Abstract: An Artificial Intelligence (AI) based automatic damage detection and estimation system receives images of a damaged object. The images are converted into monochrome versions if needed and analyzed by an ensemble machine learning (ML) cause prediction model that includes a plurality of sub-models that are each trained to identify a cause of damage to a corresponding portion for the damaged object from a plurality of causes. In addition, an explanation for the selection of the cause from the plurality of causes is also provided. The explanation includes image portions and pixels of images that enabled the cause prediction model to select the cause of damage. An ML parts identification model is also employed to identify and labels parts of the damaged object which are repairable and parts that are damaged and need replacement. The cost estimation for the repair and restoration of the damaged object can also be generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for assisting an agent in providing support to a customer. The methods, systems, and apparatus include actions of obtaining interaction information regarding an interaction between a customer and an agent, identifying the customer from the interaction information, aggregating the information regarding the customer from multiple sources, determining an intent of the customer from the interaction information and the aggregated information, determining a sentiment of a customer from the interaction information and the aggregated information, determining a particular action to indicate to the agent based on the aggregated information, the intent, and the sentiment, and generating an interface to provide the agent based at least on the particular action.

Abstract: A system may receive a cluster prediction requirement. The system may determine a first node conglomerate by sorting a first dataset into a first plurality of nodes. The system may determine a plurality of attributes by sorting a second dataset associated with the cluster prediction requirement. The system may determine a second node conglomerate for each of the plurality of attributes. A node confidence score may be assigned to each of the second plurality of nodes. The system may determine a node graph based on a comparison between the first node conglomerate and the second node conglomerate. The node graph may be iteratively modified based on a node optimization threshold value to generate a harmonized node graph. The node optimization threshold value may be based on a map confidence score allotted to the node graph.

Abstract: This document describes morphing objects that are created using hydrogels and techniques for creating and controlling the morphing objects. In one aspect, a method for creating a morphing object includes creating one or more heating elements on a substrate by applying one or more conductive traces onto at least one of a first surface of the substrate or a second surface of the substrate opposite the first surface and forming a hydrogel pattern on the first surface of the substrate by applying a hydrogel ink to the first surface of the substrate based on a predefined pattern.

Abstract: In some examples, migration context and flow graph based migration control may include ascertaining an application that is to be migrated from a physical environment to a cloud environment, and determining a migration issue associated with the migration of the application. Migration context and flow graph based migration control may further include identifying, from a historical issue database, a plurality of historical issues, determining, for the migration issue and the plurality of historical issues, unified proximities, sorting, based on the determined unified proximities, the historical issues, selecting, from the sorted historical issues, a topmost historical issue, and determining, from the topmost historical issue, a resolution associated with the topmost historical issue.

Abstract: Systems and methods for facilitating validation of datasets are disclosed. A system may include a processor. The system may include a data validator implemented via the processor to receive an input dataset including a component metadata. The data validator may perform, using an validation model and through a rules engine, validation of information in the component metadata to obtain a validation dataset. The validation may enable to predict at least one invalid feature in the component dataset. The system may include an insight generator implemented via the processor to generate, based on the validation datasets, automated insights pertaining to mitigation of the at least one invalid feature. In an embodiment, the automated insights may be stored in a distributed ledger to facilitate an authenticated storage of the automated insights. The authenticated storage may be facilitated by a network comprising a plurality of nodes.

Abstract: Systems and methods for generating an output representation are disclosed. A system may include a processor including a representation generator. The representation generator may receive an input data comprising an input content and an instruction. The representation generator may include a parsing engine to parse the input data to obtain parsed information. The representation generator include a mapping engine to map the parsed information with a pre-stored base template pertaining to a pre-defined module, to obtain a mapped template. The representation generator may generate, through a machine learning (ML) model, based on the mapped template, an output representation in a pre-defined format. The output representation may correspond to the expected representation of the input content.

Abstract: In some examples, dark web content analysis and identification may include ascertaining data that includes text and images, and analyzing the data by performing deep learning based text and image processing to extract text embedded in the images, and deep embedded clustering to generate clusters. Clusters that are to be monitored may be ascertained from the generated clusters. A determination may be made as to whether the ascertained data is sufficient for classification. If so, a deep convolutional generative adversarial networks (DCGAN) based detector may be utilized to analyze further data with respect to the ascertained clusters, and alternatively, a convolutional neural network (CNN) based detector may be utilized to analyze the further data with respect to the ascertained clusters. Based on the analysis of the further data, an operation associated with a website related to the further data may be controlled.

Abstract: A system and method of determining whether specific clauses in a contract have a likelihood of falling under a particular risk category is disclosed. The proposed systems and methods describe an autonomous digital assistant that accepts contract-related queries from end-users and generates conversational responses. For example, an end-user may request information about the contract's terms, and the system can automatically provide intelligent analytical responses that bypass the need to manually evaluate the various features of the document.

Abstract: Implementations are directed to a smart filter apparatus including an air filter, a sensor supported by the air filter and sensitive to a pathogen, and a control unit in data communication with the sensor and operable to perform operations including receiving, from the sensor, an indication of the pathogen present in air incident on the sensor, generating, by the control unit, a pathogen alert response, and providing, by the control unit, the pathogen alert response.

Abstract: In some examples, artificial intelligence based project implementation may include implementing, for a project team, self-evaluation of viability for utilizing a project implementation framework. The project team may be guided on utilization of the project implementation framework. A discussion by the project team may be documented in a digital format during envisioning associated with the project implementation framework, and documented information may be maintained for reference during execution, by the project team, of a journey associated with the project implementation framework. During execution of the journey, implementation of a social contract by the project team may be evaluated. A determination may be made as to whether the social contract is not implemented for at least one specified occurrence associated with the project implementation framework, and at least one impediment associated with the project implementation framework may be identified.

Abstract: Implementations of the present disclosure include receiving, from an agile security platform, attack graph (AG) data representative of one or more AGs, each AG representing one or more lateral paths within an enterprise network for reaching a target asset from one or more assets within the enterprise network, processing, by a security platform, data from one or more data sources to selectively generate at least one event, the at least one event representing a potential security risk within the enterprise network, and selectively generating, within the security platform, an alert representing the at least one event, the alert being associated with a priority within a set of alerts, the priority being is based on the AG data.

Abstract: An utterance recommendation system may obtain a plurality of utterance influencing attributes influencing a response recommended for a user query from a plurality of sources. The system may collate the utterance influencing attributes to provide enriched user data and may identify a set of preconfigured potential utterance options associated with the user query. The system may implement a plurality of utterance recommendation techniques to analyze the enriched user data based on associated predefined rules, and provide a preferential rank ordering of the preconfigured potential utterance options to be recommended based on the analysis. The system may determine a single optimized rank ordering of the preconfigured potential utterance options representing a ranking order of the preconfigured potential utterance options. The system may provide the response to the user query, based on a potential utterance option ranked highest in the single optimized rank ordering.

Abstract: Methods, systems, and apparatus for solving cost optimization problems. In one aspect, a method includes receiving data representing a bill of materials (BOM) optimization problem, the BOM optimization problem comprising a task of determining a BOM recommendation that satisfies one or more constraints, wherein each constraint comprises one or more constraint variables and a constraint constant; generating, based on the data representing the BOM optimization problem, a quadratic unconstrained binary optimization (QUBO) formulation, wherein the QUBO formulation comprises i) for each constraint variable in the one or more constraints, a binary representation of the constraint variable and ii) a first parameter that depends on a difference between a respective constraint constant and the binary representations of the constraint variables; and obtaining data representing a solution to the BOM optimization problem from a quantum computing resource.

Abstract: In some examples, extended reality based immersive project workspace creation may include obtaining sensing data from at least one sensor of a device worn by a user, and analyzing, based on the sensing data, an environment of the user. A plurality of insights associated with the user may be determined, and prioritized based on a plurality of prioritization criteria. An insight of the plurality of prioritized insights associated with the user may be rendered in the environment of the user. Further, the rendering of the insight may be controlled based on an interaction of the user with the rendered insight.

Abstract: Implementations include receiving an AAG that at least partially defines a digital twin of an enterprise network and includes rule nodes each representing an attack tactic that can be used to move along a path, determining security controls each mitigating at least one rule node, executing an iteration of a simulation of a sub-set of security controls in the enterprise network, the iteration including: for each security control in the set of security controls, determining, an influence score that represents a change in a security risk from implementing the security control and a rule distribution, defining the sub-set of security controls based on the first influence scores, and reducing the AAG based on the sub-set of security controls to provide a residual AAG, determining a decrease in a graph risk value and the first AAG, and selectively implementing the sub-set of security controls in the enterprise network.

Abstract: A system and method for facilitating digital rationalization of a correspondence is disclosed. The system may include a processor including DTRE. The DTRE may receive a plurality of templates from at least one database coupled to the processor. The plurality of templates may pertain to a given correspondence. The DTRE may process the plurality of templates to identify static objects and dynamic objects. The static objects may be indicative of components that may be common across the plurality of templates. The dynamic objects may be indicative of components that may vary across the plurality of templates. The DTRE may generate, at least one rationalized template based on analysis of the identified static and dynamic objects. The at least one rationalized template may optimally represent the given correspondence, and may enable transmission of the given correspondence having content pertaining to any of the plurality of templates.

Abstract: In some examples, collaborative learning-based cloud migration implementation may include identifying a migration agent that is to perform an application migration from a first cloud environment to a second cloud environment, and identifying a plurality of additional migration agents. A technical context and a migration flow context may be determined for the migration agent and for the plurality of additional migration agents. Executed allowed and error-response migration actions may be identified for states that are similar to a current state of the application migration, and a similarity between the migration agent and each of the migration agents that executed the allowed and error-response migration actions may be determined. A migration action that is to be performed may be identified based on a maximum relevance associated with the allowed and error-response migration actions. The identified migration action may be executed by the migration agent to perform the application migration.

Abstract: A device may receive application data identifying an application to be executed by a hybrid cloud computing environment and constraint data identifying constraints associated with the hybrid cloud computing environment. The device may select objectives based on the application data and the constraint data, and may identify factors associated with the objectives. The device may correlate the factors with potential data centers, and may apply weights to the correlated factors to generate correlated factor scores. The device may identify a list of data centers based on the correlated factor scores, and may determine a reduced list of data centers. The device may apply a preference technique to the reduced list of data centers to generate a ranked list of data centers, and may determine the hybrid cloud computing environment based on the ranked list of data centers. The device may perform actions based on the hybrid cloud computing environment.

Abstract: Implementations are directed to methods for providing an enhanced encounter via a holographic virtual assistant, including detecting, by one or more processors, an encounter request from a user, selecting a first encounter including a first holographic representation and a first dialog output, providing the first encounter for presentation to the user on the holographic virtual assistant, receiving, from the user, a first user reaction, the first user reaction including a first user dialog input and a first user engagement input, and training, using the first user reaction, a conversational goal model.