Abstract: A system for generating an expandable pool of virtual agents to provide solutions in a virtual environment comprises a call center server in communication with a metaverse server. The call center server generates the virtual agents with corresponding skills of each real-world agent using a machine learning model based on historical observation operations performed by each particular real-world agent and a historical rule set to address the service issue. The metaverse server identifies the virtual agents in the virtual environment. The call center server routes a service inquiry with a service issue from a user equipment of a user to the metaverse server. The metaverse server identifies a first virtual agent with a first skill and conducts a first interaction between the first virtual agent and a user avatar to generate the customized solution to address the service issue.

Abstract: Arrangements for machine learning-based dynamic learning are provided. In some examples, audio data associated with a plurality of calls may be received and analyzed to identify a topic and sub-topic of each call and metadata of each call. Feedback data may also be received. A machine learning model may be executed by inputting, to the model, the identified topic and sub-topic and metadata of each call, and the feedback data, to output one or more topics or sub-topics of concern. A plurality of ongoing calls may be monitored to identify an ongoing call related to one of: a topic or sub-topic of concern. A plurality of agents who are not subject matter experts in the identified topic or sub-topic of concern and are available may be identified and joined, via respective computing devices, to the ongoing call in a dynamic learning session.

Abstract: Arrangements for intelligent call routing are provided. Audio data from a call between an agent device and a user device may be received and a topic of the call and metadata may be extracted from the audio data. The extracted topic and metadata may be compared to an alert signals database to output whether an alert will be attached to the call. Agent parameters associated with the agent who is part of the call may be identified. A machine learning model may be executed by inputting, to the model, the extracted topic, extracted metadata, the output of whether the alert will be attached to the call, and the agent parameters, to output a routing signal. Based on the routing signal, a second call communication session may be initiated between the agent computing device and a computing device of at least one of another agent or a supervisor.

Abstract: A method includes monitoring an interaction of a user with a metaverse session. A notification is sent to a first developer that the user is facing an issue while interacting with the metaverse session. The first developer is allowed access to the metaverse session at a location of the issue using a first developer avatar. One or more error flags are generated within a field of view of the first developer avatar in the metaverse session. Each error flag includes a respective error code. In response to determining that a first error code of a first error flag matches a first stored error code, a first solution is determined. The first solution includes a first stored solution corresponding to the first stored error code. In response to determining that the first solution solves the issue of the user, the first solution is deployed to the metaverse session.

Abstract: A system for generating an expandable pool of virtual agents to provide solutions in a virtual environment comprises a call center server in communication with a metaverse server. The call center server generates the virtual agents with corresponding skills of each real-world agent using a machine learning model based on historical observation operations performed by each particular real-world agent and a historical rule set to address the service issue. The metaverse server identifies the virtual agents in the virtual environment. The call center server routes a service inquiry with a service issue from a user equipment of a user to the metaverse server when determining that a particular real-world agent is not available. The metaverse server identifies a first virtual agent with a first skill and conducts a first interaction between the first virtual agent and a user avatar to generate the customized solution to address the service issue.

Abstract: Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.

Abstract: In one embodiment, an apparatus comprises a log circuit to: identify an input associated with a logarithm operation, wherein the logarithm operation is to be performed by the log circuit using piecewise linear approximation; identify a first range that the input falls within, wherein the first range is identified from a plurality of ranges associated with a plurality of piecewise linear approximation (PLA) equations for the logarithm operation, and wherein the first range corresponds to a first equation of the plurality of PLA equations; compute a result of the first equation based on a plurality of operands associated with the first equation; and return an output associated with the logarithm operation, wherein the output is generated based at least in part on the result of the first equation.

Abstract: Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.

Abstract: Systems and methods are disclosed for real time, frictionless channel switching to map and transpose a transaction on a preferred channel from an incoming channel. The systems and methods may use a machine learning model that processes features from a plurality of channels to determine the preferred channel. An omni channel processor is used to determine intended functionality data of the transaction for the preferred channel. The systems and methods may generate transposed intent data based on the intended functionality data of the transaction for the preferred channel. A deep link is generated and embedded with the transposed intent data and a channel access token for the transaction on the preferred channel. The deep link is configured to access and complete the requested transaction on the preferred channel.

Abstract: Systems, computer program products, and methods are described herein for determining optimal resource transfer routing using quantum gateway optimization.

Abstract: A method includes rendering, on displays of an extended reality (XR) device, an XR environment, and detecting, based on sensor data obtained from sensors of the XR device, a device capability associated with the XR device and one or more environmental conditions associated with the XR environment. The method further includes receiving a request corresponding to one or more user interactions with an XR application. In response to receiving the request, the method includes generating, based the device capability and the environmental conditions, a dynamic digital profile to be associated with the user, in which the dynamic digital profile is dynamically generated to be responsive to one or more input modalities associated with the request, and render, on the displays, the dynamic digital profile. The rendered dynamic digital profile includes a set of elements responsive to the one or more input modalities of the request.

Abstract: An apparatus and method for cleaning or etching a molybdenum film or a molybdenum nitride film from an interior of a reaction chamber in a reaction system are disclosed. A remote plasma unit is utilized to activate a halide precursor mixed with an inert gas source to form a radical gas. The radical gas reacts with the molybdenum film or the molybdenum nitride film to form a by-product that is removed from the interior of the reaction chamber by a purge gas.

Abstract: The present disclosure relates generally to systems, methods, instructions, and other aspects describing automated transcription and associated script generation. In one aspect, a method includes facilitating a voice bot segment of a two-way communication session, where the voice bot segment is between a customer device and a non-human bot agent, and transfer of the session to a human agent device as part of a human voice segment of the two-way communication session, wherein the transfer occurs following a failure of the non-human bot agent to resolve a customer issue. Accessing survey data describing the two-way communication session, wherein the survey data is associated with successful resolution of the customer issue and automatically processing transcript data from the two-way communication with the survey data to identify language data from the transcript associated with resolution of the customer issue. The non-human bot agent is then dynamically updated using the language data.

Abstract: A computing platform may detect a live interaction between an agent and a customer. The computing platform may input information of the live interaction into a first machine learning model and a second machine learning model to produce a first solution deviation score and a first emotional deviation score, respectively. The computing platform may compare the first solution deviation score to a solution deviation threshold and the first emotional deviation score to an emotional deviation threshold. Based on detecting that one or more of the solution deviation threshold or the emotional deviation threshold are met or exceeded, the computing platform may initiate one or more corrective actions. The computing platform may update, based on the first solution deviation score and the first emotional deviation score, the first machine learning model and the second machine learning model.

Abstract: In one embodiment, an apparatus comprises a log circuit to: identify an input associated with a logarithm operation, wherein the logarithm operation is to be performed by the log circuit using piecewise linear approximation; identify a first range that the input falls within, wherein the first range is identified from a plurality of ranges associated with a plurality of piecewise linear approximation (PLA) equations for the logarithm operation, and wherein the first range corresponds to a first equation of the plurality of PLA equations; compute a result of the first equation based on a plurality of operands associated with the first equation; and return an output associated with the logarithm operation, wherein the output is generated based at least in part on the result of the first equation.

Abstract: A method includes receiving a request. The request is encrypted to generate an encrypted request. The encrypted request includes a version information for a first software package deployed in a standalone computing system, and a region information and a hardware information for the standalone computing system. The encrypted request is sent to a respective regional data center of a cloud computing system based on the region information of the first software package. A second software package is identified among software packages stored in the respective regional data center. The second software package corresponds to the hardware information of the first software package. The version information of the first software package is compared to a version information of the second software package. In response to identifying that the second software package is more recent than the first software package, the second software package is deployed to the standalone computing system.

Abstract: A system identifies data objects from a first piece of code in an original programming language and creates a knowledge graph that represents a relationship among the data objects. The system identifies a particular data object that is unique to the original programming language. The system determines a counterpart data object that is used for a particular purpose as the identified data object in a target programming language. The system creates a second piece of code in the target programming language by replacing the particular data object with the counterpart data object. The system determines if the second piece of code is configured to perform a task that the first piece of code is programmed to perform. In response to determining that the second piece of code is configured to perform the particular task, the system executes the second piece of code.

Abstract: An apparatus and method for cleaning or etching a molybdenum film or a molybdenum nitride film from an interior of a reaction chamber in a reaction system are disclosed. A remote plasma unit is utilized to activate a halide precursor mixed with an inert gas source to form a radical gas. The radical gas reacts with the molybdenum film or the molybdenum nitride film to form a by-product that is removed from the interior of the reaction chamber by a purge gas.

Abstract: A system identifies data objects from a first piece of code in an original programming language and creates a knowledge graph that represents a relationship among the data objects. The system identifies an expression syntax in the first piece of code and determines an interpretation of the expression syntax. The system creates a sentence that indicates an interpretation of a respective code line. The system determines a counterpart data object in a target programming language for each word in the created sentence. In response, the system creates a second piece of code in the target programming language, such that the second price of code satisfies syntax rules in the target programming language. In response to determining that the second piece of code is configured to perform a particular task that the first piece of code is configured to, the system executes the second piece of code.

Abstract: Methods are provided for an artificial intelligence (“AI”) agent answering a call within a voice AI container. The methods may include the AI agent receiving the call from a human caller within the voice AI container, the call may include a query. The methods may include parsing the query to identify context associated with the query. The methods may include identifying using the context an intent of the query. The methods may include determining whether a first valid mapping stored within a backend database, located in the voice AI container, is associated with the intent of the query. The methods may include loading the first valid mapping. The methods may include navigating an agent screen using the loaded valid mapping. The methods may include gathering information required to satisfy the intent of the query. The methods may include relaying the information to the human caller.