Abstract: According to examples, an apparatus may include a processor that may determine that an application was accessed through a portal. Based on a determination that the application was accessed through the portal, the processor may determine whether a first credential type or a second credential type was supplied to access the application, in which the first credential type may include a set of personal credentials of a user and the second credential type may include a set of single sign-on credentials that the user may use to access multiple applications. The processor may also output a trace that may indicate an identification of the application that was accessed and the type of the credential supplied to access the application, in which a backed entity may analyze the data included in the trace.

Abstract: Non-transform blocks of video content may be coded by selectively changing a scanning order. In some implementations, an encoder or decoder may perform a scanning process on a block according to a scanning order. When the block has not been transformed, the encoder or decoder may selectively change the scanning order to a different order. For example, if the block is associated with a particular type of prediction, the scanning order may be changed to a different order. In another example, if the non-transform block has a size that is smaller than a predetermined size, the scanning order may be changed to a different order.

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: Systems and methods disclosed herein are related to an intelligent UI element selection system using eye-gaze technology. In some example aspects, a UI element selection zone may be determined. The selection zone may be defined as an area surrounding a boundary of the UI element. Gaze input may be received and the gaze input may be compared with the selection zone to determine an intent of the user. The gaze input may comprise one or more gaze locations. Each gaze location may be assigned a value according to its proximity to the UI element and/or its relation to the UI element's selection zone. Each UI element may be assigned a threshold. If the aggregated value of gaze input is equal to or greater than the threshold for the UI element, then the UI element may be selected.

Abstract: A data processing system implements training a first convolutional neural network (CNN) to classify shapes in digital ink inputs, the first CNN being trained to receive ink stroke information as an input and to output an indication whether the ink stroke information represents a hand drawn geometric shape. The data processing system further implements compressing the first CNN to generate a second CNN capable of being operated on a resource-constrained computing device lacking sufficient computing resources to operate an instance of the first CNN and installing the second CNN on the resource-constrained computing device to process ink stroke information captured by a user interface of the computing device.

Abstract: A computing device is provided, including one or more processing devices, one or more temperature sensors, a fan, and a fan tachometer. The one or more processing devices may be configured to execute an application program. While executing the application program, the one or more processing devices may be further configured to collect performance data including temperature data received from the one or more temperature sensors and fan speed data received from the fan tachometer. The one or more processing devices may be further configured to generate a fan control signal at least in part by applying a machine learning model to the performance data. The one or more processing devices may be further configured to control the fan according to the fan control signal.

Abstract: This application relates to video encoding and decoding, and specifically to tools and techniques for using and providing supplemental enhancement information in bitstreams. Among other things, the detailed description presents innovations for bitstreams having supplemental enhancement information (SEI). In particular embodiments, the SEI message includes picture source data (e.g., data indicating whether the associated picture is a progressive scan picture or an interlaced scan picture and/or data indicating whether the associated picture is a duplicate picture). The SEI message can also express a confidence level of the encoder's relative confidence in the accuracy of this picture source data. A decoder can use the confidence level indication to determine whether the decoder should separately identify the picture as progressive or interlaced and/or a duplicate picture or honor the picture source scanning information in the SEI as it is.

Abstract: A display assembly includes a display layer with a plurality of display elements to provide display light and form a display image. A first subset of display elements is used while the display assembly is operating in a full visibility mode, and a second subset of display elements is used while the display assembly is operating in a restricted visibility mode. A touch-sensitive layer includes a plurality of conductive traces disposed proximate to the display layer. The plurality of conductive traces are shaped and positioned to block a first portion of the display light while the display assembly is operating in the full visibility mode, and block a second, greater portion of the display light while the display assembly is operating in the restricted visibility mode. A visibility controller is used to switch the display assembly between the full visibility mode and the restricted visibility mode.

Abstract: Apparatus and methods for training a neural network accelerator using quantized precision data formats are disclosed, and in particular for storing activation values from a neural network in a compressed format having lossy or non-uniform mantissas for use during forward and backward propagation training of the neural network. In certain examples of the disclosed technology, a computing system includes processors, memory, and a compressor in communication with the memory. The computing system is configured to perform forward propagation for a layer of a neural network to produced first activation values in a first block floating-point format. In some examples, activation values generated by forward propagation are converted by the compressor to a second block floating-point format having a non-uniform and/or lossy mantissa. The compressed activation values are stored in the memory, where they can be retrieved for use during back propagation.

Abstract: The description relates to enhancing computer performance, such as by decreasing latency associated with storage operations. One example can include recoverable processes. Each recoverable process can be configured to periodically write log records to individual storage partitions. Each log record includes a vector timestamp that describes the processes' dependencies on log records of other recoverable processes.

Abstract: Embodiments of the system in include a method of clustering data sets based on the data set characteristics. A data repository stores a plurality of heterogeneous data sets. For a selected group of data sets (i) obtaining metadata; (ii) identifying upstream data sets; and (iii) extracting semantic features. The method further comprises clustering the plurality of data sets into one or more clusters based on similarity, wherein the similarity is determined based on a combination of the metadata, the upstream data sets, and the semantic features of the selected data sets. In one embodiment, the data sets are ranked within each cluster based on data set quality. The method enables the presenting of at least one cluster including one or more ranked data sets in response to a search query.

Abstract: Methods and systems for detecting systemwide service issues by using anomaly localization. In an example, a method includes receiving time-series monitoring data for multiple services, the time-series monitoring data including multiple dimensions and an error metric; for the monitoring data from each service, evaluating scopes within the monitoring data based on an objective function for a time-series of the error metric to identify at least one anomalous scope, each scope including at least one dimension and a value for the dimension; based on evaluating the scopes, generating a ranked list of scopes for each service based on objective function scores for the scopes; correlating the ranked lists of scopes across the multiple services to identify a cross-service anomaly; and generating an alert for the services based on the cross-service anomaly, the alert indicating at least one scope as a potential root cause for the cross-service anomaly.

Abstract: Systems and methods are provided for handing off execution of an application from a local computing device to a cloud-based computing device. The disclosed technology is directed to determining whether and when to initiate handing off the execution of the application based on monitoring resource consumption of the local computing device. When the application is not previously installed on the cloud-based computing device, the local computing device transmits an application installer executable to the cloud-based computing device for enabling use of the same application on the cloud-based computing device.

Abstract: Systems and methods for deploying dependent updates include mechanisms for requiring that dependency information be provided for each update so that dependent updates may be identified. Update dependencies are tracked so that dependent updates are not deployed until parent updates have been completed. Deployment sequencing is implemented on top of existing asynchronous deployment policies so that asynchronous workflow remains intact and unaltered. The asynchronous workflow is upgraded to a synchronous (i.e., sequential) workflow for updates having dependencies to ensure that updates having dependencies are applied in the correct order.

Abstract: A liquid-submersible thermal management system includes a cylindrical outer shell and an inner shell positioned in an interior volume of the outer shell. The cylindrical outer shell has a longitudinal axis oriented vertically relative to a direction of gravity, and the inner shell defines an immersion chamber. The liquid-submersible thermal management system a spine positioned inside the immersion chamber and oriented at least partially in a direction of the longitudinal axis with a heat-generating component located in the immersion chamber. A working fluid is positioned in the immersion chamber and at least partially surrounding the heat-generating component. The working fluid receives heat from the heat-generating component.

Abstract: Systems and methods for clustering metrics for reducing a search space of metrics used for service health analyses. Determining a root cause of an event includes performing an automated analysis of metrics associated with the service. To diagnose and resolve events quickly and efficiently, aspects correlate and cluster a plurality of metrics for a specific service based on historical data, where each cluster represents a root cause direction. After clustering metrics by similarity, metrics are scored and ranked to select representative metrics from each cluster, which reduces the dimensionality of the search space. The representative metrics may provide a saliant representation of each metrics cluster. The representative metrics are provided to a service health analyzer, which performs a root cause analysis of the representative metrics to diagnose and mitigate the event.

Abstract: Biosensing measurements (e.g., heart rate, pupil size, cognitive load, stress level, etc.) are communicated in the context of events that occurred concurrently with the biosensing measurements. The biosensing measurements and the contextual events can be presented in real-time or as historical summaries. Such presentations allow users to easily gain useful insights into which specific events triggered which specific physiological responses in users. Therefore, the present concepts more effectively communicate insights that can be used to change user behavior, modify workflow, design improved products or services, enhance user satisfaction and wellbeing, increase productivity and revenue, and eliminate negative impacts on user's emotions and mental state.

Abstract: A method of operating a computing device in support of improved accessibility includes displaying a user interface to an application on a display screen of the computing device, wherein the computing device includes an accessibility assistant that reads an audible description of an element of the user interface; initiating, on the computing device, a virtual assistant that conducts an audible conversation between a user and the virtual assistant through at least a microphone and a speaker associated with the computing device, wherein the virtual assistant is not integrated with an operating system of the computing device; inhibiting an ability of the accessibility assistant to read the audible description of the element of the user interface; and upon transition of the virtual assistant from an active state, enabling the ability of the accessibility assistant.

Abstract: Innovations in the area of prediction of block vector (“By”) values improve encoding or decoding of blocks using intra block copy (“BC”) prediction. For example, some of the innovations relate to use of a default BV predictor with a non-zero value. Other innovations relate to use of a selected one of multiple BV predictor candidates for a current block. Still other innovations relate to use of a skip mode in which a current intra-BC-predicted block uses a predicted BV value.

Abstract: A system for generating a user interface described herein can include a processor to detect a type of the system based on hardware components residing within the system or coupled to the system and determine a user interface manager to execute based on the type of the system. The processor can also execute the user interface manager to generate a user interface for the system, wherein the type of the user interface manager comprises a plurality of rules to indicate a layout of the user interface.

Abstract: A method for automatically improving the legibility of text within graphic designs is implemented via a computing system including a processor. The method includes executing a graphics application and causing surfacing of a graphic design GUI on a display. The method includes generating a templatized image including text responsive to the user-initiated insertion of a desired image into a design template surfaced via the graphic design GUI. The method also includes assigning a legibility score to the text within the templatized image and, responsive to a determination that the legibility score is less than a predetermined threshold, generating a bounding box around the text area. The method further includes generating an improved templatized image with improved text legibility by selectively blurring the image portion that falls within the bounding box, as well as causing surfacing of the second templatized image via the graphic design GUI.

Abstract: A method for computer question answering includes, at a retriever subsystem of a question answering computer system, identifying a plurality of relevant text evidence strings for an input text question. At a linker subsystem of the question answering computer system, one or more of the plurality of relevant text evidence strings are associated with a respective secondary text evidence string to form a plurality of evidence chains via a previously-trained entity-linking machine-learning model. At a chainer subsystem of the question answering computer system, a ranked set of the evidence chains is identified based at least in part on an output of a generative machine-learning model applied to each of the plurality of evidence chains. At a reader subsystem of the question answering computer system, an answer to the input text question is output based at least in part on the ranked set of evidence chains.

Abstract: This document relates to automated generation of machine learning models, such as neural networks. One example method involves obtaining a first machine learning model having one or more first inference operations. The example method also involves identifying a plurality of second inference operations that are supported by an inference hardware architecture. The example method also involves generating second machine learning models by modifying the first machine learning model to include individual second inference operations that are supported by the inference hardware architecture. The example method also involves selecting a final machine learning model from the second machine learning models based on one or more metrics.

Abstract: A data processing system implements receiving a far-end signal associated with a first computing device participating in an online communication session and receiving a near-end signal associated with a second computing device participating in the online communication session. The near-end signal includes speech of a target speaker, a first interfering speaker, and an echo signal. The system further implements providing the far-end signal, the near-end signal, and an indication of the target speaker as an input to a machine learning model. The machine learning model trained to analyze the far-end signal and the near-end signal to perform personalized noise suppression (PNS) to remove speech from one or more interfering speakers and acoustic echo cancellation (AEC) to remove echoes. The model is trained to output an audio signal comprising speech of the target speaker. The system obtains the audio signal comprising the speech of the target speaker from the model.

Abstract: A query-processing technique includes an operation of matching the input query against a plurality of candidate target items, to produce a set of candidate query-item pairings. The matching is applicable to different classes of matching, but is performed by a computer processing architecture that uses a class-agnostic instance of query-processing logic and a class-agnostic target item index. After the matching operation, the technique assigns a matching class to each candidate query-item pairing in the set of candidate query-item pairings, to produce a set of classified pairings. The technique ultimately serves a particular output item to an end user, where the particular output item is chosen based on the results of the matching and assigning. Some implementations of the technique include a filtering operation whereby the candidate-item pairings are filtered to conform to a specified selection strategy or strategies. This filtering operation supplements or replaces the assigning operation.

Abstract: A hardware retire circuit includes: one or more input queues, each queue corresponding to an input stream of tasks and being configured to store input task identifiers corresponding to tasks of the input stream; and processing logic configured to: receive a completed task event; determine whether a completed task queue identifier and a completed task identifier of the completed task event match an input task identifier of an input task at a head of an input queue having an input queue identifier corresponding to the completed task queue identifier; and in response to determining a match, pop the task at the head of the input queue and output a task retirement event corresponding to the input task.

Abstract: A computing device configured to removably attach a component comprises a housing comprising first and second device electromagnets. A wireless charging transmitting antenna is between the electromagnets. Instructions are executable by a processor to synchronize a first device current through the first device electromagnet with a first component current through a first component electromagnet of the component to attract the electromagnets, and to synchronize a second device current through the second device electromagnet with a second component current through a second component electromagnet of the component to attract the electromagnets.

Abstract: Systems and methods for protecting privacy-relevant data from unauthorized disclosure in source code of an application. For instance, the present disclosure provides a plurality of technical features including: a privacy-relevant data analyzer that analyzes source code, detects privacy-relevant data in the source code, and generates a report of instances of detected privacy-relevant data. In some examples, the privacy-relevant data analyzer scans through source code to detect annotations that denote if fields, records, or combinations thereof include privacy-relevant data. The privacy-relevant data analyzer further generates and provides a report of detected privacy issues associated with sensitive data included in source code so that the issues can be resolved to ensure that privacy is not breached.

Abstract: A data processing system implements receiving an access request from the client device of a content requestor to access a content item for which access to the content item is managed by a content access management platform and obtaining access control information. The access control information comprising information associated with a content owner associated with the content item, information associated with the content requestor, and information associated with the content item.

Abstract: Examples are disclosed that relate to applying haptic output to a touch-sensitive input device. One example provides a touch-sensitive input device comprising a body, a haptic feedback mechanism within the body, a sensor subsystem, a logic processor, and a memory. The memory stores instructions executable by the processor to receive from the sensor subsystem sensor data indicating locations along the body of a plurality of contact points between a user hand and the body, based at least in part on the sensor data, determine a touch profile of the user hand applied to the body, based at least in part on the touch profile of the user hand, determine a selected haptic output to be applied to the body, and cause a drive signal to be transmitted to the haptic feedback mechanism to apply the selected haptic output to the body.

Abstract: Systems and methods for generating a shared collaborative channel for collaboration are provided. In particular, a computing device may receive a request, from an originating member of an organization, to create the shared collaborative channel, the request including an invitee to be added to the shared collaborative channel. In response to receipt of the request, the computing device may provision a substrate group by creating a container associate with the shared collaborative channel including a substrate database associated with the shared collaborative channel, generate an invitation including a custom link to the shared collaborative channel for the invitee, and determine whether the invitee belongs to an originating collaboration team associated with the originating member based on the substrate database. If the invitee belongs to the originating collaboration team, the computing device may further update the substrate group to add the invitee as a new member of the shared collaborative channel.

Abstract: Examples are disclosed that relate to generating expressive avatars using multi-modal three-dimensional face modeling and tracking. One example includes a computer system comprising a processor coupled to a storage system that stores instructions. Upon execution by the processor, the instructions cause the processor to receive initialization data describing an initial state of a facial model. The instructions further cause the processor to receive a plurality of multi-modal data signals. The instructions further cause the processor to perform a fitting process using the initialization data and the plurality of multi-modal data signals. The instructions further cause the processor to determine a set of parameters based on the fitting process, wherein the determined set of parameters describes an updated state of the facial model.

Abstract: This document relates to training and employing a quality estimation model. One example includes a method or technique that can be performed on a computing device. The method or technique can include providing degraded audio signals to one or more packet loss concealment models, and obtaining enhanced audio signals output by the one or more packet loss concealment models. The method or technique can also include obtaining quality labels for the enhanced audio signals and training a quality estimation model to estimate audio signal quality based at least on the enhanced audio signals and the quality labels.

Abstract: Indirect time-of-flight camera systems for operating in multiple optical channels using active modulated light and accompanying methods of operation are provided. In one aspect, the indirect time-of-flight camera system includes first and second modulatable laser sources outputting light of different wavelengths for illuminating a target environment. The camera system further includes a wavelength-selective reflective element designed to reflect the light of a first wavelength and to transmit the light of a second wavelength. The camera system further includes a controller comprising instructions executable to control the camera system to, in a first time period, activate the first modulatable laser source and deactivate the second modulatable laser source, and in a second time period, deactivate the first modulatable laser source and activate the second modulatable laser source.

Abstract: A computing system includes a logic subsystem and a storage subsystem holding instructions executable by the logic subsystem to implement a transformer-based text encoder. The transformer-based text encoder includes a plurality of transformer blocks previously-trained to apply encoding operations to computer-readable text representations of input text strings, the computer-readable text representations including computer-readable question representations of input text questions, and computer-readable passage representations of input text passages. The plurality of transformer blocks include a shared transformer block trained for both the computer-readable question representations and the computer-readable passage representations and a specialized transformer block including two or more input-specific subnetworks, and a routing function to select an input-specific subnetwork of the two or more input-specific subnetworks for each of the computer-readable text representations.

Abstract: A foldable computing device comprises a first frame rotatably coupled to a second frame. The second frame comprises a push-to-open mechanism comprising an actuator and a power switch located for actuation by the actuator. A detection mechanism detects a displaced position of the actuator that corresponds to releasing the foldable computing device from a closed configuration. Actuation of the power switch is detected and used with detection of the displaced position of the actuator to control an operating state of the computing device.

Abstract: The description relates to accelerator architectures for deep learning models. One example can obtain a deep learning training script associated with a deep learning model and extract an operator graph from the training script. The example can split the operator graph into first and second portions of a heterogeneous pipeline and tune a first accelerator core for the first portion of the heterogeneous pipeline and a second accelerator core for the second portion of the heterogeneous pipeline. The example can also generate a hardware architecture that includes the first accelerator core and the second accelerator core arranged to collectively accomplish the deep learning model.

Abstract: The description relates to resource aware object detection for encoded video streams that can identify frames of the video stream that include an object of interest, such as a human, without decoding the frames.

Abstract: Methods and systems cause display of email messages of a user on a screen of a computing system based on scores associated with the email messages. An email ranking system may have assigned the scores to the email messages. The scores are based on actions that other recipients of the email messages have taken with respect to the email messages. In calculating the scores, the actions of the other recipients may receive different weights based on how closely connected a recipient is to the user and a type of connection the recipient has to the user. A network graph may indicate how closely connected the recipient is to the user and the type of connection the recipient has to the user.

Abstract: Examples are disclosed that relate to fairly ordering financial market trades received from different market participant computers via a cloud computing network. In one example, a plurality of trades generated by a plurality of market participant computers are received. The trades are generated based at least on a financial market data point received by the plurality of market participant computers. Each trade is tagged with a delivery clock time stamp that tracks time in relation to financial market events that occur at a corresponding market participant computer. The trades are ordered based on the delivery clock time stamps and sent to a central exchange server computer. The central exchange server computer processes the trades.

Abstract: A general methodology is presented for optimizing a value at risk (VaR) associated with an allocation of objects (i.e., a strategy) having variable performance and loss characteristics. For purposes of illustration, investment strategies prescribing a portfolio of items from a set of candidates with unknown and generally correlated joint losses are discussed. The framework is based on approximating the VaR using nonparametric estimates of the portfolio loss density and, using mathematical insights, an efficient approach to computing the VaR gradient with respect to the strategy. The approach also allows inclusion of constraints on the strategy (e.g. a maximum fraction per item) and allows the VaR optimization problem to be solved using optimization techniques such as sequential quadratic programming.

Abstract: This document relates to performing live video stream analytics on edge devices. One example determines resources available to the system, and a video analytics configuration is selected that distributes work between edge devices and cloud devices in a cascading manner, where edge device processing is prioritized over cloud processing in order to conserve resources. This example can dynamically modify the allocation of processing depending on changing conditions, such as network availability.

Abstract: A document re-finding system generates embeddings for concept clips provided by a user, the concept clips defining a concept for searching for content of interest to the user in a plurality of documents previously seen by the user. The re-finding system determines semantic relationships between the concept and document clips, related to respective document among the plurality of documents, based on the concept embedding and embeddings generated for the document clips. A graphical user interface depicting the semantic relationships is rendered to the user and is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.

Abstract: A computing system including a quantum computing device and a classical computing device. The computing system computes an estimated unitary matrix over a plurality of iterations that each include, at a processor, computing a current-iteration exponent, a current-iteration error parameter, and a conjugate transpose of a current-iteration estimate of the unitary matrix. Each iteration further includes transmitting the current-iteration exponent, the current-iteration error parameter, and the conjugate transpose to the quantum computing device. At the quantum computing device, each iteration further includes computing a process tomography result and outputting the process tomography result to the classical computing device. At the processor, each iteration further includes computing a distance measure between the current-iteration estimate and the process tomography result, and, when the distance measure is below a predefined constant, updating the current-iteration estimate.

Abstract: A method of and system for automatically generating an ink note object is carried out by detecting receipt of a digital ink input on a user interface (UI) screen, the UI screen being displayed by an application and being associated with at least one of a document, a page or an event. Once digital ink input is detected, the digital ink input is captured. Additionally, contextual data associated with the digital ink input is collected, the contextual data being related to at least one of the document, the page, the event, and a user providing the digital ink input. An ink note object is then generated and stored for the digital ink input, the ink note object including the captured digital ink input and the contextual data, and the ink note object being an entity that is separate from the document, the page and the even.

Abstract: A touch-screen display device comprises a series of column electrodes and a series of row electrodes, with an electronic display layer arranged behind the series of column electrodes and behind the series of row electrodes. The series of row electrodes crosses the series of column electrodes such that the electrical impedance at each crossing of a row and column electrode is responsive to the proximity of a touch input to that crossing. A row-drive circuit is configured to apply an excitation signal to a selected row electrode and to concurrently apply a compensation signal to one or more other row electrodes, the compensation signal being out of phase with respect to the excitation signal. A column-sense circuit is configured to sense a column signal from the series of column electrodes and to provide a corresponding column output.

Abstract: Systems, methods, and computer-readable storage devices are disclosed for simulated choral audio chatter in communication systems. One method including: receiving audio data from each of a plurality of users participating in a first group of a plurality of groups for an event using a communication system; generating first simulated choral audio chatter based on the audio data received from each of the plurality of users in the first group; and providing the generated first simulated choral audio data to at least one user of a plurality of users of the event.

Abstract: Systems and methods for identifying and evicting idle sessions include training a machine learning model as a session classifying model to learn rules for classifying active sessions between clients and the cloud-based service. The session classifying model is trained to receive a plurality of parameters pertaining to the document associated with an active session as input and to apply the rules to the plurality of parameters to determine a classification for the active session and to provide an output indicative of the classification for the active session. The session classifying model is then utilized in the cloud-based service to classify the active sessions. The active sessions classified as idle sessions may then be evicted from the cloud-based service.

Abstract: Systems and methods directed to generating a predicted quality metric are provided. Telemetry data may be received from a from a first group of devices executing first software. A quality metric for the first software may be generated based on the first telemetry data. Telemetry data from a second group of devices may be received, where the second group of devices is different from the first group of devices. Covariates impacting the quality metric based on features included in the first telemetry data and the second telemetry data may be identified, and a coarsened exact matching process may be performed utilizing the identified covariates to generate a predicted quality metric for the first software based on the second group of devices.

Abstract: In some examples, matrix based bot implementation may include obtaining, for a plurality of bots that are used to respond to a query, a matrix that includes entries including a plurality of scenarios, a plurality of questions corresponding to the plurality of scenarios, and a plurality of responses. Each response may correspond to a specified question. A plurality of scripts may be generated based on an analysis of the matrix. Each script may include at least one question followed by at least one response, and further followed by at least one scenario. For each script, a closest pre-existing script may be identified based on a comparison of the script to pre-existing scripts. For each script, a modification to the matrix may be generated based on a difference in the script from the closest pre-existing script. The bots may be utilized to respond to the query based on the modified matrix.