Abstract: Systems, computer program products, and methods are described herein for configuring network architecture using advanced computational models for data analysis and automated processing. The present disclosure is configured to receive a service request, wherein the service request comprises configuring a node to complete the service request; determine a protocol based on the service request, wherein the protocol comprises evaluating the service request using application servers; determine the node to be used in a network configuration, wherein the node is determined in response to decision compute requirements; arrange, using an artificial intelligence (AI) model, the node into the network configuration, wherein the AI model optimizes the network configuration based on the decision compute requirements and one or more network parameters; and monitor the network configuration using a configuration monitor, wherein the configuration monitor analyzes the one or more network parameters.

Abstract: Arrangements for leveraging quantum computing to optimize cash recycling at ATMs are provided. Current status data including location data, cash depletion rate data, and the like, may be received from a plurality of ATMs. Telemetry data from one or more cash replenishment vehicles may be received. The telemetry data may include GPS-based location data from a computing device associated with each vehicle, speed data, and the like. A machine learning model may be executed using the ATM status data and telemetry data as inputs to output an optimized replenishment scenario. In some examples, quantum computing may be used to analyze the data and identify the optimized replenishment scenario for execution. Executing the optimized replenishment scenario may include generating one or more instructions that causing one or more ATMs to activate or deactivate cash recycling functionality, causing one or more cash replenishment vehicles to modify a replenishment route, or the like.

Abstract: A decentralized swarm intelligence algorithm over a network of paired ATMs to prevent or control surface attacks on ATMs. The ATMs may be seeded with an initial swarm intelligence model to identify suspicious activity. An ATM may relay alerts about suspicious activity at that ATM to other paired ATMs. The ATMs use machine learning to update the model and perform swarm intelligence autonomously at the paired ATMs. A bank may provide the initial swarm intelligence model, receive alerts about and analyze the attacks, and provide updated swarm intelligence models to prevent or limit future attacks. Smart contracts may be used to specify rules for performing swarm intelligence using the paired ATMs. Records regarding swarm intelligence models, attempted suspicious attacks including payment instruments that may have been used, actions taken in response to the attacks, and smart contracts may be recorded on a blockchain distributed ledger.

Abstract: Systems and processes are disclosed for processing and integrating multinational data into data lakes. Utilizing a generative AI engine, data schema templates can be dynamically generated to standardize diverse data streams from various sources. The systems and processes incorporate edge computing for localized preprocessing, ensuring data quality and compliance with international regulations. Innovative features include real-time data routing and prioritization algorithms for efficient hyper-ingestion, and an embedded livestream for instantaneous business decision-making. The disclosed cutting-edge approaches address the complexities of modern data integration challenges.

Abstract: An apparatus comprises a memory communicatively coupled to a processor. The processor is configured to determine a configuration mapping corresponding to a deployment operation and create a secret parameter based at least in part upon the configuration mapping, receive a request to release multiple testing operations to a managed server, identify a source of the request, and determine that the request is received from a trusted device in response to determining that the source at least partially matches a server profile of the one or more server profiles. Further, the processor is configured to determine multiple pods associated with the managed server in response to determining that the request is received from the trusted device, generate a verification block based at least in part upon the secret parameter and the configuration mapping, and enable access between the pods and the portion of application data.

Abstract: An apparatus comprises a memory communicatively coupled to a processor. The memory is configured to store multiple deployment operations configured to control access to one or more portions of application data. The processor is configured to determine a deployment operation associated with a portion of the application data, perform multiple collected testing operations for the portion of the application data based at least in part upon the deployment operation, and determine pod data indicating multiple role parameters based at least in part upon the deployment operation. The role parameters are configured to indicate multiple testing operations on the portion of the application data. Further, the processor is configured to identify a pod that at least partially matches the pod data and trigger one or more distributed testing operations at the pod.

Abstract: A method for establishing an alternative transaction gateway when a default transaction network is down leveraging a network of low-orbit satellites is provided. The method may include creating, using an internet of things (“IoT”) device, a non-fungible token (“NFT”) associated with a transaction executed at the IoT device. The method may include storing the NFT at the IoT device pending proximity to a low-orbit satellite. The method may further include transmitting the NFT to a first low-orbit satellite when the first low-orbit satellite is within a first pre-determined proximity to the IoT device. The method may include, in response to receiving the NFT at the first low-orbit satellite, running a smart contract to identify an optimal pathway for transporting the NFT. The pathway may include the first low-orbit satellite and one or more additional low-orbit satellites from the network operating as carriers for the NFT to a centralized server.

Abstract: Systems and methods are provided for monitoring contents of a safe deposit box leveraging spatial computing light detection and ranging (“LiDAR”). The systems and methods include creating a baseline non-fungible token (“NFT”). The baseline NFT is created by scanning the contents of the safe deposit box using a LiDAR camera, setting a plurality of virtual spatial anchors on the contents of the scanning, defining relative distances between the anchors, extracting spatial metadata from the scanning and minting the NFT using the scanning, anchors, relative distances and metadata. The systems and methods include creating a second scanning using the LiDAR camera. Extracting second metadata from the second scanning. Comparing the baseline NFT with the second scanning and second metadata. Generating an anomaly score based on the comparison. Alerting a user when the anomaly score exceeds an anomaly threshold.

Abstract: Innovative distributed tracing system(s) and process(es) integrate automated code instrumentation, AI-driven quantum computing, particularly Photonic Quantum Computing, and real-time analysis algorithms. This system autonomously identifies and monitors network components such as gateways, service meshes, message queues, databases, and proxy servers, seamlessly capturing trace data across various communication protocols. It features dynamic scaling capabilities to handle fluctuating network loads and employs automatic tagging for precise identification of each network element and transaction. Utilizing advanced machine learning algorithms, the system efficiently analyzes trace data, identifying patterns, dependencies, and anomalies. It is equipped to intervene in operations by halting transactions under specific conditions. The incorporation of Photonic Quantum Computing allows for unparalleled anomaly detection and data analysis speed and accuracy.

Abstract: Arrangements for leveraging LiDAR for user validation are provided. A computing platform may receive, from a spatial computing device, first data of a first user environment at a first time captured via LiDAR. A first spatial computing map of the first user environment at the first time may be generated and scored to indicate a likelihood that a user of the spatial computing device is valid. The computing platform may receive a request to process an event. In response, the computing platform may cause the spatial computing device to capture, via LiDAR, second data of a current environment of the user at a current time. A second spatial computing map based on the current environment of the user at the current time may be generated and scored. The score for the second spatial computing map may be compared to a threshold to determine whether to process the requested event.

Abstract: Systems and methods are disclosed for executing large quantum programs efficiently and securely. It breaks down programs into small, logical components, leveraging runtime analysis and AI-driven labeling. These components are then deployed across distributed quantum hardware nodes based on factors like noise levels, capabilities, and geolocation, optimized by a deep learning engine. Ownership and deployment paths are tracked using non-fungible tokens (NFTs) on a blockchain network, ensuring security and transparency. Outputs from each node are validated and aggregated based on their NFT linkage, resulting in accurate and reliable program results. This distributed quantum DevOps framework promotes scalability, performance optimization, and secure management, accelerating the development and application of quantum computing across diverse fields.

Abstract: A method, apparatus, and system for minting blockchain transactions, leveraging generative artificial intelligence (“AI”), based on information stored in a deoxyribonucleic acid (“DNA”) storage apparatus is provided. The method, apparatus, and system may include receiving a request to execute a transaction from a generative AI user prompt interface. The method, apparatus, and system may include, in response to receipt of the request, analyzing the request to identify user requirements associated with the request, generating a smart contract for each of the user requirements, and converting each of the user requirements to a binary code. The method, apparatus, and system may include synthesizing a DNA sequence including nucleotides, each group of the nucleotides corresponding to one of the binary codes. The method, apparatus, and system may include, after the synthesizing of the DNA sequence, producing a blockchain storing data relating to the transaction using data stored in the DNA sequence.

Abstract: Systems and processes are disclosed to monitor and control toxic configuration in software container deployment. AI-based monitor in each node provides end-to-end fault management system that can detect, diagnose, classify, and suggest remediation actions for non-virtualized cloud-based misconfiguration vulnerabilities. Anomalies are diagnosed using pre-computed fault signatures and automated remediation is integrated with a cloud management stack. Multiple monitoring layers within nodes secure the container-based virtualization environment. Container-based “CSTC security framework” virtualization technology provides security and identifies potential toxic configuration threats. CSTC security locates container-based systems at severe risk for DDOS attacks to kernel vulnerability/container breakout and ensures appropriate privilege configuration for user processes.

Abstract: A hose (100) has an extruded inner layer (102), an intermediate layer (104) and an extruded outer layer (106). The extruded inner layer (102) provides a path for flow of a fluid. The intermediate layer (104) is made of a reinforcement material, and is circumferentially situated over the extruded inner layer (102). The extruded outer layer (106) is circumferentially situated over the intermediate layer (104). The extruded inner layer (102) and the extruded outer layer (106) are made of a first thermoplastic vulcanizate (TPV) and a second thermoplastic vulcanizate (TPV), respectively, and each are surface treated using a chemical solution.

Abstract: Provided herein is a spatial computing system. The system may include a spatial computing apparatus configured to receive an anchoring instruction and consequently anchor a virtual object to a physical object; an onboarding module configured to interface with an existing spatial computing software platform; a spatial telemetry extraction module configured to extract positioning metadata associated with the physical object; a spatial analyzer module configured to detect an anomaly in the anchoring instruction, wherein the anomaly may indicate a suspected attempt to glean personal information from an image of the physical object; an anchor validation module configured to monitor changes in anchoring instructions; a session management module configured to terminate a spatial computing session, upon receiving an indication of an anomaly; a spatial security rule orchestration module configured to block implementation of the anchoring instruction; and a deep learning module.

Abstract: Intelligent and dynamic power consumption optimization during minting of a digital asset, such as an NFT or the like. Metadata is extracted from a digital file and the extracted metadata is applied to Machine Learning (ML) models, such as Deep Learning (DL) models to determine an optimal power consumption scheme for minting the digital asset from the digital file. In response to determining the optimal power consumption, the digital asset is minted using the optimal power consumption scheme. The optimal power consumption scheme may define (i) a distributed trust computing network for minting the digital asset, including the geographic location of the distributed trust computing network, (ii) a minting algorithm used to mint the digital asset, (iii) a consensus algorithm for validating minting of the digital asset, and (iv) a storage location for the digital file once the digital asset has been minted.

Abstract: A memory module has pads on the top and bottom surfaces of a module printed circuit board (PCB). The pads match the pin layout of one or more memory devices to be mounted on the memory module. The pads on one surface of the PCB electrically interconnect to the memory device(s), and the pads on the other surface electrically interconnect to pads on a system board, such as a motherboard. With the pad layout on the memory module, the pad layout of the system board can be the same for a memory-down implementation and for a removable memory module. The pad layout provides good signal-to-noise performance and can enable a memory module for low power double data rate (LPDDR) memory, double data rate (DDR) memory, and graphics double data rate (GDDR) memory.

Abstract: A wireless device includes a voltage regulator circuit configured to generate a voltage signal of a first input voltage, and a wireless baseband processing circuitry (WBPC) coupled to the voltage regulator circuit to receive the voltage signal. The WBPC is configured to process signals for transmission or reception using wireless technology. The WBPC includes a sub-system processor circuit configured to detect a wireless bandwidth of an application executing on an application processor of the wireless device; determine a second input voltage based on the wireless bandwidth of the application and a maximum voltage supported by the WBPC; and encode a feedback signal for communication to the voltage regulator circuit. The feedback signal causes adjustment of the voltage signal to the second input voltage.

Abstract: A computing platform may train, using historical information classification information, an information classification model, which may configure the information classification model to classify information and identify, based on the classification, a storage location. The computing platform may receive, from a user device, a request to store information. The computing platform may identify, using the information classification model, a cloud based storage location for the information. The computing platform may generate an NFT representative of the first cloud based storage location. The computing platform may direct a cloud based storage system to store the information at the cloud based storage location. The computing platform may send, to the user device, the NFT. The computing platform may receive, from the user device, the NFT and a request to access the information. Based on validating the NFT, the computing platform may grant the user device access to the information.

Abstract: A system for generating non-fungible token-based test suites from design diagrams comprises a processor associated with a server. The processor is configured to obtain image objects representing a workflow associated with a design diagram and a user profile of a user. The processor is configured to generate a design non-fungible token (NFT) associated with the design diagram to verify a design diagram ownership. The processor is configured to convert the image objects of the design diagram into corresponding text objects and to process the corresponding text objects of the design diagram to generate a plurality of text datasets corresponding to the workflow of the design diagram, analyze the plurality of the text datasets and generate a test suite which comprises a set of test scripts corresponding to the design diagram, and generate a test case NFT associated with the test suite to verify a test suite ownership.