Abstract: Methods, systems, and computer-readable storage media for determining for each query in a set of high-cost queries, an access pattern to data objects accessed by the query in a legacy system, determining for each query in a set of low-cost queries, an access pattern to each data object accessed by the query in the legacy system, providing a first set of design patterns representative of first data objects of the legacy system to be offloaded to the target system and a second set of design patterns representative of second data objects of the legacy system to remain on the legacy system, and executing at least one design pattern of the first set of design patterns to offload one or more first data objects to the target system.

Abstract: Call preparation engine for customer relationship management (“CRM”) is presented. Example embodiments of the present invention include invoking an intelligence assistant to retrieve lead details, customer information, and insights for use during a call between a tele-agent and a customer; administering tele-agent call preparation notes for use during the call between the tele-agent and the customer; and displaying, through a call preparation cockpit, the lead details, customer information, insights and tele-agent call preparation notes.

Abstract: Methods, systems, and apparatus for implementing a hexadecimal to quantum computation translation. In one aspect, a method includes obtaining one or more hexadecimal data inputs; applying a quantum computation translation operation to each hexadecimal data input to generate one or more corresponding sequences of quantum computations; implementing the one or more sequences of quantum computations using quantum computing hardware to obtain one or more corresponding sequence of measurement results; and providing the one or more sequences of measurement results as respective representations of the one or more hexadecimal data inputs.

Abstract: Implementations of the present disclosure include receiving a color image and an IR image, the IR image taken contemporaneously with the color image, providing a set of facial landmarks depicted in the color image, determining a depth value for each facial landmark in the set of color landmarks, depth values being provided from the IR image, determining an average depth difference based on at least a sub-set of facial landmarks in the set of facial landmarks, comparing the average depth difference to a difference threshold to provide a comparison, and selectively authenticating the person based on the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.

Abstract: Implementations of the present disclosure include executing, within a computer network, multiple instances of a process, each instance including a simulation of execution of the process within the computer network, receiving session datasets representative of sessions performed during execution of each instance of the process, generating a set of session traces, each session trace representing a sequence of sessions performed during an instance of the process within the computer network, processing the set of session traces using a clustering algorithm to cluster sessions of each session trace into two or more clusters, each cluster having an associated label, and providing a process model that generically represents multiple executions of the process within the computer network, the process model comprising a sequence of labels of the two or more clusters corresponding to session traces in the set of session traces.

Abstract: Implementations include providing a first set of tags by processing a document using generic entity extraction based on one or more external taxonomies, providing a second set of tags by processing the electronic document using specific entity extraction based on internal taxonomies specific to the enterprise, determining a relevance score for each tag in the first set of tags, and the second set of tags, defining a set of tags including one or more tags of the first set of tags, and one or more tags of the second set of tags, tags of the set of tags being in rank order based on respective relevance scores, receiving user input to the set of tags, and performing one or more of adjusting a ranking of tags based on the user input, and editing at least one internal taxonomy of the one or more internal taxonomies based on the user feedback.

Abstract: Automated computing machinery agnostically augmenting a CRM application, including an agent hub that associates an identity of a tele-agent and an indication whether the tele-agent is logged on to the agent hub; the agent hub operatively coupled to a browser, the browser bearing a browser extension through which a sales template for a sales campaign to which the tele-agent is assigned to work is operatively exposed as a GUI overlay of the browser, the overlay overlaid upon a web page of the CRM application; a leadership hub that associates the tele-agent and the sales campaign to which the tele-agent is assigned, the leadership hub operatively coupled to the agent hub; and a campaign management portal that associates the sales campaign and the display template, the display template associating a question and an answer form, the campaign management portal operatively coupled for data communications to the agent hub.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: Embodiments of the present invention include a dynamic script engine for tele-agents including a statistics engine configured to receive, during a sales call, real-time industry trend data from one or more remote industry resources; create a current industry score in dependence upon the industry trend data and current products available to a customer on an active call; and transmit the current industry score to a script generator; and a script generator configured to receive the current industry score from the statistics engine and dynamically reorder in real-time and in dependence upon the industry score one or more sentences of a dynamic script to be read by a sales agent to the customer during the sales call.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for test cycle optimization using contextual association mapping. In one aspect, a method includes obtaining an artifact that includes a collection of reference items, where each reference item includes a sequence of words, generating candidate tags from each of the reference items based on the sequences of words in the reference items, selecting a subset of the candidate tags as context tags based on an amount that the candidate tags appear in the reference items, obtaining a sample item that includes a sequence of words, identifying a subset of the context tags in the sequence of words in the sample item, and classifying a subset of the reference items as contextually similar to the sample item based the context tags that were identified.

Abstract: A device may generate a synthetic knowledge graph based on a true knowledge graph, may partition the synthetic knowledge graph into a set of synthetic data partitions, and may determine, using a plurality of teacher models, an aggregated prediction. The aggregated prediction may be based on individual predictions from corresponding individual teacher models included in the plurality of teacher models. The device may determine, using a student model and based on the synthetic knowledge graph and noise, a student prediction. The student model may be trained based on historical synthetic knowledge graphs and historical aggregated predictions associated with the plurality of teacher models. The device may determine an error metric based on the aggregated prediction and the student prediction, and may perform an action associated with the synthetic knowledge graph based on the error metric.

Abstract: Implementations directed to providing a computer-implemented system for providing a logistic demand forecasting comprising receiving a plurality of electronic receipts, each electronic receipt comprising a plurality of logistic data elements, parsing the electronic receipts to aggregate the logistic data elements, processing the aggregated logistic data elements through a logistics demand forecasting analytics model, the logistics demand forecasting analytics model having been trained using a set of training data describing historic and actual demand within a logistic supply chain, determining a logistic demand forecasting based on the processing, the logistic demand forecasting indicating an upcoming demand for transportation assets within the logistic supply chain, and providing the logistic demand forecasting to an automated warehouse system servicing the logistic supply chain.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for initiating actions based on sequences of events. In one aspect, a process includes receiving, from each of multiple devices, data specifying an event detected by the device. The events are compared to configured scenarios that each specify a sequence of trigger events and an action to be initiated in response to detecting the sequence of trigger events. A determination is made that the events match a first scenario of the scenarios. In response to determining that the events detected by the multiple devices match the first scenario, a first action specified by the first scenario is initiated. A determination is made that a combination of one or more of the events detected by the multiple devices and the first action matches a second scenario. In response, a second action specified by the second scenario is initiated.

Abstract: Customer relationship management (“CRM”) implemented in a computer system, including parsing a word, from call notes of a conversation between a tele-agent of a call center and a customer representative, into a parsed triple of a description logic; determining whether the parsed triple is recorded in a semantic CRM triple store of the computer system; if the parsed triple is not recorded in the semantic CRM triple store, recording the parsed triple as a call note in the semantic CRM triple store.

Abstract: A device may generate, from a subset of historical ontology data and a substance description of a substance, a knowledge base. The subset of historical ontology data may be associated with historical substances. The device may generate, based on the knowledge base, a substance knowledge graph embedding (KGE) that is representative of the substance; compare the substance KGE and a historical KGE associated with the knowledge base; determine, based on comparing the substance KGE and the historical KGE, a similarity score associated with the substance KGE and the historical KGE; determine, based on the similarity score, whether substance data associated with a related substance is similarly represented in the substance KGE and the historical KGE; and perform, based on whether the substance data is similarly represented in the substance KGE and the historical KGE, an action associated with the related substance relative to the substance description or the knowledge base.

Abstract: In some implementations, a device may receive, from a camera of a source device, video data depicting a physical environment. The device may detect a target indicator associated with a target zone of the physical environment. The device may determine, based on the target indicator, a zone configuration of the target zone relative to the target indicator. The device may generate, based on a position of the source device, an initial masking content that is associated with a boundary of the target zone that is defined by the zone configuration using a spatial mapping model based on the video data and the target indicator. The device may generate a final masking content using chroma keying based on the initial masking content. The device may generate display data associated with the final masking content and the video data. The device may provide the display data to a destination device.

Abstract: The present disclosure provides a clustering device configured to detect varying density. The clustering device may receive a set of parameters (e.g., a density parameter specifying a plurality of density values, a size parameter, and a node parameter that includes information associated with a plurality of nodes) for identifying clusters. The clustering device may determine a distance between different pairs of nodes of the plurality of nodes and identify candidate nodes of the plurality of nodes based on the distance determined for the different pairs of nodes and the size parameter. Candidate nodes may be assigned to a candidate cluster that may be evaluated against the density parameter to determine whether a density of the candidate cluster satisfies at least one of the plurality of density values. A cluster may be identified based on whether the candidate cluster satisfies at least one of the plurality of density values.

Abstract: A device receives a machine learning model, model data associated with the machine learning model, and identifier generation data. The identifier generation data includes data utilized to generate identifier pairs that may be used to authenticate the machine learning model. The device selects an identifier model, for generating the identifier pairs, based on the machine learning model, the model data, and the identifier generation data. The device processes the machine learning model, the model data, and the identifier generation data, with the selected identifier model, to generate the identifier pairs and identifier pair data. The device stores the identifier pairs and the identifier pair data in one or more data structures, and utilizes the identifier pairs to identify and provide authentication for the machine learning model.

Abstract: A device may receive user personalized data and user activity data identifying tasks and actions performed by a user, and may perform natural language processing on the user personalized data and the user activity data to generate processed textual data. The device may train machine learning models based on the processed textual data to generate trained machine learning models, and may receive, from a client device, a command identifying a particular task to be performed. The device may process the command and the user activity data, with the trained machine learning models, to determine whether a particular action in the user activity data correlates with the particular task. The device may perform actions when the particular action correlates with the particular task.