Abstract: A method of tracking an entity includes generating data relevant to the entity at a first location, storing the data at a server, and accessing at least a portion of the data at the first location or at a second location. The data can include location information, time information, image data, text, and/or biometric data. The data can be encrypted, organized, categorized, updated, accumulated with other data, classified, and/or disseminated, and an automated search can include an image feature recognition and facial recognition search. The entity can be a person, an animal, or an object. A communications system includes a processing device and a server that includes an automated search engine. The server can be configured to perform data analysis, such as data grouping.

Abstract: Data characterizing a prompt and/or a parameter set can be received. Data characterizing an enhanced prompt can be generated. The enhanced prompt can be stored in a template. When a change in ta type of the artificial intelligence based model, a setting of the artificial intelligence based model, or a configuration for an enterprise in which the artificial intelligence based model is deployed, is determined to be above a threshold, the enhanced prompt can be modified. The modified enhanced prompt can be provided to one or more applications interfacing with the artificial intelligence model, or derivative of the template. Related apparatus, systems, techniques, and articles are also described.

Abstract: A method of tracking an entity includes generating data relevant to the entity at a first location, storing the data at a server, and accessing at least a portion of the data at the first location or at a second location. The data can include location information, time information, image data, text, and/or biometric data. The data can be encrypted, organized, categorized, updated, accumulated with other data, classified, and/or disseminated, and an automated search can include an image feature recognition and facial recognition search. The entity can be a person, an animal, or an object. A communications system includes a processing device and a server that includes an automated search engine. The server can be configured to perform data analysis, such as data grouping.

Abstract: A method includes receiving data characterizing a first output of one or more of a first set of models associated with a first organization, the first set of models trained on a first dataset using a first set of resourcing levels; training one or more of a second set of models associated with a second organization based on a second dataset using a second set of resourcing levels, global constraints and the first output, wherein the second set of resourcing levels specifying a second condition on outputs of the one or more of the second set of models; assessing, based on a second output of the one or more of the second set of models, performance of the one or more of second set of models; and retraining the first set of models or a subset thereof. Related apparatus, systems, articles, and techniques are also described.

Abstract: Data is received characterizing an impact function, a first plurality of inputs to the impact function, and a plurality of weights associated with the first plurality of inputs. A first coefficient characterizing an interaction between a first input and a second input of the plurality of inputs is calculated based on a first set of weights of the plurality of weights. The first set of weights are indicative of interaction between the first input and the second input. A graphical object including a plurality of regions is displayed in a graphical user interface (GUI). A first region and a second region of the plurality of regions are indicative of the first input and the second input, respectively. A second graphical object connecting the first region to the second region is displayed in the GUI. Related apparatus, systems, techniques and articles are also described.

Abstract: Data characterizing a query can be received. A dataset specific to an enterprise and a parameter set specific to the enterprise can be determined using an information model. A query response using a foundational model, the dataset specific to the enterprise, and the parameter set specific to the enterprise can be determined. The query response can be provided to a user. Related apparatus, systems, techniques, and articles are also described.

Abstract: A method of tracking an entity includes generating data relevant to the entity at a first location, storing the data at a server, and accessing at least a portion of the data at the first location or at a second location. The data can include location information, time information, image data, text, and/or biometric data. The data can be encrypted, organized, categorized, updated, accumulated with other data, classified, and/or disseminated, and an automated search can include an image feature recognition and facial recognition search. The entity can be a person, an animal, or an object. A communications system includes a processing device and a server that includes an automated search engine. The server can be configured to perform data analysis, such as data grouping.

Abstract: Data is received characterizing an impact function, a first plurality of inputs to the impact function, and a plurality of weights associated with the first plurality of inputs. A first coefficient characterizing an interaction between a first input and a second input of the plurality of inputs is calculated based on a first set of weights of the plurality of weights. The first set of weights are indicative of interaction between the first input and the second input. A graphical object including a plurality of regions is displayed in a graphical user interface (GUI). A first region and a second region of the plurality of regions are indicative of the first input and the second input, respectively. A second graphical object connecting the first region to the second region is displayed in the GUI. Related apparatus, systems, techniques and articles are also described.

Abstract: A first node having a first location in the first GUI and indicative of a first analytical task is provided in a first graphical user interface (GUI). A multi-step analytical process includes the first analytical task. Data is received characterizing a first user input indicative of selection of the first node. A first set of nodes is displayed in the first GUI. The first set of nodes are adjacent to the first node and are associated with a next step of the multi-step analytical process. The multi-step analytical process includes at least one of importing a dataset, building a model using the dataset, and/or deploying the model to operate on live data. Related apparatus, systems, techniques and articles are also described.

Abstract: A first node having a first location in the first GUI and indicative of a first analytical task is provided in a first graphical user interface (GUI). A multi-step analytical process includes the first analytical task. Data is received characterizing a first user input indicative of selection of the first node. A first set of nodes is displayed in the first GUI. The first set of nodes are adjacent to the first node and are associated with a next step of the multi-step analytical process. The multi-step analytical process includes at least one of importing a dataset, building a model using the dataset, and/or deploying the model to operate on live data. Related apparatus, systems, techniques and articles are also described.

Abstract: Data is received characterizing an impact function, a first plurality of inputs to the impact function, and a plurality of weights associated with the first plurality of inputs. A first coefficient characterizing an interaction between a first input and a second input of the plurality of inputs is calculated based on a first set of weights of the plurality of weights. The first set of weights are indicative of interaction between the first input and the second input. A graphical object including a plurality of regions is displayed in a graphical user interface (GUI). A first region and a second region of the plurality of regions are indicative of the first input and the second input, respectively. A second graphical object connecting the first region to the second region is displayed in the GUI. Related apparatus, systems, techniques and articles are also described.

Abstract: A first set of nodes indicative of a multi-step analytical process including a plurality of analytical tasks is provided in a first graphical user interface (GUI). A first node of the first set of nodes is indicative of a first analytical task of the multi-step analytical process. A spatial arrangement of the first set of nodes in the GUI is indicative of a temporal order associated with the plurality of analytical tasks in the multi-step analytical process. Data characterizing a first input from a first user indicative of a request for assistance with the first analytical task is received. A second user with a second GUI including the spatial arrangement of the first set of nodes is provided. Data characterizing a second input indicative of interaction of a second user with the first analytical task via the first node is received. Related apparatus, systems, techniques and articles are also described.

Abstract: A first node having a first location in the first GUI and indicative of a first analytical task is provided in a first graphical user interface (GUI). A multi-step analytical process includes the first analytical task. Data is received characterizing a first user input indicative of selection of the first node. A first set of nodes is displayed in the first GUI. The first set of nodes are adjacent to the first node and are associated with a next step of the multi-step analytical process. The multi-step analytical process includes at least one of importing a dataset, building a model using the dataset, and/or deploying the model to operate on live data. Related apparatus, systems, techniques and articles are also described.

Abstract: An approach for determining a veracity of a reported event is provided. In an embodiment, a set of predictor variables is retrieved from a selected use case. Each of these predictor values is a condition that indicates the veracity of the reported event. In addition, a set of hidden predictor variables is generated from a set of unstructured documents related to the reported event using a hidden Markov model that is based on the predictor variables using a cognitive system. These hidden predictor variables are combined with the set of predictor variables to generate a set of updated predictor variables. These updated predictor variables are used by the cognitive system to return a determination of the veracity of the reported event.

Abstract: A method of tracking an entity includes generating data relevant to the entity at a first location, storing the data at a server, and accessing at least a portion of the data at the first location or at a second location. The data can include location information, time information, image data, text, and/or biometric data. The data can be encrypted, organized, categorized, updated, accumulated with other data, classified, and/or disseminated, and an automated search can include an image feature recognition and facial recognition search. The entity can be a person, an animal, or an object. A communications system includes a processing device and a server that includes an automated search engine. The server can be configured to perform data analysis, such as data grouping.

Abstract: A method includes receiving data characterizing a first output of one or more of a first set of models associated with a first organization, the first set of models trained on a first dataset using a first set of resourcing levels; training one or more of a second set of models associated with a second organization based on a second dataset using a second set of resourcing levels, global constraints and the first output, wherein the second set of resourcing levels specifying a second condition on outputs of the one or more of the second set of models; assessing, based on a second output of the one or more of the second set of models, performance of the one or more of second set of models; and retraining the first set of models or a subset thereof. Related apparatus, systems, articles, and techniques are also described.

Abstract: Methods and systems for datacenter migrations are disclosed. A method includes: virtualizing, by a computing device, servers in a source environment; installing, by the computing device, an isolation firewall to isolate a target environment from the source environment; installing, by the computing device, shared services in the target environment; installing, by the computing device, monitoring and management tools in the virtualized servers in the source environment; replicating, by the computing device, between the source environment and the target environment; and cutting over, by the computing device, from the source environment to the target environment by switching a route advertisement from the source datacenter to the target datacenter.

Abstract: An approach is provided that selects a geographic location to which transmission of a data packet is disallowed. The approach identifies disallowed network devices that reside in the selected geographic location and builds a routing path through a public computer network through an allowed set of network devices with the allowed set of network devices not including any of the disallowed network devices. The approach then transmits the data packet from a transmitting network device to a receiving network device using the routing path.

Abstract: A method includes receiving input specifying a first selection of a first value of a variable of a dataset, the variable including a set of values associated with a model including a set of submodels, the set of submodels including a first submodel, the first value associated with the first submodel; determining a first routing rule specifying use of the first submodel associated with the selected first value when the model receives the selected first value as input; and deploying the model with the first routing rule. Related apparatus, systems, techniques and articles are also described.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: obtaining radio signal encoded data from one or more radio signal emitting device disposed on one or more fabric item used for thermal insulation by a user; performing data processing using an obtained environmental temperature of the user and one or more thermal characteristic, wherein the one or more thermal characteristic is determined using the radio signal encoded data; and providing one or more output based on the data processing.