of sub-videos based on the input video and the tracking data, including: for each sub-video, generating a respective sequence of sub-video frames that are each extracted from a respective video frame of the input video to include a respective instance of a given target object from among the identified target objects of the target object type; and generating an output video that comprises the plurality of sub-videos.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for pre-fetching data from memory using neural networks. One example system receives a sequence of prior program counter addresses of a computer program and corresponding delta values. The system creates an input representation based on the sequence. The system provides the input representation as input to a recurrent neural network. The system receives from the recurrent neural network an output that defines a probability distribution over future delta values. Each probability in the distribution represents a likelihood that execution of a future instruction of the computer program will cause data to be fetched from a particular future memory address.

Abstract: A computer-implemented method of compressing floating point data of a machine-learned model into a compressed representation of the floating point data can include obtaining floating point data including a plurality of machine-learned model parameters encoded as a tensor, determining a sign vector including a sign bit of each of the plurality of machine-learned model parameters, determining a normalization exponent based on the floating point data, determining a plurality of offsets descriptive of a difference between an exponent of the machine-learned model parameters and the normalization exponent, determining a bitmap including a unary representation of the plurality of offsets, determining a plurality of adjusted mantissas based at least in part on the plurality of offsets, and storing a compressed representation of the floating point data, the compressed representation including the sign vector, the normalization exponent, the bitmap, and one or more bits of each of the plurality of adjusted mantissas.

Abstract: Implementations are directed to dynamically adapting which assistant on-device model(s) are locally stored at assistant devices of an assistant device group and/or dynamically adapting the assistant processing role(s) of the assistant device(s) of the assistant device group. In some of those implementations, the corresponding on-device model(s) and/or corresponding processing role(s), for each of the assistant devices of the group, is determined based on collectively considering individual processing capabilities of the assistant devices of the group. Implementations are additionally or alternatively directed to cooperatively utilizing assistant devices of a group, and their associated post-adaptation on-device model(s) and/or post-adaptation processing role(s), in cooperatively processing assistant requests that are directed to any one of the assistant devices of the group.