Abstract: Rendering images on an active area of an OLED includes rendering images on the active area of the display panel with a plurality of different frame rates. For a plurality of the different frame rates having a frame rate that matches or is above a threshold frame rate, an image refresh operation is performed once per frame period and a self-refresh operation is not performed during the frame period. When rendering images on the active area, for at least one of the different frame rates having a frame rate that is lower than the threshold frame rate, an image refresh operation is performed once per frame period and a self-refresh operation is performed at least once during the frame period.

Abstract: This document describes systems and techniques for modulating credit allocations in memory subsystems. The described systems and techniques can provide a feedback mechanism to a credit controller to improve the bandwidth at a memory interface. The memory controller monitors statistics associated with transaction requests served to one or more random access memories (RAMs) of the memory subsystem. The memory controller can then provide suggestions to the credit controller or to the one or more clients to modulate the number of credits allocated to one or more clients. In this way, the described systems and techniques can improve the efficiency of the memory controller in managing the transaction requests and the bandwidth at the memory interface.

Abstract: Methods, systems, and media for detecting the presence of a digital media device on a network are provided. In some embodiments, methods for detecting a presence of a particular type of digital media device is provided, the methods comprising: identifying cached device details for devices previously associated with the network; performing a simple device discovery protocol (SSDP) on the network, and substantially concurrently sending a unicast message to an address associated with the identified cached digital media device using hypertext transfer protocol (HTTP); and indicating the presence of a digital media device on the network in response to either (i) receiving a response to the unicast message, or (ii) determining that a type of a device discovered using SSDP is the same as the particular device type.

Abstract: A cyber-security analysis method uses machine learning (ML) technology to classify cyber-threat indicators, for example, as malicious or benign, by generating a threat score. The method includes receiving, at a compute device, a data set including cyber-threat indicators and verdicts serving as votes from each source in the set of sources. Each of the votes is associated with one of the cyber-threat indicators. An ML model is trained based on at least one of agreements among the sets of votes, and disagreements among the sets of votes to produce a trained ML model. In response to receiving a new cyber-threat indicator, votes are identified for each source from a subset of the sources, to define a second set of votes. The cyber-threat score is generated for the new cyber-threat indicator based on the trained ML model and the second set of votes.

Abstract: A method includes receiving trace data representing access information about files stored in a large-scale distributed storage system, identifying file access patterns based on the trace data, receiving metadata information associated with the files stored in the large-scale distributed storage system, and generating a preferred storage parameter for each file based on the received metadata information and the identified file access patterns. The method also includes receiving, file reliability or accessibility information of a new file, determining whether the received file reliability or accessibility information of the new file matches information of a file group of the files in the large-scale distributed storage system, and when the file reliability or accessibility information of the new file matches the information of the file group, storing the new file in the large-scale distributed storage system using the preferred storage parameter associated with the file group.

Abstract: Implementations relate to dynamically adapting a given assistant output based on a given persona, from among a plurality of disparate personas, assigned to an automated assistant. In some implementations, the given assistant output can be generated and subsequently adapted based on the given persona assigned to the automated assistant. In other implementations, the given assistant output can be generated specific to the given persona and without having to subsequently adapt the given assistant output to the given persona. Notably, the given assistant output can include a stream of textual content to be synthesized for audible presentation to the user, and a stream of visual cues utilized in controlling a display of a client device and/or in controlling a visualized representation of the automated assistant. Various implementations utilize large language models (LLMs), or output previously generated utilizing LLMs, to reflect the given persona in the given assistant output.

Abstract: Implementations set forth herein relate to providing selectable autofill suggestions, which correspond to application actions that are at least partially fulfilled using server command data—prior to a user selecting a particular selectable autofill suggestion. Proactively fulfilling command data in this way mitigates latency between user selection of a suggestion and fulfillment of a particular action. Initially, a partial input can be processed to generate autofill suggestions, which can be communicated to a server device for further processing. The autofill suggestions can also be rendered for selection at a touch display interface, thereby allowing a user to select one of the autofill suggestions. As command fulfillment data is provided by the server, the command fulfillment data can be available to a corresponding application(s) in order that any corresponding actions can be at least partially fulfilled prior to user selection.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an encoder neural network configured to receive a data item and to process the data item to output a compressed representation of the data item. In one aspect, a method includes, for each training data item: processing the data item using the encoder neural network to generate a latent representation of the training data item; processing the latent representation using a hyper-encoder neural network to determine a conditional entropy model; generating a compressed representation of the training data item; processing the compressed representation using a decoder neural network to generate a reconstruction of the training data item; processing the reconstruction of the training data item using a discriminator neural network to generate a discriminator network output; evaluating a first loss function; and determining an update to the current values of the encoder network parameters.

Abstract: A method includes generating a first asset token that represents control, by a first entity, of a portion of a physical communication asset. The method includes publishing, to a distributed ledger, ownership of the first asset token and receiving, from a second entity, a request to control the portion of the physical communication asset represented by the first asset token. In response to receiving the request, the method includes removing the first asset token from circulation on the distributed ledger and generating a second asset token representing control, by the second entity, of the portion of the physical communication asset. The method also includes publishing, to the distributed ledger, ownership of the second asset token and transferring, using the distributed ledger, ownership of the second asset token to the second entity.

Abstract: Implementations relate to an automated assistant that is capable of interacting with non-assistant applications that do not have functionality explicitly provided for interfacing with certain automated assistants. Application data, such as annotation data and/or GUI data, associated with a non-assistant application, can be processed to map such data into an embedding space. An assistant input command can then be processed and mapped to the same embedding space, and a distance from the assistant input command embedding and the non-assistant application data embedding can be determined. When the distance between the assistant input command embedding and the non-assistant application data embedding satisfies threshold(s), the automated assistant can generate instruction(s), for the non-assistant application, that correspond to the non-assistant application data.

Abstract: A first context update indicative of a present state associated with an application is received. A first contextual situation, among a plurality of contextual situations associated with a plurality of conditions, that corresponds to the first context update is identified. Identifying the first contextual situation includes implementing a decision tree to minimize a number of the plurality of conditions to be evaluated, identifying the first contextual situation using the decision tree, and determining one or more actions to be performed corresponding with the first contextual situation.

Abstract: A method includes identifying, within an image that represents a fingerprint, a plurality of keypoints. The method also includes determining a plurality of pixel vectors by transforming, for each respective keypoint, a corresponding two-dimensional (2D) array of pixel values associated with the respective keypoint into a corresponding pixel vector, and obtaining a plurality of filter vectors that represent, for each respective filter of a plurality of filters, a transformation of a corresponding 2D array of filter values of the respective filter into a corresponding filter vector. The method additionally includes convolving the plurality of keypoints with the plurality of filters by multiplying, using a tensor processing hardware, a pixel matrix formed by the plurality of pixel vectors and a filter matrix formed by the plurality of filter vectors, and determining, based on the convolving, a representation of the fingerprint.

Abstract: Systems, devices, and methods are described for mitigating or eliminating distortion patterns (such as those caused by one or more high-volume audio sources) in a display system such as a laser projection system. Frequency components of an incoming sound that correspond to one or more resonant frequencies of an optical reflector of the display system are determined to exceed a defined volume threshold. Responsive to that determination, a magnitude and phase of one or more harmonic motions of the optical reflector are measured. Sound waves are generated to destructively interfere with at least one frequency component corresponding to the resonant frequencies of the optical reflector.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting a continued conversation are disclosed. In one aspect, a method includes the actions of receiving first audio data of a first utterance. The actions further include obtaining a first transcription of the first utterance. The actions further include receiving second audio data of a second utterance. The actions further include obtaining a second transcription of the second utterance. The actions further include determining whether the second utterance includes a query directed to a query processing system based on analysis of the second transcription and the first transcription or a response to the first query. The actions further include configuring the data routing component to provide the second transcription of the second utterance to the query processing system as a second query or bypass routing the second transcription.

Abstract: Features of various implementations are used to control operation of a second electronic device from a first electronic device using indirect control methods and optical character recognition. In some implementations, communication between a primary set-top box and a supplemental set-top box is configured in order to avoid the need for one or more provider-specific APIs. For example, one aspect of the disclosure is a method of identifying commands that can be used to control one or more features of a primary set-top box (e.g., DVR or VOD features) by a supplemental set-top box issuing commands to the primary set-top box via a wireless (e.g., IR) transmitter, and then using optical character recognition to identify the outcomes of those commands as displayed on a primary TV display or secondary display.

Abstract: The technology provides a rich attention mechanism for structured information extraction of web pages and other electronic documents. An input layer of a model obtains system, information associated with the document, including field tokens representing respective fields to be extracted from the document, structured document type tokens associated, and text tokens from a text sequence in the document. An encoder connects the field tokens, the S type tokens and the text tokens according to a set of different attention patterns. The encoder generates an overall token representation based on the set of different attention patterns. An output layer of the model extracts a final text span for the each of the respective fields from the set of text tokens. The extracted final text span for each of the respective fields is stored in memory, and can be produced in response to a search query, analytics evaluation or other request.

Abstract: Methods, systems, and media for timing presentation of content are provided.

Abstract: Methods, apparatus, and computer readable media related to interaction between a user and an automated assistant during a dialog between the user and the automated assistant. Some implementations are directed to adapting a graphical and/or audible presentation of search results provided by the automated assistant for presentation to the user. The adaptation may be in response to attribute(s), of one or more of the search results, referenced in spoken and/or typed textual input provided by the user during the dialog. Some of those implementations may enable a user to provide textual input to navigate the search results within the dialog and within resource and/or interface constraints associated with the dialog. Some of those implementations may additionally and/or alternatively enable adapting, based on textual input provided by a user to the automated assistant, when and/or whether search results having certain attributes are provided to the user by the automated assistant.

Abstract: A computer-implemented method includes receiving a document insight request that requests document insights for a corpus of documents. The document insight request includes the corpus of documents, a set of entities contained within each document of the corpus of documents, and document insight request parameters that includes a confidence value threshold. The method also includes generating the document insights for the corpus of documents based on the confidence value threshold. Here, the document insights include an accuracy target and a user review rate target. The method also includes transmitting the document insights to the user device causing a graphical user interface to display the document insights on the user device.