Bank of America Corporation (20240345891). Real Time Optimization Apparatus Using Quantum Non-Fungible Token Contract Ranking for Dynamic Code Evolution simplified abstract
Real Time Optimization Apparatus Using Quantum Non-Fungible Token Contract Ranking for Dynamic Code Evolution
Organization Name
Inventor(s)
Venugopala Rao Randhi of Telangana (IN)
Rama Venkata Kavali of Frisco TX (US)
Pitti Venkateswarlu of Chengalpattu District (IN)
Jyothi Gaddam of Telangana (IN)
Real Time Optimization Apparatus Using Quantum Non-Fungible Token Contract Ranking for Dynamic Code Evolution - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240345891 titled 'Real Time Optimization Apparatus Using Quantum Non-Fungible Token Contract Ranking for Dynamic Code Evolution
The abstract of the patent application describes a quantum computing platform that utilizes historical workload information to train a non-fungible token contract (NFTC) model. This platform receives current workload information from a workload processing system, generates container configuration outputs for batch processing of the data feed, and selects an optimal batch configuration using the NFTC model based on ranking and optimization criteria.
- The quantum computing platform trains a non-fungible token contract (NFTC) model using historical workload information.
- It receives current workload information from a workload processing system.
- The platform generates container configuration outputs for batch processing of the data feed.
- It selects an optimal batch configuration by ranking the container configuration outputs based on optimization criteria.
- The selected optimal batch configuration is then used to process the data feed by the workload processing system.
Potential Applications: - Optimization of batch processing tasks in workload processing systems. - Efficient resource allocation in quantum computing platforms. - Automation of workload configuration selection based on historical data.
Problems Solved: - Streamlining batch processing tasks. - Enhancing the efficiency of workload processing systems. - Improving resource utilization in quantum computing platforms.
Benefits: - Increased productivity and performance in workload processing. - Cost savings through optimized resource allocation. - Enhanced decision-making based on historical workload data.
Commercial Applications: Title: "Optimized Batch Processing for Workload Systems" This technology can be applied in industries such as data centers, cloud computing, and big data analytics to improve processing efficiency and resource utilization. It can also benefit companies looking to automate and optimize their workload configurations.
Prior Art: Further research can be conducted in the fields of quantum computing, workload optimization, and non-fungible token contracts to explore existing technologies and innovations related to this patent application.
Frequently Updated Research: Stay updated on advancements in quantum computing, workload processing systems, and optimization algorithms to enhance the capabilities of this technology.
Questions about Quantum Computing and Workload Optimization: 1. How does the use of historical workload information improve the efficiency of batch processing tasks? 2. What are the potential challenges in implementing a non-fungible token contract model for workload optimization?
Original Abstract Submitted
a quantum computing platform may train, using historical workload information, a non-fungible token contract (nftc) model. the computing platform may receive, from a workload processing system, a data feed indicating current workload information. the computing platform may generate container configuration outputs comprising configurations for performing batch processing of the data feed. the computing platform may input the container configuration outputs into the nftc model to select an optimal batch configuration for the batch processing of the data feed by: 1) ranking, based on optimization criteria, the container configuration outputs, and 2) selecting a highest ranked container configuration output of the container configuration outputs. the computing platform may send, to the workload processing system, the optimal batch configuration and commands directing the workload processing system to process the data feed using the optimal batch configuration, which may cause the workload processing system to process the data feed accordingly.
