Abstract: Disclosed herein are exemplary embodiments of methods, apparatus, and systems for performing content-adaptive deblocking to improve the visual quality of video images compressed using block-based motion-predictive video coding. For instance, in certain embodiments of the disclosed technology, edge information is obtained using global orientation energy edge detection (“OEED”) techniques on an initially deblocked image. OEED detection can provide a robust partition of local directional features (“LDFs”). For a local directional feature detected in the partition, a directional deblocking filter having an orientation corresponding to the orientation of the LDF can be used. The selected filter can have a filter orientation and activation thresholds that better preserve image details while reducing blocking artifacts. In certain embodiments, for a consecutive non-LDF region, extra smoothing can be imposed to suppress the visually severe blocking artifacts.

Abstract: A method to correct a fault in application of a Clifford circuit to a qubit register of a quantum computer comprises: (A) receiving circuit data defining the Clifford circuit; (B) emitting outcome code based on the circuit data, the outcome code including a series of outcome checks each corresponding to an anticipated error syndrome of the application of the Clifford circuit to the qubit register; and (C) emitting space-time quantum code corresponding to the Clifford circuit based on the circuit data and on the outcome code, the space-time quantum code including a series of check operators that support quantum-error correction, thereby enabling fault correction in the application of the Clifford circuit to the qubit register.

Abstract: Embodiments described herein are directed to implementing compliance settings by a computing device for bringing the computing device into compliance with a configuration scenario. For instance, a computing device may receive, from a server, configuration information describing compliance settings for implementing by the computing device to bring the computing device into compliance with a configuration scenario. Moreover, the computing device may identify a state machine indicated by the configuration information that describes a configuration process for implementing the compliance settings and execute the state machine to configure the computing device with the compliance settings.

Abstract: A data processing system obtains source textual content associated with a first writing style and target textual content associated with a second writing style and provides the source textual content as an input to a first machine learning model which analyzes the source content to determine the first writing style of the first textual content. The system provides an indication of the first writing style and the target textual content as an input to a second machine learning model which analyzes the target textual content and rewrites the target textual content according to the first writing style to output updated target textual content rewritten according to the first writing style. Some implementations utilize a single model trained to receive the source textual content, the target textual content, to determine the writing style of the source textual content and rewrite the target textual content according to the first writing style.

Abstract: A new processing architecture is described that utilizes a data processing unit (DPU). Unlike conventional compute models that are centered around a central processing unit (CPU), the DPU that is designed for a data-centric computing model in which the data processing tasks are centered around the DPU. The DPU may be viewed as a highly programmable, high-performance I/O and data-processing hub designed to aggregate and process network and storage I/O to and from other devices. The DPU comprises a network interface to connect to a network, one or more host interfaces to connect to one or more application processors or storage devices, and a multi-core processor with two or more processing cores executing a run-to-completion data plane operating system and one or more processing cores executing a multi-tasking control plane operating system. The data plane operating system is configured to support software functions for performing the data processing tasks.

Abstract: Examples are disclosed that relate to controlling power from a battery on a computing device. One example provides a power management system for a computing device having a battery powering first and second processing units. The power management system comprises a controller. The controller is configured to receive a RSOC of the battery and compute first and second current limit values based at least on the RSOC. The power management system further comprises a first power channel including a first first-stage regulator having a current limiter. The current limiter is configured to dynamically limit, to the first current value, a first current flowing from the battery to the first processing unit. The power management system further comprises a second power channel including a second first-stage regulator having a current limiter configured to dynamically limit, to the second current limit value, a second current flowing from the battery.

Abstract: A “Content Optimizer” applies a machine-learned relevancy model to predict levels of interest for segments of arbitrary content. Arbitrary content includes, but is not limited to, any combination of documents including text, charts, images, speech, etc. Various automated reports and suggestions for “reformatting” segments to modify the predicted levels of interest may then be presented. Similarly, the Content Optimizer applies a machine-learned comprehension model to predict what a human audience is likely to understand (e.g., a “comprehension prediction”) from the arbitrary content. Various automated reports and suggestions for “reformatting” segments to modify the comprehension prediction may then be presented.

Abstract: A method to build a lookup decoder for mapping error syndromes based on quantum-stabilizer code to corresponding error corrections comprises (A) enumerating a subset of error syndromes up to a maximum error weight based on the quantum-stabilizer code; (B) iterating through the subset of error syndromes to compute an error state of highest probability for each error syndrome of the subset, where the error state defines error in a qubit register of a quantum computer; and (C) for each error syndrome of the subset of error syndromes, storing in classical computer memory an error correction based on the error state of highest probability and mapped to that error syndrome.

Abstract: An optical fibre assembly comprises a hollow core optical waveguide comprising a hollow core surrounded by a structured arrangement of longitudinally extending capillaries providing an inner cladding surrounded by an outer cladding; a diagnostic solid core optical waveguide comprising a solid core surrounded by a cladding, and extending substantially parallel to the hollow core optical waveguide; and a jacket surrounding both the hollow core optical waveguide and the solid core optical waveguide and forming a common mechanical environment for the hollow core optical waveguide and the solid core optical waveguide. The optical fibre assembly may be or may comprise or be included in an optical fibre cable, and may be used in a method for testing hollow core optical waveguides.

Abstract: A disclosed hinge assembly for a head-mounted display device comprises a four-bar linkage. A first linkage of the four-bar linkage is mountable to or forms part of a wearable article for a head of a user. A second linkage and a third linkage of the four-bar linkage each rotatably couple the first linkage to a fourth linkage of the four-bar linkage. The fourth linkage of the four-bar linkage is mountable to or forms part of a display device. A disclosed head-mounted display device comprises a display device; a rearward mount by which the head-mounted display device is mountable to a wearable article for a head of a user; and a hinge assembly rotatably coupling the display device to the rearward mount. The hinge assembly includes a four-bar linkage that provides a path of travel for the display device along a curved path from a deployed state to a stowed state.

Abstract: Non-limiting examples of the present disclosure describe implementation of an exemplary synchronization protocol to identify file data for synchronization as well as negotiate how to achieve data transport for synchronization of the file data. In one example, a request for synchronization of data is received from a processing device. In response to receiving the request, a response is generated. The response may comprise: identification of file data for synchronization, instructions for accessing the file data and instructions indicating a data transport protocol to utilize to obtain the file data. The response may be transmitted to the processing device, for example, to enable the processing device to synchronize file data. Other examples are also described.

Abstract: This document relates to analyzing of network stack functionality that is implemented in hardware, such as on a network adapter. The disclosed implementations employ a programmable network device, such as a switch, to inject events into traffic and mirror the traffic for subsequent analysis. The events can have user-specified event parameters to test different types of network stack behavior, such as how the network adapters respond to corrupted packets, dropped packets, or explicit congestion notifications.

Abstract: Systems and methods are provided for learning classifiers for annotating a document with predicted labels under extreme classification where there are over a million labels. The learning includes receiving a joint graph including documents and labels as nodes. Multi-dimensional vector representations of a document (i.e., document representations) are generated based on graph convolution of the joint graph. Each document representation varies an extent of reliance on neighboring nodes to accommodate context. The document representations are feature-transformed using a residual layer. Per-label document representations are generated from the transformed document representations based on neighboring label attention. A classifier is trained for each of over a million labels based on joint learning using training data and the per-label document representation. The trained classifier performs highly efficiently as compared to other classifiers trained using disjoint graphs of documents and labels.

Abstract: In various embodiments, a computer-implemented method of training a neural network for creating an output signal of different modality from an input signal is described. In embodiments, the first modality may be a sound signal or a visual image and where the output signal would be a visual image or a sound signal, respectively. In embodiments a model is trained using a first pair of visual and audio networks to train a set of codebooks using known visual signals and the audio signals and using a second pair of visual and audio networks to further train the set of codebooks using the augmented visual signals and the augmented audio signals. Further, the first and the second visual networks are equally weighted and where the first and the second audio networks are equally weighted.

Abstract: A computing system including a classical computing device, including a processor that generates a Haar-random unitary matrix. The processor further computes a single-particle-basis fermion rotation based at least in part on the Haar-random unitary matrix and outputs the single-particle-basis fermion rotation to a quantum computing device. The quantum computing device receives a specification of a fermion wavefunction and further receives the single-particle-basis fermion rotation. The quantum computing device further applies the single-particle-basis fermion rotation to the fermion wavefunction. The quantum computing device further measures the rotated fermion wavefunction to obtain a classical shadow measurement result. The processor of the classical computing device further receives the classical shadow measurement result.

Abstract: According to examples, a processor may receive data pertaining to a communication sent over a network by a device, extract a set of characteristics associated with the communication from the received data, and determine whether the extracted set of characteristics meets a predefined similarity threshold with respect to a previously identified set of characteristics, in which the previously identified set of characteristics is assigned with a certain device type. The processor may also, based on a determination that the extracted set of characteristics meets the predefined similarity threshold with respect to the previously identified set of characteristics, assign the device with the certain device type.

Abstract: This document relates to training of machine learning models. One example method involves providing a machine learning model having a first classification layer, a second classification layer, and an encoder that feeds into the first classification layer and the second classification layer. The example method also involves obtaining first training examples having explicit labels and second training examples having inferred labels. The inferred labels are based at least on actions associated with the second training examples. The example method also involves training the machine learning model using the first training examples and the second training examples using a training objective that considers first training loss of the first classification layer for the explicit labels and second training loss of the second classification layer for the inferred labels. The method also involves outputting a trained machine learning model having the encoder and the first classification layer.

Abstract: Systems and methods are provided for training a data model based on training data. The training includes pre-training and fine-tuning the data model based on a combination of an autoregressive (AR) model and a non-autoregressive (NAR) model. Training data may be received and encoded into streams of tokens. A pre-trainer during decoding generates a continuum of data structures of the AR and NAR combined model including a main stream and a series of predicting streams. Masked tokens in predicting streams reference or attend to one or more preceding tokens in the main stream or the preceding predicting streams. A fine-tuner selects streams to generate a trained model according to a target data model. The target data model is determined based on balancing an accuracy constraint and an efficiency constraint for predicting tokens. The decoder acts as abridge between the AR and NAR models in generating a trained data model.

Abstract: A method for text compression comprises recognizing a prefix string of one or more text characters preceding a target string of a plurality of text characters to be compressed. The prefix string is provided to a natural language generation (NLG) model configured to output one or more predicted continuations each having an associated rank. If the one or more predicted continuations include a matching predicted continuation relative to the next one or more text characters of the target string, the next one or more text characters are compressed as an NLG-type compressed representation. If no predicted continuations match the next one or more text characters of the target string, a longest matching entry in a compression dictionary is identified. The next one or more text characters of the target string are compressed as a dictionary-type compressed representation that includes the dictionary index value of the longest matching entry.

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 identify configuration information to be used by an on-premise access management service to provide authentication services to applications by users. The processor may also transform the identified configuration information into a transformed set of configuration information to be used by a cloud-based access management service to provide authentication services to the applications by users. In addition, the processor may store the transformed set of configuration information for use by the cloud-based access management service to provide authentication services to the applications by users to migrate authentication of the users from the on-premise access management service to the cloud-based access management service.

Abstract: A system and method and for searching for an element in and replacement a portion of a video is conducted by retrieving the video and generating a video index for the video, the video index indexing a plurality of elements of the video such as text, audio and video. To search in the vide, a search query is received that includes at least one of a text element, an audio element, an image element, or a video element. Features and embeddings are extracted from the search query before comparing the search query features with the video index to identify a portion of the video that includes one of the text element, audio element, image element or video element of the search query. The identified portion is then automatically replaced with a replacement portion to generate a revised video.

Abstract: A method for multi-intent searching includes surfacing, via a web browser provided through a network, a search engine UI in a first browser tab, where the search engine UI includes a search box for specifying a search query. The method includes, responsive to user input, entering keystrokes into the search box, surfacing an autocomplete menu adjacent to the search box, and populating the autocomplete menu with suggested search queries related to the entered keystrokes. The method also includes surfacing a pop-out icon corresponding to each suggested search query within the autocomplete menu and, responsive to additional user input including a selection of the pop-out icon corresponding to one of the suggested search queries, launching a second browser tab including search results for the suggested search query, where the autocomplete menu with the suggested search queries is maintained within the first browser tab after the launching of the second browser tab.

Abstract: A computing device, including a processor configured to perform data transfer scheduling for a hardware accelerator including a plurality of processing areas. Performing data transfer scheduling may include receiving a plurality of data transfer instructions that encode requests to transfer data to respective processing areas. Performing data transfer scheduling may further include identifying a plurality of transfer path conflicts between the data transfer instructions. Performing data transfer scheduling may further include sorting the data transfer instructions into a plurality of transfer instruction subsets. Within each transfer instruction subset, none of the data transfer instructions have transfer path conflicts. For each transfer instruction subset, performing data transfer scheduling may further include conveying the data transfer instructions included in that transfer instruction subset to the hardware accelerator.

Abstract: Innovations in phase quantization during speech encoding and phase reconstruction during speech decoding are described. For example, to encode a set of phase values, a speech encoder omits higher-frequency phase values and/or represents at least some of the phase values as a weighted sum of basis functions. Or, as another example, to decode a set of phase values, a speech decoder reconstructs at least some of the phase values using a weighted sum of basis functions and/or reconstructs lower-frequency phase values then uses at least some of the lower-frequency phase values to synthesize higher-frequency phase values. In many cases, the innovations improve the performance of a speech codec in low bitrate scenarios, even when encoded data is delivered over a network that suffers from insufficient bandwidth or transmission quality problems.

Abstract: An application is installed on a computing device from an application package. An origin of the application (e.g., a managed installer for an enterprise, a reputation checking service) is propagated to files written to a storage device of the computing device as part of the installation, such as by writing origin information to the storage device as metadata associated with the file. The origin information for a file, in conjunction with a policy on the computing device specifying one or more trusted origins for applications on the computing device, is used to identify whether a particular action can be taken with and/or by the file. These actions can include, for example, execution of an application from an executable file. If the origin information for a file indicates an origin that is a trusted origin specified by the policy, then the action can be performed.

Abstract: A server system is provided that includes one or more processors configured to execute a platform for an online multi-user chat service that communicates with a plurality of client devices of users of the online multi-user chat service that exchanges user chat data between the plurality of client devices. The one or more processors are configured to execute a user chat filtering program that performs filter actions for user chat data exchanged on the platform for the online multi-user chat service. The user chat filtering program includes a plurality of trained machine learning models and a filter decision service that determines a filter action to be performed for target portions of user chat data based on output of the plurality of trained machine learning models for those target portions of user chat data.

Abstract: Some implementations disclosed herein provide techniques and arrangements to enable translating language characters in media content. For example, some implementations receive a user selection of a first portion of media content. Some implementations disclosed herein may, based on the first portion, identify a second portion of the media content. The second portion of the media content may include one or more first characters of a first language. Some implementations disclosed herein may create an image that includes the second portion of the media content and may send the image to a server. Some implementations disclosed herein may receive one or more second characters of a second language corresponding to a translation of the one or more first characters of the first language from the server.

Abstract: An organic light emitting diode (OLED) display system comprises an OLED array and a power management system that includes at least one voltage generator for the OLED array. A timing microcontroller comprises a decoder/encoder configured to receive HDR pixel data and output display pixel data. A portion of the HDR pixel data is sampled and a luminance index value of the sampled portion is determined, where the luminance index value corresponds to a maximum luminance of the sampled portion. The luminance index value is used to control the at least one voltage generator to reduce power consumption of the OLED display system.

Abstract: A method for simulating a quantum-capacitance response of a material configuration comprises (a) constructing a non-interacting Hamiltonian for the material configuration based on input data; (b) computing a natural-orbitals basis for each of a plurality of parts of the material configuration under the non-interacting Hamiltonian; (c) projecting the non-interacting Hamiltonian in the natural-orbitals basis to obtain a non-interacting quantum-mechanical description for each part; (d) constructing an interacting Hamiltonian by adding an electron-interaction term to the non-interacting Hamiltonian for each of the plurality of parts; (e) for each of a plurality of representative points in a sample space of at least one tunable parameter of the material configuration, using a sums-of-Gaussians procedure to assemble a basis of Gaussian states for approximating low-energy eigenstates of the material configuration under the interacting Hamiltonian; (f) for each of a plurality of vicinities of representative points in

Abstract: According to examples, an apparatus may include a processor that may send, to a measurements manager (MM), a first measurement for the processor, cause a hardware and/or a software to send a second measurement to the MM, and cause a virtual machine (VM) to send a third measurement to the MM. The processor may also cause the MM to accumulate the first measurement, the second measurement, and the third measurement and cause the MM to output the accumulated measurements from the MM for attestation of the processor, the hardware and/or the software, the VM, or a combination thereof.

Abstract: Systems and methods for providing color recommendations for content editing applications include receiving a color recommendation request from a content editing application that includes color information pertaining to a document being edited by the content editing application. At least one color is identified based on at least one of a predefined accessibility standard, predetermined telemetry data, and organizational/group preferences with reference to the color information in the color recommendation request using a color recommendation service. A color recommendation indicating the at least one identified color is provided from the color recommendation service to the content editing application.

Abstract: A data processing system implements a receiving a textual input comprising a query for a first image. The data processing system also implements analyzing the textual input to determine a predicted color palette associated with a subject matter of the query; and procedurally generating the first image using the predicted color palette. Another implementation of the data processing system implements providing the textual input to a first machine learning model to obtain the first image, the first machine learning model being trained using a dataset comprising abstract imagery and analyzing the textual input using the first machine learning model to obtain the first image in response to receiving the textual input.

Abstract: Systems and methods relate to executing a task using a machine learning model based on prompt generation and collaborative interactions with a user. The machine language model generating a set of questions based on a task request. The user interactively answers the questions. A task processor generates a set of question-answer pairs based on the questions generated by the machine learning model and the answers given by the user. The machine learning model generates a task specific output based on the set of question-answer pairs. The machine learning model represents a large language model with deep learning. The simple question-and-answer prompts enable non-expert users to instruct the machine learning model with information that is sufficient to execute the task without overwhelming the users with the operations. The machine learning model leverages the answers to execute the task with accuracy, thereby providing efficacy of the prompting technique.

Abstract: A technique is described herein for capturing signals that indicate when any calling BOT delegates control to a called BOT, or when a calling BOT is preconfigured to contact a called BOT (e.g., as conveyed by a manifest file associated with the calling BOT). The technique can leverage these signals to facilitate the selection of BOTs. For example, the technique can use the signals to improve searches performed by a search engine and/or recommendation engine. The technique can also use the signals to generate metadata items that describe the properties of the available BOTs.

Abstract: Systems and methods for reconfiguring application windows in a display. An example method includes displaying a first application window and a second application window; receiving a drag input for moving the first application window; based on the drag input entering an invocation region, displaying a layout menu with a plurality of display layouts, each of the display layouts including one or more snap zones; receiving a hover of the first application window over a particular snap zone of a particular display layout of the plurality of display layouts; based on the hover of the first application window over the particular snap zone, displaying a zone-indicator pane corresponding to the particular snap zone; receiving a drop input of the first application window over the particular snap zone; and in response to the drop input, resizing and repositioning the first application window according the particular snap zone.

Abstract: The present disclosure provides techniques for management of user interface elements based on historical configuration data. Use of historical configuration data to render user interface elements improves usability of graphical user interfaces by maintaining a consistent user experience. The states of user interface objects in a hosting environment are retained as historical configuration data and linked to a hosting environment profile. When the same or similar hosting environment is detected, the user interface elements are rendered based on the historical configuration data. For example, the last positions of windows in a particular monitor topology are stored as historical configuration data linked to that monitor topology. The windows are returned to their previous positions when a computing device is next configured with the same or similar monitor topology.

Abstract: The present disclosure relates to systems and methods for transmitting Standard Dynamic Range (SDR) content. The systems and methods may use a modified Electro-Optical Transfer Function (EOTF) curve to convert nonlinear color values of SDR content into optical output values of modified SDR content. The systems and methods may encode the modified SDR content using eight bits while preventing banding. The systems and methods may transmit the encoded data to a client device for presentation on a display.

Abstract: A data processing system implements displaying a tabbed user interface comprising a plurality of tabs for navigating among a plurality of electronic documents; determining a first tab of the plurality of tabs is associated with a first tab group according to a first grouping criterion; and causing a first tab group control element to be displayed proximate to the first tab, the first tab group control element providing a set of tools for accessing content associated with the first tab group and for creating new tabs associated with the first tab group

Abstract: A computing apparatus of an insight interfacing system receives from a user a request for a dataset comprising a plurality of subspaces of a multi-dimensional data structure. Insights are received based on the received request then presented on a display device. Also, a chart may be presented based on the received request. The computing apparatus receives a selection of at least a portion of the presented one or more insights or a portion of the chart, then receives contextual insights based on the selected portion and presents the contextual insights on the display device.

Abstract: Systems and methods cross device application discovery and/or control. Cross device application discovery and/or control can provide for simple detection and activation of applications on remote devices. Cross device application discovery and/or control can provide for the control of remote applications in a master and slave configuration. Responsive to an activation message, an application can execute a task in an application, the task being displayed on a target device. Responsive to an activation message, an application can execute a task in an application on a target device, a task context data for the task being streamed to the source device for presentation on a display. Cross device application discovery and/or control can be enabled on a single operating system, or across a plurality of operating systems.

Abstract: A method and system for securing an anonymous discovery service may include receiving a request from a client device, the request being directed to an anonymous Autodiscover service, identifying a source from which the request originated from within the client device, and responsive to the source being of a first type of sources, transmitting a first response to the client and responsive to the source being of a second type of sources transmitting a second response to the client. The first response does not return a Uniform Resource Locator (URL) to a service endpoint, the second response returns a URL to a service endpoint. Furthermore, the anonymous discovery service may be a discovery service that requires no authentication.

Abstract: A process automatically generates configuration information used to build a target computing environment based on an image that depicts an architecture of the target computing environment. First, the process generates an original graph data structure having nodes and edges that respectively represent services and connectors detected in the image. The system then determines attributes of the target computing environment based on the original graph data structure. At least in part, the attributes describe a context in which the target computing environment is used, such as the type of industry associated with the target computing environment. The process then modifies the original graph data structure based on the attributes that have been determined, to produce a modified graph data structure. Finally, the process provides the configuration information to a deployment system, which uses the configuration information to deploy the target computing environment on a computing platform.

Abstract: A video-processing technique uses machine-trained logic to detect and track people that appear in video information. The technique then ranks the prominence of these people in the video information, to produce ranking information. The prominence of a person reflects a level of importance of the person in the video information, corresponding to the capacity of the person to draw the attention of a viewer. For instance, the prominence of the person reflects, at least in part, an extent to which the person appears in the video information. The technique performs its ranking based on person-specific feature information. The technique produces each instance of person-specific feature information by accumulating features pertaining to a particular person. One or more application systems make use of the ranking information to control the presentation of the video information.

Abstract: A system and method and for detecting meeting participant inattentiveness during an online meeting includes retrieving meeting content data from the ongoing online meeting, meeting metadata associated with the online meeting, and user data associated with participants of the online meeting, the online meeting being conducted via an online meeting application, the user data including camera data and data about user interactions with applications other than the online meeting application. Participant inattentiveness is detected, based on at least one of the camera data or the data about user interactions with the applications other than the online meeting application. Upon detecting participant inattentiveness, notification data is provided for display to the inattentive participant, receiving an indication of the participant's return to the online meeting, and providing data for displaying a summary of meeting events that occurred during the time period to the participant.

Abstract: Systems, storage media and methods for providing information for user prioritization of tasks associated with collaboratively developed content are described. Some examples may include: receiving a conversation thread associated with collaboratively developed content, the conversation thread including a plurality of comments authored by multiple different authors, generating a predicted measure of completion for the received conversation thread, the predicted measure of completion being at least one of a predicted number of remaining actions until the received conversation thread is resolved or a predicted number of total actions for the conversation thread to be resolved and providing, for display at a user interface, the predicted measure of completion for the received conversation thread, the predicted measure of completion being associated with the conversation thread at the user interface.

Abstract: An apparatus comprising: a crystal; a wire pair formed of a first wire connected so as to receive a first alternating current, and a second wire connected so as to receive a second alternating current substantially antiparallel to the first alternating current in the first wire, and located adjacent the first wire such that a localized electromagnetic filed is created in a region local to the wire pair via constructive electromagnetic interference between the first wire and the second wire in the region local to the wire pair and destructive electromagnetic field interference between the first wire and the second wire outside of the region local to the wire pair; and a colour centre located within the crystal in the region local to the wire pair.

Abstract: According to examples, an apparatus may include a processor that may, responsive to a secondary display being detected, cause a window including an option for a user to proceed with a location detection operation of the secondary display to be displayed on a primary display. The processor may also cause an icon to be displayed on the secondary display, track a movement of a cursor from the primary display to the icon displayed on the secondary display, and determine a position of the secondary display with respect to the primary display based on the tracked movement of the cursor. The processor may further store the determined position of the secondary display with respect to the primary display.

Abstract: A data processing system implements managing the deployment of updates to a cloud-based service by deploying an update to one or more components of a cloud-based service according to a deployment plan. The deployment plan defines a plurality of stages in which the update is deployed to a subset of the components associated with a different subset of users of a userbase. The system implements receiving signal data that includes information regarding the performance of the update at each stage of the deployment plan; analyzing the signal data to determine whether one or more trigger conditions of halt and recovery rules associated with the update have been satisfied; and automatically halting deployment of the update to the one or more components of the cloud-based service responsive to at least one of the trigger conditions associated with the halt and recovery rules associated with the update having been satisfied.

Abstract: Systems and methods for authoring workflows for processing data from a large-scale dataset include defining a metadata schema for the large-scale dataset, and receiving user input defining a workflow as a plurality of operations to be performed on the data. Each of the operations includes input metadata formatted according to the metadata schema. The input metadata describes input data to be processed by the operation and identifying a location for the input data in the data storage system, programmed instructions for performing an atomic operation on the input data to generate output data; and output metadata formatted according to the metadata schema. The output metadata describes the output data and identifying a location for the output data in the data storage system.

Abstract: Systems and methods are provided for dynamically balancing workloads among data flow processors based on flow characteristics of data flows. The system determines a flow characteristic score associated with the data flow based on results from deep packet inspection of data packets in the data flow. The system further determines load scores associated with a plurality of processors. A load balancer of the system selects a processor among the plurality of processors for processing the data flow based on the flow characteristic score associated with the data flow. The system monitors workload levels of respective processors by periodically receiving performance data associated with the respective processors. The performance data includes flow characteristic scores of data flows being processed. Based on the current status of the workload distribution among the plurality of processors, the system regenerates load scores and re-balancing the workloads by re-distributing data flows to the respective processors.