Abstract: The present disclosure provides methods, systems, and devices for non-invasively measuring a level of an analyte in a user using Stimulated Raman Scattering. A device can include a Raman pump source that emits pump light toward a tissue at a pump wavelength and a Stokes source that emits Stokes light toward the tissue at one or more Stokes wavelengths. The device can further include one or more mirrors and lenses. The device can further include a beam controller that controls the one or more mirrors and the one or more lenses to target the pump light emitted by the Raman pump source and the Stokes light emitted by the Stokes source at an optimal target location. The device can further include a photodetector that measures light that emanates from the tissue. The device can further include a processor that estimates the level of the analyte in the user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying data objects. One of the methods includes obtaining data that associates each term in a vocabulary of terms with a respective high-dimensional representation of the term; obtaining classification data for a data object, wherein the classification data includes a respective score for each of a plurality of categories, and wherein each of the categories is associated with a respective category label; computing an aggregate high-dimensional representation for the data object from high-dimensional representations for the category labels associated with the categories and the respective scores; identifying a first term in the vocabulary of terms having a high-dimensional representation that is closest to the aggregate high-dimensional representation; and selecting the first term as a category label for the data object.

Abstract: To detect a change in lane marker geometry, a computing device receives map patch data from one or more vehicles within a geographic area indicative of measured lane marker positions. For each data point within the map patch data, the computing device determines an error metric based on one or more differences between one or more measured lane marker positions for the data point and one or more reference lane marker positions from a database. The computing device identifies relationships between the data points according to the error metric for each data point, a time when each data point was collected, or a location of each data point, and identifies a lane marker change event occurring within the geographic area based on the relationships between the data points. Then the computing device discards reference lane marker positions from the database corresponding to the lane marker change event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting hotwords using a server. One of the methods includes receiving an audio signal encoding one or more utterances including a first utterance; determining whether at least a portion of the first utterance satisfies a first threshold of being at least a portion of a key phrase; in response to determining that at least the portion of the first utterance satisfies the first threshold of being at least a portion of a key phrase, sending the audio signal to a server system that determines whether the first utterance satisfies a second threshold of being the key phrase, the second threshold being more restrictive than the first threshold; and receiving tagged text data representing the one or more utterances encoded in the audio signal when the server system determines that the first utterance satisfies the second threshold.

Abstract: A method includes receiving a request indication indicating a GUI interaction by a user on a user device, and in response, providing to the device a response configured to cause the device to display, within a GUI, a structured prompt including a plurality of user input fields, each user input field representing a corresponding training sample and including a first corresponding text input field for capturing input text to be provided to an ML model, and a second corresponding text input field for capturing ground-truth output text. The method also includes receiving, from the device, the training samples, and, in response, adjusting the ML model using the training samples. The method further includes receiving, from the device, test input text, generating, using the adjusted ML model, test output text based on the test input text, and providing, to the user device, the test output text for display within the GUI.

Abstract: A method for training a machine learning model included generating training data for the machine learning model. Generating the training data includes generating first training input that includes candidate text portions of one or more electronic documents and generating a first target output for the first training input. The first target output identifies a formatting type for each of the candidate text portions. The training data is provided to train the machine learning model on (i) a set of training inputs including the first training input, and (ii) a set of target outputs including the first target output.

Abstract: The technology is generally directed to determining whether a consumer being presented with a digital component is a disengaged and/or qualifying disengaged consumer at the time the digital component is being selected. An artificial intelligence model may be trained and used to predict whether the consumer is a disengaged and/or qualifying disengaged consumer. The prediction may be a probability representing the likelihood that the user is a disengaged and/or qualifying disengaged consumer for a given merchant. The probability may be used to dynamically adjust the merchant's bid at the time of auction to have the merchant's digital component selected. The probability may, in some examples, may be used to dynamically adjust the conversion values after the merchant's digital component is provided for output.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for the selection, provision and display of one or more digital components during display of content. Methods can include identifying a plurality of digital components that can be presented on the client device. A maximum number of digital components that can be presented in a slot of a content and the time duration of the slot is determined. For each digital component a score is generated based on the duration, a position requirement and the number of times the digital component is available for provision within the slot is generated. A first set of digital component is selected based on the scores and provided to the client device.

Abstract: The present document describes techniques for a magnetically self-shielded speaker box for a mobile device. The speaker box described herein includes a thin metal enclosure, thereby reducing or eliminating plastic components from the exterior enclosure of the speaker box. The metal of the enclosure has a high magnetic permeability to prevent penetration of a magnetic field generated by the speaker transducer within the exterior enclosure. Also, the exterior enclosure includes at least two enclosure portions that are joined together with a continuous welded seam. Accordingly, the speaker box described herein is a thin-walled, fully metal, high-permeability enclosure resulting in a smaller, self-shielded solution that reduces both (i) the total physical volume of the speaker box for a given internal speaker back volume and (ii) the spacing requirements to adjacent voice-coil-motor auto-focus camera modules.

Abstract: Generally disclosed herein is a mechanism to manage the thermal control of servers equipped in a data center based on the measurements of the power consumption of each server and each thermally critical component in the server system. A controller may monitor the power consumption of one or more components or one or more servers and trigger responsive cooling action by one or more cooling fans based on changes in the power consumption. In this regard, the cooling fans are proactively activated prior to temperatures reaching high levels, thereby efficiently maintaining safe operating temperatures in the data center for the computing devices and/or for occupational safety.

Abstract: A method includes obtaining a video having image frames, and determining, for each respective image frame, a corresponding frame content score based on a visual content thereof. The method also includes selecting, from the image frames, a plurality of video clips, where each respective video clip includes a plurality of consecutive image frames and is selected based on the corresponding frame content scores of the plurality of consecutive image frames thereof. The method additionally includes determining, for each respective video clip, a corresponding clip content score based on the corresponding frame content scores of the plurality of consecutive image frames thereof. The method further includes generating a highlight video that includes the plurality of video clips and a representation of a ranking of the plurality of video clips, where the ranking is based on the corresponding clip content score of each respective video clip.

Abstract: A system for repair of an accelerator architecture including a plurality of accelerator host having a plurality of accelerator elements in each host and high-speed interconnects between accelerator elements and including a link health monitor service in the host determining a status of each interconnect internal and external to the host. The link health monitor service detects link status of the interconnects and communicates this to a pod manager responsible for managing a number of interconnected hosts. The pod manager communicates with a scheduler for scheduling processing tasks to each accelerator element or group of elements. Upon detection of an interconnect problem, the pod manager flags a least common ancestor in a binary tree of elements containing elements adjacent to the failed interconnect and flags the ancestor and its parent nodes as unavailable. Pod manager further generates a corrective action repairing the problem interconnect communicating the action to a technician.

Abstract: A method includes obtaining a pre-trained machine learning model and a training embedding snapshot from a remote system, and obtaining one or more input data samples captured by a user device. The method includes, for each particular input data sample of the one or more input data samples, processing, using an on-device machine learning model corresponding to the pre-trained machine learning model, the particular input data sample to generate a corresponding on-device embedding and one or more corresponding predicted outputs, and generating, using the training embedding snapshot and the corresponding on-device embedding, corresponding performance data. The method includes aggregating the corresponding performance data for the one or more input data samples to determine one or more performance metrics for the on-device machine learning model, and transmitting the one or more performance metrics to the remote system.

Abstract: A method executed on data processing hardware and including displaying, on a display in communication with the data processing hardware, a user interface for a chat session between a user and a chatbot, the user interface including a plurality of entries input by the user and a plurality of corresponding responses from the chatbot. The method also includes receiving, in the user interface, a user input indication indicating selection of a particular entry of the plurality of entries, the particular entry being other than a last entry of the plurality of entries. The method further includes receiving, in the user interface, a new entry input by the user for an additional entry associated with the particular entry. The method additionally includes based on the additional entry associated with the particular entry, causing the chatbot to update one or more of the plurality of corresponding responses from the chatbot.

Abstract: Timestamp synchronization may be performed by determining a time offset between a first virtual machine having a first virtual clock counter of a computing system and a second virtual machine having a second virtual clock counter of the computing system; and adjusting timestamps of traces with timestamps based on the second virtual clock counter according to the time offset.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speeding up document loading. In some implementations, a resource of a document is requested from a first source, and metadata for the document is requested from a second source that is different from the first source. The requested metadata is received from the second source, and the requested resource is received from the first source. A first representation of the document based on the received metadata is provided for display. After providing the first representation, a second representation of the document that combines portions of the first representation with additional portions of the document is generated, and the second representation is provided for display.

Abstract: Implementations relate to ascertaining to what extent predictions, generated using a machine learning model, can be effectively reconstructed from model updates, where the model updates are generated based on those predictions and based on applying a particular loss technique (e.g., a particular cross-entropy loss technique). Some implementations disclosed generate measures that each indicate a degree of conformity between a corresponding reconstruction, generated using a corresponding model update, and a corresponding prediction. In some of those implementations, the measures are utilized in determining whether to utilize the particular loss technique (utilized in generating the model updates) in federated learning of the machine learning model and/or of additional machine learning model(s).

Abstract: Implementations process, using a large language model, a free-form natural language (NL) instruction to generate to generate LLM output. Those implementations generate, based on the LLM output and a NL skill description of a robotic skill, a task-grounding measure that reflects a probability of the skill description in the probability distribution of the LLM output. Those implementations further generate, based on the robotic skill and current environmental state data, a world-grounding measure that reflects a probability of the robotic skill being successful based on the current environmental state data. Those implementations further determine, based on both the task-grounding measure and the world-grounding measure, whether to implement the robotic skill.

Abstract: The present disclosure provides for Contextual Alerting Functions (CAFs). CAFs are an interface paradigm for synchronized device frameworks across multi-device ecosystems and user data models. CAFs replace existing concepts such as apps and/or notifications.

Abstract: A first base station communicates with a UE via the first base station and a second base station. The first base station transmits, via a radio interface to the second base station, a configuration for concurrent communication between the UE and a group of base stations including the first base station and the second base station. The first base station communicates, by processing hardware, data over the radio interface directly with the UE, and via the radio interface and the second base station.