Abstract: A system for communicating with eye wear. The system may include smart glass pairing instructions that are configured to establish a radio frequency (“RF”) communication link between a terminal and the eye wear. The system may include image proximity instructions that are configured to estimate a distance from the eye wear to the terminal. The system may include overlay instructions that are configured to overlay an eye wear display on a view of the terminal through the eye wear. The system may include response instructions configured to receive from a user a response to the eye wear display. The system may include synchronization instructions configured to: define a virtual integrated UI that corresponds to the terminal and the eye wear display; and record a state of the virtual integrated UI.

Abstract: Systems, computer program products, and methods are described herein for detection and recordation of functional code logic components on a distributed development platform. The present invention is configured to retrieve, from a source code repository, a source code script, wherein the source code script is associated with a first source; initiate a machine learning model on the source code script; determine, using the machine learning model, at least one functional code logic component from the source code script; initiate an NFT source code mapping engine on the at least one functional code logic component; generate, using the NFT source code mapping engine, a NFT for the at least one functional code logic component, wherein the NFT comprises the at least one functional code logic component and information associated with the first source; and record the NFT in a distributed ledger.

Abstract: A system for auto-generating and sharing customized virtual environments comprises a processor associated with a server. The processor detects an avatar associated with a user device interacting with virtual environment objects in a virtual environment for an interaction with an entity. The processor generates user data objects associated with the interaction and a user profile. The processor extracts user behavior objects and user device objects from the user data objects. The processor applies a machine learning model to map the user behavior objects and the user device objects to the virtual environment objects. The processor integrates the user behavior objects and the user device objects with the virtual environment objects into a set of interaction objects based on the mapping. The processor determines customized environment virtual objects based on the interaction objects.

Abstract: An apparatus comprises a memory communicatively coupled to a processor. The memory may be configured to store data exchange requests. The processor may be configured to determine that a data exchange request of the data exchange requests comprises a status indicating that the data exchange request is incomplete, generate a priority value for the data exchange request indicating a batch priority associated with the data exchange request, and assign a weight for the data exchange request indicating that the data exchange request is expected to be completed in one or more batch orders. Further, the processor is configured to generate a batch order comprising a position in a queue corresponding to the batch priority and complete the data exchange request in the decentralized network in accordance with the position in the batch order.

Abstract: A user may print a smart card on-demand by leveraging an Extended Reality (XR) interface to enter card specifications and supply them to a card issuer as an encrypted payload. The card issuer may send the user a non-fungible token (NFT) with instructions for rendering and 3D printing the card using the user's XR interface. The printed card may have an interior layer that includes a pattern of micro electromechanical sensor (MEMS) tactile sensors that uniquely identify the card. The sensors may be placed in selected locations based on a predefined grid pattern of potential sensor locations. The 3D printer may add a non-programmed smart chip to the card. The 3D printer may be a user's printer, or may be a 3D printer at an automated teller machine (ATM). An ATM may be configured to validate and activate the card after detecting the MEMS pattern and programming the smart chip.

Abstract: A solid cleansing product including at least a first surfactant and a second surfactant present in a combined surfactant weight amount; at least a first buffering agent and a second buffering agent a present in a combined buffering agent weight amount; and magnesium sulfate; where the combined buffering agent weight amount is greater than the combined surfactant weight amount.

Abstract: An apparatus comprises a memory communicatively coupled to a processor. The memory may be configured to store user profiles, security information, and multiple updated tokens. The processor may be configured to identify a first updated token and a second token that are associated with user profiles in a user group; determine a first entitlement associated with a first user profile; and determine a second entitlement associated with a second user profile. Further, the processor may be configured to generate an initial token indicating that the user group is entitled to access the first entitlement and the second entitlement; transmit the initial token to a decentralized network; and receive a third updated token from the decentralized network indicating a firewall configuration that a first user device and a second user device use to implement a firewall at the first user device and at the second user device.

Abstract: Various principles and methods are described herein to improve wireless communication in a user computing device. Certain aspects of the disclosure describe management of wireless transmissions relative to various regulations related to a specific absorption rate. Other aspects of the disclosure relate to detection of user proximity to a transmitting antenna. Other aspects relate to alternative strategies to improve wireless communication, such as selection of alternate antennas or baseband modems, or changes in device orientation.

Abstract: In some examples, a first user device receives, from a second user device, a provisioning reference and an access token, the provisioning reference and the access token obtained by the second user device as part of a provisioning procedure performed by the second user device with a server. The first user device accesses the server using the provisioning reference and the access token to provision the first user device. The first user device receives, from the server, a network profile in response to the access token. The first user device connects to a network using the network profile.

Abstract: Aspects of the disclosure relate to a dynamic caching platform. The dynamic caching platform may train a machine learning model based on historical complexity score information. The dynamic caching platform may receive information streams from a client metaverse device and a metaverse host system. The dynamic caching platform may generate a complexity score based on the interaction information streams using the machine learning model. The dynamic caching platform may compare the complexity score to complexity thresholds. Based on the comparison, the dynamic caching platform may identify caching rules. The dynamic caching platform may cache interaction information based on the caching rules. The dynamic caching platform may update the complexity score using the machine learning model. The dynamic caching platform may update the caching rules based on the updated complexity score. The dynamic caching platform may cache interaction information based on the updated caching rules.

Abstract: Methods, apparatus, and system to summarize an audio-visual media with a neural network machine learning architecture.

Abstract: A system includes a memory, and a processor. The processor receives a request to register a device. In response, the processor extracts a set of parameters from the device, and stores a baseline record associated with the device, which includes the set of parameters, in the memory. The processor determines that an update to the device modified the set of parameters. In response, the processor extracts the modified set of parameters from the device, and stores a new record associated with the device, which includes the modified set of parameters, in the memory. The baseline record was used to validate an identity of the device prior to the processor determining that the update modified the set of parameters. The new record is used to validate the identity of the device subsequent to the processor determining that the update modified the set of parameters.

Abstract: Aspects of the disclosure relate to computing hardware and software for IoT event processing. A computing platform may monitor communication between an initiating IoT device and a service provider IoT device to detect an event processing request. The computing platform may extract, from the event processing request, event features. The computing platform may feed the event features into a deep learning engine, which may produce a smart contract corresponding to the event processing request. The computing platform may identify, using a distributed ledger, whether the event features comply with the smart contract. Based on identifying that the event features do comply with the smart contract, the computing platform may send, to an event processing system, authorization to process the event processing request, which may cause the event processing system to transfer funds from an initiating user to the service provider.

Abstract: Systems, computer program products, and methods are described herein for implementing an enhanced authentication framework using Erasable Programmable Read-Only Memory (EPROM) grid pattern recognition.

Abstract: Systems, computer program products, and methods are described herein for detection and recordation of functional code logic components on a distributed development platform. The present invention is configured to retrieve, from a source code repository, a source code script, wherein the source code script is associated with a first user; initiate a machine learning model on the source code script; determine, using the machine learning model, at least one functional code logic component from the source code script; initiate an NFT source code mapping engine on the at least one functional code logic component; generate, using the NFT source code mapping engine, a NFT for the at least one functional code logic component, wherein the NFT comprises the at least one functional code logic component and information associated with the first user; and record the NFT in a distributed ledger.

Abstract: An apparatus for activating a physical card in a virtual environment comprises a processor associated with a server. The processor is configured to receive a request to issue a physical card to a first user and to generate a first non-fungible token (NFT) for storage in the physical card, wherein the first NFT is then displayed as a digital card in a virtual environment. The processor is further configured to receive the digital card in an interaction and to generate a second NFT. The processor is further configured to combine the first NFT and the second NFT to generate an activation NFT that allows the physical card to access a profile corresponding to the first user during an interaction. The processor is further configured to transmit the activation NFT and an instruction to the first user device to store the activation NFT in the physical card.

Abstract: An architecture is disclosed for submission and recordation of application programmer interfaces (APIs) using non-fungible tokens (NFTs) inserted into a blockchain. The API-NFT pairings are validated by nodes of the network. The system automatically searches for and generate NFTs for APIs and/or intermediate layers on a computer network based on metadata associated with the API and a hash of the API/intermediate layer. The API-NFT pair binding ensures that developers/consumers are ingesting APIs that are secure and do not include malicious rules. Furthermore, performance monitoring of the API is performed using artificial intelligence (AI) and machine learning (ML), including long short term memory (LSTM) neural networks.

Abstract: An architecture is disclosed for submission and recordation of application programmer interfaces (APIs) using non-fungible tokens (NFTs) inserted into a blockchain. The API-NFT pairings are validated by nodes of the network. The system automatically searches for and generate NFTs for APIs and/or intermediate layers on a computer network based on metadata associated with the API and a hash of the API/intermediate layer. The API-NFT pair binding ensures that developers/consumers are ingesting APIs that are secure and do not include malicious rules. Furthermore, performance monitoring of the API is performed using artificial intelligence (AI) and machine learning (ML), including long short term memory (LSTM) neural networks.

Abstract: An architecture is disclosed for submission and recordation of application programmer interfaces (APIs) using non-fungible tokens (NFTs) inserted into a blockchain. The API-NFT pairings are validated by nodes of the network. The system automatically searches for and generate NFTs for APIs and/or intermediate layers on a computer network based on metadata associated with the API and a hash of the API/intermediate layer. The API-NFT pair binding ensures that developers/consumers are ingesting APIs that are secure and do not include malicious rules. Furthermore, performance monitoring of the API is performed using artificial intelligence (AI) and machine learning (ML), including long short term memory (LSTM) neural networks.

Abstract: A solid cleansing product including at least a first surfactant and a second surfactant present in a combined surfactant weight amount, both of the first and second surfactants being free of sulfate-containing materials; at least a first buffering agent and a second buffering agent a present in a combined buffering agent weight amount; where the combined buffering agent weight amount is at least double the combined surfactant weight amount.