Abstract: A computer-implemented method for optimizing the placement of previously selected breaks in a media item is provided herein. Embodiments of the method include steps of identifying a break in a media item, the break being associated with a first break point at a first time during playback of the media item. The method may also include steps of dynamically adjusting the placement of the breaks within the media item based on the performance of the media item.

Abstract: The present disclosure is directed to interactive voice navigation. In particular, a computing system can provide audio information including one or more navigation instructions to a user via a computing system associated with the user. The computing system can activate an audio sensor associated with the computing system. The computing system can collect, using the audio sensor, audio data associated with the user. The computing system can determine, based on the audio data, whether the audio data is associated with one or more navigation instructions. The computing system can, in accordance with a determination that the audio data is associated with one or more navigation instructions, determine a context-appropriate audio response. The computing system can provide the context-appropriate audio response to the user.

Abstract: The disclosed embodiments include computerized methods, systems, and devices, including computer programs encoded on a computer storage medium, for generating terms of a search query based on a user's spoken utterances, identifying multiple cross-platform messages based on the generated terms, and to generating, via a presentation device, a single interface that enables the user to interact with identified messages. Based on a spoken utterance, the disclosed embodiments may determine user-specified search terms and/or criteria, and based on the user-specified search terms and/or criteria, may obtain cross-platform message data that corresponds to the search query. The communications device may generate one or more interface elements that describe corresponding ones of the cross-platform messages, which may be presented within a unified graphical user interface or voice-user interface by a communications device.

Abstract: Techniques are described herein for detecting and/or enrolling (or commissioning) new “hot commands” that are useable to cause an automated assistant to perform responsive action(s) without having to be first explicitly invoked. In various implementations, an automated assistant may be transitioned from a limited listening state into a full speech recognition state in response to a trigger event. While in the full speech recognition state, the automated assistant may receive and perform speech recognition processing on a spoken command from a user to generate a textual command. The textual command may be determined to satisfy a frequency threshold in a corpus of textual commands Consequently, data indicative of the textual command may be enrolled as a hot command. Subsequent utterance of another textual command that is semantically consistent with the textual command may trigger performance of a responsive action by the automated assistant, without requiring explicit invocation.

Abstract: A computing system and method that can be used for safe and privacy preserving video representations of participants in a videoconference. In particular, the present disclosure provides a general pipeline for generating reconstructions of videoconference participants based on semantic statuses and/or activity statuses of the participants. The systems and methods of the present disclosure allow for videoconferences that convey necessary or meaningful information of participants through presentation of generalized representations of participants while filtering unnecessary or unwanted information from the representations by leveraging machine-learning models.

Abstract: A comprehensive cybersecurity platform includes a cybersecurity intelligence hub, a cybersecurity sensor and one or more endpoints communicatively coupled to the cybersecurity sensor, where the platform allows for efficient scaling, analysis, and detection of malware and/or malicious activity. An endpoint includes a local data store and an agent that monitors for one or more types of events being performed on the endpoint, and performs deduplication within the local data store to identify “distinct” events. The agent provides the collected metadata of distinct events to the cybersecurity sensor which also performs deduplication within a local data store. The cybersecurity sensor sends all distinct events and/or file objects to a cybersecurity intelligence hub for analysis. The cybersecurity intelligence hub is coupled to a data management and analytics engine (DMAE) that analyzes the event and/or object using multiple services to render a verdict (e.g., benign or malicious) and issues an alert.

Abstract: Implementations described herein are directed to enabling collaborative ranking of interpretations of spoken utterances based on data that is available to an automated assistant and third-party agent(s), respectively. The automated assistant can determine first-party interpretation(s) of a spoken utterance provided by a user, and can cause the third-party agent(s) to determine third-party interpretation(s) of the spoken utterance provided by the user. In some implementations, the automated assistant can select a given interpretation, from the first-party interpretation(s) and the third-party interpretation(s), of the spoken utterance, and can cause a given third-party agent to satisfy the spoken utterance based on the given interpretation.

Abstract: Remote automated assistant component(s) generate client device notification(s) based on a received IoT state change notification that indicates a change in at least one state associated with at least one IoT device. The generated client device notification(s) can each indicate the change in state associated with the at least one IoT device, and can optionally indicate the at least one IoT device. Further, the remote automated assistant component(s) can identify candidate assistant client devices that are associated with the at least one IoT device, and determine whether each of the one or more of the candidate assistant client device(s) should render a corresponding client device notification.

Abstract: Routing packetized actions in a voice activated data packet based computer network environment is provided. A system can receive audio signals detected by a microphone of a device. The system can parse the audio signal to identify trigger keyword and request, and generate an action data structure. The system can transmit the action data structure to a third party provider device. The system can receive an indication from the third party provider device that a communication session was established with the device.

Abstract: Implementations can reduce the time required to obtain responses from an automated assistant through proactive caching, locally at a client device, of proactive assistant cache entries—and through on-device utilization of the proactive assistant cache entries. Different proactive cache entries can be provided to different client devices, and various implementations relate to technique(s) utilized in determining which proactive cache entries to provide to which client devices. In some of those implementations, in determining which proactive cache entries to provide (proactively or in response to a request) to a given client device, a remote system selects, from a superset of candidate proactive cache entries, a subset of the cache entries for providing to the given client device.

Abstract: A three dimensional neural network accelerator that includes a first neural network accelerator tile that includes a first transmission coil, and a second neural network accelerator tile that includes a second transmission coil, wherein the first neural network accelerator tile is adjacent to and aligned vertically with the second neural network accelerator tile, and wherein the first transmission coil is configured to wirelessly communicate with the second transmission coil via inductive coupling.

Abstract: Automatically communicating information related to a user computing device from a central computing system to a transaction computing system prior to initiation of a transaction between the user computing device and the transaction computing system comprises a digital wallet application and a central computing system. A digital wallet application receives a beacon signal from a transaction computing system indicating the specific identification of the terminal with which the user intends to conduct a transaction. The user computing device communicates the terminal identification to the central computing system. The central computing system communicates customer data, such as loyalty information and offers, to the transaction computing system associated with the terminal. The transaction computing system communicates the customer data to the terminal. When the user taps the user computing device to initiate the transaction, the terminal provides any benefits associated with the customer data.

Abstract: The present disclosure provides systems and methods that perform machine-learned natural language processing. A computing system can include a machine-learned natural language processing model that includes an encoder model trained to receive a natural language text body and output a knowledge graph and a programmer model trained to receive a natural language question and output a program. The computing system can include a computer-readable medium storing instructions that, when executed, cause the processor to perform operations. The operations can include obtaining the natural language text body, inputting the natural language text body into the encoder model, receiving, as an output of the encoder model, the knowledge graph, obtaining the natural language question, inputting the natural language question into the programmer model, receiving the program as an output of the programmer model, and executing the program on the knowledge graph to produce an answer to the natural language question.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for introducing a user to functions of various applications through interactions with an assistant agent. The assistant agent can correspond to an assistant application that can provide a user interface with multiple selectable elements, each of which can correspond to a separate application. When a user selects one of the selectable elements, a function of an application can be demonstrated to the user, in order that the user might become more familiar with functions of the application. In some implementations, a portion of the selectable element can be selected to cause information about the application to be presented to the user. This allows the user to have the option to try out or learn about an application before investing computational resources through downloading and installing the entire application.

Abstract: PWM-frame rate misalignment is mitigated through implementation of a discrete variable refresh rate (VRR) scheme. A target frame rate is limited to a frame rate selected from only those frame rates that facilitate alignment of each frame period to a specified edge of a PWM cycle of a brightness control signal of a display panel. This alignment results in each frame period at the selected frame rate starting at a same point in a corresponding PWM cycle and ending at a same point in a corresponding PWM cycle to help ensure a constant effective duty cycle across each successive frame period, which in turn mitigates perception of flicker that otherwise would arise. Further, the discrete VRR scheme can employ a compensation mode for compensating for the delay in rendering or otherwise obtaining a frame for display so as to maintain a consistent duty cycle in the brightness control signal.

Abstract: Implementations set forth herein relate to an automated assistant that uses circumstantial condition data, generated based on circumstantial conditions of an input, to determine whether the input should affect an action been initialized by a particular user. The automated assistant can allow each user to manipulate their respective ongoing action without necessitating interruptions for soliciting explicit user authentication. For example, when an individual in a group of persons interacts with the automated assistant to initialize or affect a particular ongoing action, the automated assistant can generate data that correlates that individual to the particular ongoing action. The data can be generated using a variety of different input modalities, which can be dynamically selected based on changing circumstances of the individual. Therefore, different sets of input modalities can be processed each time a user provides an input for modifying an ongoing action and/or initializing another action.

Abstract: Techniques described herein relate to facilitating end-to-end multilingual communications with automated assistants. In various implementations, speech recognition output may be generated based on voice input in a first language. A first language intent may be identified based on the speech recognition output and fulfilled in order to generate a first natural language output candidate in the first language. At least part of the speech recognition output may be translated to a second language to generate an at least partial translation, which may then be used to identify a second language intent that is fulfilled to generate a second natural language output candidate in the second language. Scores may be determined for the first and second natural language output candidates, and based on the scores, a natural language output may be selected for presentation.