Abstract: A resonant drive circuit for a capacitive sensor device includes a resonant LC stage, a signal source, and an amplifier stage. The resonant LC stage includes an inductorless floating gyrator circuit electrically connected to a sense capacitor. The inductorless floating gyrator circuit is configured to synthesize a fixed inductance. The resonant LC stage is configured to output a sensed capacitance signal based on the fixed inductance and a change in capacitance of the sense capacitor. The signal source is configured to output a reference signal. The amplifier stage is configured to receive the sensed capacitance signal and the reference signal and output a measured capacitance signal that indicates a difference in one or more of amplitude and phase between the sensed capacitance signal and the reference signal.

Abstract: A computing system including a processor configured to transmit, to a client computing device, a data quality specification prompt including a data quality specification template. The processor may receive a data quality specification from the client computing device. The data quality specification may be an at least partially filled copy of the data quality specification template and may include a data quality rule for entries included in a database. The data quality specification may further include a violation rate threshold for the data quality rule. The processor may store the data quality specification in memory. As specified by the data quality specification, the processor may determine that among the entries, a proportion of the entries exceeding the violation rate threshold violate the data quality rule. The processor may transmit a data quality rule violation notification to the client computing device.

Abstract: The description relates to representing acoustic characteristics of real or virtual scenes. One method includes generating directional impulse responses for a scene. The directional impulse responses can correspond to sound departing from multiple sound source locations and arriving at multiple listener locations in the scene. The method can include processing the directional impulse responses to obtain coherent sound signals and incoherent sound signals. The method can also include encoding first perceptual acoustic parameters from the coherent sound signals and second perceptual acoustic parameters from the incoherent sound signals, and outputting the encoded first perceptual acoustic parameters and the encoded second perceptual acoustic parameters.

Abstract: A computing system including one or more processors configured to train a data quality machine learning model at least in part by receiving training data including a plurality of training datasets that each include a plurality of training entries. Training the data quality machine learning model may further include receiving a plurality of training data quality rules respectively associated with the training datasets, and, using the training data quality rules and the training datasets, performing a respective plurality of model parameter updating iterations. The one or more processors may receive a runtime dataset including a plurality of runtime entries, and, at the data quality machine learning model, generate a runtime data quality rule based at least in part on the plurality of runtime entries. The one or more processors may transmit an indication of the runtime data quality rule for output at a graphical user interface.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine-readable instructions that when executed by the processor, may cause the processor to cause a graphical user interface to be displayed, the graphical user interface including graphical icons of a plurality of authentication types available for assignment to users and a graphical icon of a first user. The instructions may also cause the processor to detect a movement of a graphical icon of a first authentication type from a first location to a second location in the graphical user interface, the second location corresponding to the graphical icon of the first user and based on the detected movement, assign the first authentication type to the first user.

Abstract: The combination of active and reference haptics on an electronic device, such as a wearable display device, can convey information to a user without requiring the user to look at the device. An electronic device may include a housing, a display disposed in the housing and including an interface surface arranged for user contact and a reference haptic. The interface surface includes an active haptic output that provides a time-dependent haptic output and a reference haptic disposed on the housing or the interface surface to provide a time-independent haptic output related to the time-dependent haptic output.

Abstract: A computing system is provided, including a processor configured to identify a plurality of measurement sequences that implement a logic gate. Each measurement sequence may include a plurality of measurements of a quantum state of a topological quantum computing device. The processor may be further configured to determine a respective estimated total resource cost of each measurement sequence of the plurality of measurement sequences. The processor may be further configured to determine a first measurement sequence that has a lowest estimated total resource cost of the plurality of measurement sequences. The topological quantum computing device may be configured to implement the logic gate by applying the first measurement sequence to the quantum state.

Abstract: A computing device is provided, including a processor configured to receive a selection of a performance profile of a plurality of performance profiles. The performance profile may indicate a performance variable goal state for a first network stack component included in a network stack of a plurality of network stack components. In response to receiving the selection of the performance profile, the processor may be further configured to control a network performance parameter of the first network stack component such that a performance variable of the first network stack component approaches the performance variable goal state. The processor may be further configured to transmit, to an additional network stack component of the plurality of network stack components, instructions to control an additional network performance parameter of the additional network stack component such that the performance variable of the first network stack component approaches the performance variable goal state.

Abstract: A method for pollutant sensor placement for pollutants from point sources is described. Data about environmental characteristics for a geographic region are received from a plurality of environmental sensors. The geographic region includes pollutant sources that emit a pollutant. The received data from one or more of the plurality of environmental sensors are transformed into common data having a common spatial and temporal discretization across the geographic region. Predicted emission plumes are generated for the pollutant sources within the geographic region that identify pollutant detection regions for the pollutant when the pollutant is emitted by the pollutant sources using the common data. Sensor locations for a plurality of pollutant sensors are greedily selected across the common spatial and temporal discretization according to a number of predicted emission plumes that are detectable by the plurality of pollutant sensors.

Abstract: A data processing system implements obtaining a set of first input parameters associated with a first update to be deployed to one or more components of a cloud-based service; providing the set of first input parameters to a machine learning model to obtain a first deployment policy for the first update; analyzing the set of first input parameters using the machine learning model to generate the first deployment policy, the machine learning model being trained to analyze input parameters associated with an update to be deployed to the cloud-based service and to generate a deployment policy for the update, the deployment policy identifying a set of rings for deploying the update and when the update is to be deployed to a subset of the userbase of the cloud-based service associated with that ring; and executing the first deployment policy to deploy the update to the one or more components.

Abstract: A computing device is provided, including a storage device configured to store image data and a processor coupled to a memory that stores instructions, which, upon execution by the processor, cause the processor to select a target image from the image data. The processor is further configured to display conversion possibility information that indicates that the target image can be converted into a larger image that has a larger field of view by stitching other images together with at least a portion of the target image and an associated selector. The processor is further configured to display the larger image upon receiving a user selection of the selector.

Abstract: A system and method and for retrieving one or more visual assets includes receiving a search query for the one or more visual assets, the search query including textual data, encoding the textual data into one or more text embedding representations via a trained text representation machine-learning (ML) model, transmitting the one or more text embedding representations to a matching and selection unit, providing visual embedding representations of one or more visual assets to the matching and selection unit, comparing, by the matching and selection unit, the one or more text embedding representations to the visual embedding representations to identify one or more visual asset search results, and providing the one or more visual asset search results for display.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine-readable instructions that when executed by the processor, may cause the processor to receive a request for result data from a requestor and determine queries to create the result data. The processor may determine a subset of a data set based on the queries. The subset of the data set may be displayed in small multiples by the requestor. The processor may output the subset of the data set as the result data to the requestor. In some examples, the processor may receive a request for additional result data from the requestor. The processor may determine a second subset of the data set to be displayed in the small multiples and output the second subset of the data set as the additional result data to the requestor.

Abstract: The description relates to hinged devices, such as hinged computing devices. One example can include a first portion and a second portion that are rotatably secured relative to a hinge axis through a range of rotation from a closed orientation to an open orientation. The example can also include an oblong friction shaft and a friction band secured to the first portion and defining an oblong aperture configured to receive the oblong friction shaft. At the closed orientation a major axis of the oblong friction shaft is aligned with a major axis of the oblong aperture to provide a relatively low resistance to rotation and at the open orientation the major axis of the oblong friction shaft is rotated relative to the major axis of the oblong aperture to provide a relatively high resistance to rotation.

Abstract: Techniques for adapting previously-annotated training examples into updated training examples for training a machine learning model are disclosed. One example includes a computer program that recognizes a find expression, a replacement expression, and a filtering constraint in which the filtering constraint distinguishes a subset of previously-annotated training examples from others of the previously-annotated training examples. An instance of the find expression is identified by the computer program within the subset of the previously-annotated training examples that were identified among the previously-annotated training examples based on the filtering constraint. The instance of the find expression identified within the subset of the previously-annotated training examples is replaced by the computer program with an instance of the replacement expression to obtain an updated subset of training examples.

Abstract: A hinged mobile computing device includes a first housing part and a second housing part coupled by a hinge assembly having a harness, a harness cover, a first hinge body, and a second hinge body. The harness is configured to accommodate flexible printed circuitry and a cable that extend from the first housing part to the second housing part via the hinge assembly. The hinge bodies include respective friction bands, each friction band being configured to engage a respective shaft formed on the harness and having a gear configured to mesh with a respective cog arranged within the harness cover to coordinate a timing of the rotation of the first and second housing parts between face-to-face and back-to-back orientations. The hinge assembly further includes a spring-loaded opening mechanism.

Abstract: A secured virtual container is enabled to securely store personal data corresponding to a user, where such data is inaccessible to processes running outside the secured virtual container. The secured virtual container may also include an execution environment for a machine learning model where the model is securely stored and inaccessible. Personal data may be feature engineered and provided to the machine learning model for training purposes and/or to generate inference values corresponding to the user data. Inference values may thereafter be relayed by a broker application from the secured virtual container to applications external to the container. Applications may perform hyper-personalization operations based at least in part on received inference values. The broker application may enable external applications to subscribe to notifications regarding availability of inference values. The broker may also provide inference values in response to a query.

Abstract: A multiplex assay for nucleic acid detection includes a substrate, a sample, and a fluorophore-labeled oligonucleotide. The substrate has a plurality of physically separated assay locations, each of which includes a nucleotide-targeting enzyme configured to cleave nucleic acids, a guide ribonucleic acid (gRNA), and a quencher-labeled oligonucleotide. A portion of the sample is distributed to each assay location. The gRNA recognizes target nucleic acid in the sample, thereby activating the nucleotide-targeting enzyme to cleave nucleic acids, including the quencher-labeled oligonucleotide. The fluorophore-labeled oligonucleotide is subsequently added to each assay location, which facilitates identification of a presence of the target nucleic acid in the sample via detection of unquenched light emitted by the fluorophore in one or more of the plurality of assay locations.

Abstract: Systems and methods are provided for sorting cells with distinct cell designs for characterizing a library of the cell designs. The present disclosure uses randomized sorting rules associated with bins and pseudo-random numbers to counts the cells with measured fluorescence values in one of the bins. A mean fluorescence value for a cell design group may be determined based on a ratio of cell counts of the cells associated with the cell design group across the bins. Unlike the traditional histogram-based sorting that use a mean fluorescence value of a bin, the disclosed technology determines mean fluorescence values of cell design groups for characterizing libraries of the cell design group. Use of the mean fluorescence values with unbiased “sort-seq” and a de-multiplexed sequencing using the mean fluorescence values enables characterizing libraries of cell designs with improved accuracy over traditional use of discrete histograms.

Abstract: One example provides a computing device including a first portion including a first display, a second portion including a second display and a camera, the second portion connected to the first portion via a hinge, a hinge angle sensing mechanism including one or more sensors, a logic device, and a storage device holding instructions executable by the logic device to execute a camera application and to receive sensor data from the one or more sensors, based at least in part on the sensor data received from the one or more sensors, determine a device pose, output the camera application to the first display when the device pose is indicative of the camera being world-facing, and output the camera application to the second display when the device pose is indicative of the camera being user-facing.

Abstract: A computing system including one or more processors configured to receive an audio input. The one or more processors may generate a text transcription of the audio input at a sequence-to-sequence speech recognition model, which may assign a respective plurality of external-model text tokens to a plurality of frames included in the audio input. Each external-model text token may have an external-model alignment within the audio input. Based on the audio input, the one or more processors may generate a plurality of hidden states. Based on the plurality of hidden states, the one or more processors may generate a plurality of output text tokens. Each output text token may have a corresponding output alignment within the audio input. For each output text token, a latency between the output alignment and the external-model alignment may be below a predetermined latency threshold. The one or more processors may output the text transcription.

Abstract: Systems and methods are provided for determining a response to a query in a dialog. An entity extractor extracts rules and conditions associated with the query and determines a particular task. The disclosed technology generates a transformer-based dialog embedding by pre-training a transformer using dialog corpora including a plurality of tasks. A task-specific classifier generates a first set of candidate responses based on rules and conditions associated with the task. The transformer-based dialog embedding generates a second set of candidate responses to the query. The classifier accommodates changes made to a task by an interactive dialog editor as machine teaching. A response generator generates a response based on the first and second sets of candidate responses using an optimization function.

Abstract: A transformer is described herein for using transformer-based technology to process data items (e.g., image items). The transformer increases the efficiency of the transformer-based technology by using a modified attention component. In operation, the modified attention component accepts embedding vectors that represent a plurality of item tokens, together with a classification token. A first stage of the modified attention component generates original attention information based on the embedding vectors. A second stage generates score information based on a portion of the original attention information that pertains to the classification token. A third stage produces modified attention information by removing attention values from the original attention information, as guided by a sampling operation that is performed on the score information. The second and third stages do not rely on machine-trained values, which expedites the deployment of these functions in existing transformers.

Abstract: Described herein is a user interface that enables messages within a collaborative workspace environment to be propagated to different workspaces that are associated with different tabs in the collaborative workspace environment. Thus, a comment made in a workspace associated with a first tab is reflected in a workspace associated with a different tab and vice versa.

Abstract: A link-analyzing system (LAS) extracts information from a markup language (ML) document associated with a web page link. In some implementations, the information that is extracted includes at least: a) address content that is part of the link's destination address; and b) text that is associated with the link but that is not part of the destination address itself. The LAS generates feature information based on the address content and the text, and then uses a classification model to make a classification assessment for the link based on the feature information. In some implementations, the LAS can control a crawling engine based on the classification assessment. In some implementations, the LAS can revise a low-confidence classification assessment based on an examination of the classification assessments of a group of similar links described by the ML document. Other implementations use the above-described functionality to classify other parts of an ML document.

Abstract: A computing device, including memory, an accelerator device, and a processor. The processor may generate a plurality of data packs that each indicate an update to a variable of one or more variables of a combinatorial cost function. The processor may transmit the plurality of data packs to the accelerator device. The accelerator device may, for each data pack, retrieve a variable value of the variable indicated by the data pack and generate an updated variable value. The accelerator device may generate an updated cost function value based on the updated variable value. The accelerator device may be further configured to determine a transition probability using a Monte Carlo algorithm and may store the updated variable value and the updated cost function value with the transition probability. The accelerator device may output a final updated cost function value to the processor.

Abstract: A method for training a language model comprises (a) receiving vectorized training data as input to a multitask pretraining problem; (b) generating modified vectorized training data based on the vectorized training data, according to an upstream data embedding; (c) emitting pretraining output based on the modified vectorized training data, according to a downstream data embedding equivalent to the upstream data embedding; and (d) adjusting the upstream data embedding and the downstream data embedding by computing, based on the pretraining output, a gradient of the upstream data embedding disentangled from a gradient of the downstream data embedding, thereby advancing the multitask pretraining problem toward a pretrained state.

Abstract: A computer system is provided that includes one or more processors configured to receive user input for inked content to a digital canvas, and process the inked content to determine one or more writing regions. Each writing region includes recognized text and one or more document layout features associated with that writing region. The one or more processors are further configured to tokenize a target writing region of the one or more writing regions into a sequence of tokens, process the sequence of tokens of the target writing region using task extraction subsystem that operates on tokens representing both the recognized text and the one or more document layout features of the target writing region, segment the target writing region into one or more sentence segments, and classify each of the one or more sentence segments as a task sentence or a non-task sentence.

Abstract: Traditionally, meetings are widely utilized in business and personal communications, whether in-person and/or virtual. Organizing such meetings typically involves multiple exchanges of content and messages between users before, during, and after the meeting. In some cases, meetings may occur impromptu and may result in inefficient and unproductive collaboration. A collaboration object configured to enable users to dynamically collaborate before, during, and after a meeting is provided. In aspects, the collaboration object links content generated before, during, and after the meeting in a single location and provides functionality for concurrent multi-user interaction and synchronization of the content across applications. The collaboration object may be available from a variety of application platforms, enabling and persisting real-time editing and collaboration before, during and after the meeting.

Abstract: A method to predict a traversal-time interval for traversal of a service queue comprises receiving video of a region including the service queue, recognizing in the video, via machine vision, a plurality of persons awaiting service within the region, estimating an average crossing-time interval between successive crossings, by the plurality of persons, of a fixed boundary along the service queue, wherein such estimating is based on features of the service queue and of the one or more persons awaiting service, and returning an estimate of the traversal-time interval based on a count of the persons awaiting service and on the average crossing-time interval as estimated.

Abstract: Innovations in use of chroma quantization parameter (“QP”) offsets when determining a control parameter for deblock filtering. For example, as part of encoding, an encoder sets a picture-level chroma QP offset and slice-level chroma QP offset for encoding of a slice of a picture. The encoder also performs deblock filtering of at least part of the slice, where derivation of a control parameter considers only the picture-level chroma QP offset. The encoder outputs at least part of a bitstream including the encoded content. As part of decoding, a corresponding decoder sets a picture-level chroma QP offset and a slice-level chroma QP offset for decoding of a slice of a picture, but derivation of a control parameter for deblock filtering considers only the picture-level chroma QP offset.

Abstract: A method for classifying a tenant as being associated with one of a plurality of customer categories includes receiving a request to classify a tenant as being associated with one of a plurality of customer categories, dynamically retrieving from one or more data source systems, a plurality of data signals associated with the tenant, one or more of the plurality of data signals being stored as individual properties for the tenant in the one or more data source systems, dynamically identifying, in real-time, the tenant as being associated with one of the plurality of customer categories based at least on the plurality of data signals, and storing the identified one of the plurality of customer categories as a classification data signal for the tenant.

Abstract: A system and method for method for providing access to a resource includes receiving, from a user device of a user, a request to access the resource and an access token, the access token identifying an access role associated with the user and the request identifying a task to be performed on the resource; retrieving the access role from the access token; examining a role-to-permissions map to identify one or more permission available for the access role; determining, based on the available permissions for the access role that the user is authorized to perform the task on the resource; determining, based on the access role and the available permissions that the user has permission to access the resource managed by an object model; and upon determining that the user is authorized to perform the task on the resource and the user has permission to access the resource managed by the object model, permitting the user device of the user to access the resource to perform the task.

Abstract: A method and system for providing access to virtual desktops may include receiving an input indicating hovering of a pointer over an icon in a toolbar, identifying one or more existing virtual desktops, determining a state for each of the one or more existing virtual desktops by identifying one or more instances of any applications that are currently running in each of the one or more existing virtual desktops and determining a running state for each of the one or more instances, and displaying a preview of each of the one or more existing virtual desktops in response to the hovering of the pointer over the icon. The preview may include displaying the running state for one of the one or more instances for each existing virtual desktop.

Abstract: Embeddable extensions of the functionality of email and calendaring applications are described herein. An originating email and calendaring application formats meeting items to include extensible content, e.g., within the body field of the meeting item. Recipient email and calendaring applications receive the meeting items and, depending on whether they are configured to provide an extended functionality, will either deploy the extensible content item according to the extended functionality or present the extensible content item according to a standardized functionality. The body field includes the extensible content item according to the standardized functionality that is interpretable by configured clients to provide the extended functionality.

Abstract: A method of fabricating semiconductor-superconductor nanowires, comprising: forming a first mask amorphous mask having first openings over trenches in a substrate; forming a monocrystalline conducting material in the first openings by selective area growth, thus forming gates for the nanowires in the trenches pf the substrate; forming a second mask over the substrate and gates, the second mask also being amorphous and having a pattern of second openings; forming an insulating crystalline buffer in the second openings; forming a crystalline semiconductor material on the buffer in the second openings by selective area growth in order to form the cores of the nanowires, wherein the gates intersect with the cores in the plane of the substrate; and forming the coating of superconductor material over at least part of each of the cores.

Abstract: In a numerical simulation, input data expressed in at least a first domain is received. The input data is decomposed into at least i) low-pass filtered data that captures a low-pass filtered version of the input data in the at least the first domain and ii) high-pass filtered data that captures a high-pass filtered version of the input data in the at least the first domain. The low-pass filtered data is transformed to frequency domain, and weights are applied to the low-pass filtered data in the frequency domain to generate weighted low-pass filtered data in the frequency domain. The weighted low-pass filtered data is transformed from the frequency domain to the at least the first domain, and output data for the numerical simulation is composed based on at least the weighted low-pass filtered data in the at least the first domain.

Abstract: Techniques of memory tiering in computing devices are disclosed herein. One example technique includes retrieving, from a first tier in a first memory, data from a data portion and metadata from a metadata portion of the first tier upon receiving a request to read data corresponding to a system memory section. The method can then include analyzing the data location information to determine whether the first tier currently contains data corresponding to the system memory section in the received request. In response to determining that the first tier currently contains data corresponding to the system memory section in the received request, transmitting the retrieved data from the data portion of the first memory to the processor in response to the received request. Otherwise, the method can include identifying a memory location in the first or second memory that contains data corresponding to the system memory section and retrieving the data from the identified memory location.

Abstract: In a numerical simulation, input data expressed in at least a first domain is received. The input data is transformed to generate frequency modes of the input data in frequency domain. The transformed data is down-sampled to retain a subset of the frequency modes in the frequency domain. The down-sampled data is successively processed with one or more stages of a neural network to generate a down-sampled output in the frequency domain. The processing includes applying, in each stage of the one or more stages, a non-linear transformation to the subset of the frequency modes. The down-sampled output is then up-sampled to generate an up-sampled output corresponding to the frequency modes in the frequency domain, and the up-sampled output is transformed from the frequency domain to the at least the first domain to generate a result of the numerical simulation.

Abstract: Examples are disclosed herein relating to signal processing in a time of flight (ToF) system. One example provides, a method comprising emitting, via a light source, amplitude-modulated light toward an object, acquiring, via an image sensor comprising a plurality of pixels, a plurality of image frames capturing light emitted from the light source that is reflected by the object, wherein the plurality of image frames are acquired at two or more different frequencies of the amplitude-modulated light and collectively form a multifrequency frame, and for each pixel of the multifrequency frame, determining a brightness level, applying an adaptive denoising process by setting a kernel size based on the brightness level, and performing a phase unwrapping process to determine a depth value for the pixel.

Abstract: Conversational understanding systems allow users to conversationally interface with a computing device. In examples, a query may be received that includes a request for execution of a task. A data exchange task definition may be accessed. The data exchange task definition assists a conversational understanding system in managing task state tracking for information needed for task execution. Using the data exchange task definition, a per-turn policy for interacting with the user computing device is generated based on the state of a dialogue with a computing device and an evaluation of a process flow chart provided by a task owner resource. The task owner resource may be independent from the conversational understanding system. A response to the query may be generated and output based on the per-turn policy. In examples, the per-turn policy is used to generate one or more responses during a dialogue with a user via a computing device.

Abstract: One aspect provides semiconductor-superconductor hybrid device comprises a substrate, a first semiconductor component arranged on the substrate, a superconductor component arranged to be capable of energy level hybridisation with the first semiconductor component, and a second semiconductor component arranged as a gate electrode for gating the first semiconductor component. Another aspect provides a semiconductor-superconductor hybrid device, comprising: a substrate; a semiconductor component arranged on the substrate; a gate electrode for gating the semiconductor component; and a superconductor component capable of undergoing energy level hybridisation with the semiconductor component; wherein the gate electrode is arranged in a channel in the substrate. Also provided are methods of fabricating the semiconductor-superconductor hybrid devices.

Abstract: A computing device including a processor configured to simulate a quantum device at least in part by receiving a single-particle Hamiltonian matrix that describes an initial Hamiltonian operator. The initial Hamiltonian operator may model a plurality of parts of a quantum device. Simulating the quantum device may further include estimating a reduced density matrix associated with a first part, estimating a plurality of eigenvectors and eigenvalues of the reduced density matrix, and generating a transformed Hamiltonian matrix. Generating the transformed Hamiltonian matrix may include transforming the single-particle Hamiltonian matrix into a natural-orbital basis of the first part such that the transformed Hamiltonian matrix has a reduced dimensionality. The natural-orbital basis may be spanned by a subset of the eigenvectors of the reduced density matrix.

Abstract: A data processing system implements receiving, from a first user, a first request to submit a first template for an electronic document to a template publication service, the request includes first policy information indicating who may access the template and is available only to users who are associated with a first organization; storing the first template and the first policy information in a template data store; receiving, from a second user, a second request for available templates from the template data store; determining that the second user has access to the first template based on the policy information and the information identifying the second user indicating that the second user is associated with the first organization; including the first template in a plurality of first templates determined to be available to the second user; and causing the plurality of first templates available to the second user to be displayed.

Abstract: A server computing device generates training data based upon an identifier for a device, a timestamp, and a label received from a developer computing device. The server computing device trains a computer-implemented machine learning (ML) model based upon the training data. The server computing device also generates client configuration data for the ML model that specifies transformations that are to be applied to values in order to generate input values for the ML model. The server computing device deploys ML assets to client computing devices, the ML assets comprising the ML model and the client configuration data. The client computing devices execute the ML model using input values derived via transformations of (local) values produced by the client computing devices and transmit telemetry data to the server computing device. The server computing device updates the ML assets based upon the telemetry data.

Abstract: A data processing system implements techniques for provisioning and operating databases including receiving a request to provision a new database that includes multiple replicas. The data processing system provisions the new database including the plurality of replicas. The plurality of replicas includes a primary replica, one or more secondary replicas, and one or more delta replicas. The primary replica is configured to handle read and write operations. The one or more secondary replicas include a copy of data and transactional log information of the primary replica and are unable to handle write operations. The one or more delta replicas are a copy of the transactional log information of the primary replica and are unable to handle read operations or write operations.

Abstract: A computing device for organizing a collaborative workspace for a user implements providing, using a display of the computing device, an interactive user interface associated with the collaborative workspace in which the user may work on a shared task in a coordinated fashion with other users; identifying, based on one or more factors, one or more activities specific to the user from within the collaborative workspace; assigning the identified one or more activities to a catch-up list associated with the user; displaying, within the interactive user interface, the catch-up list; detecting that at least one of the one or more activities has been addressed from within the collaborative workspace or the catch-up list; and updating, based on the detection, the collaborative workspace and the catch-up list.

Abstract: A system to detect an abnormal classic authorizations, such as in a classic authorization system of a resource access management system, and take action is described. The system determines an anomaly score in from a model applied to a classic assignment event. An indicator score is determined from the classic assignment event applied to domain-based rules. The security action is taken based on a combination of the anomaly score and the indicator score.

Abstract: Systems and methods are provided for determining faces and bodies of people in an image by adaptively scaling images and by iteratively using a deep neural network for inferencing. A camera captures an image including faces and bodies of people. A face/body determiner determines faces and bodies of people appearing in the image by resizing the image into a predetermined pixel dimension as input to the deep neural network. A region cropper determines a crop region associated with a low level of confidence in detecting faces and bodies that are too small to determine with an acceptable level of confidence. The region cropper resizes the crop region into the predetermined pixel dimension as input to the deep neural network. The face and body determiner determines other faces and bodies appearing in the resized crop region. An aggregator aggregates locations of the determined faces and bodies in the image.

Abstract: One example provides a computing device comprising a logic machine and a storage machine holding instructions executable by the logic machine to implement a depth image processing pipeline comprising a neural network, the neural network comprising an edge detecting layer. The neural network is configured to receive input of an active brightness image and receive input of one or more of real data or imaginary data of a complex depth image, the complex depth image corresponding to the active brightness image. The neural network is further configured to, at the edge detecting layer, apply one or more convolutional processes to the active brightness image to identify one or more edge pixels in the active brightness image, and at a second layer, denoise one or more of the real data or the imaginary data of the complex depth image based on the one or more edge pixels identified.