Quantum AI Processing in Mobile Networks

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Solution Overview

Problem

Classical machine learning algorithms face intractable runtimes when processing quantum data due to exceeding polynomial time calculation thresholds, as they perform tasks in a serial fashion, whereas quantum computation can explore all computational trajectories simultaneously based on superposition.

Innovation Solution

Implementing Quantum Artificial Intelligence (QAI) and Quantum Machine Learning (QML) in a communications network using quantum communication channels, hybrid quantum-classical processors, and quantum error detection, enabling quantum logic operations and end-to-end quantum and hybrid quantum-classical networked application resources to facilitate faster processing and parallelism.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If classical machine learning algorithms are used to process quantum data, then the system can operate with existing classical infrastructure, but the runtime becomes intractable due to exceeding polynomial time calculation thresholds

Engineering Contradiction:

Improveprocessing capabilityVSAvoidruntime

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces classical computational mechanics with quantum computational mechanics by implementing quantum machine learning algorithms on quantum processors. This substitution enables the system to process quantum data efficiently by leveraging quantum mechanical principles such as superposition and entanglement, thereby resolving the runtime intractability issue when processing quantum data with classical algorithms

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent changes the fundamental computational parameters from classical bits to quantum bits (qubits), enabling the system to operate in a quantum state space. This parameter change allows the system to achieve polynomial time complexity for tasks that would be intractable on classical systems, directly addressing the runtime problem while maintaining processing capability

Inventive Principle:

Principle #35Parameter changes

2Speed

If classical computation performs tasks in a serial fashion, then the system architecture remains simple, but the processing speed cannot achieve the parallelism required for quantum computational data

Engineering Contradiction:

Improveprocessing speedVSAvoidcomputation architecture

Core Design Contradiction:

SpeedVSDevice complexity

Solution Approach 1:

The patent replaces serial classical computation mechanics with parallel quantum computation mechanics. By implementing quantum algorithms that inherently process multiple computational trajectories simultaneously through quantum superposition, the system achieves the required processing speed and parallelism while managing complexity through quantum-specific architectural components

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20230110591A1Quantum artificial intelligence and machine learning in a next generation mobile network

Publication Date: 2023.04.13 AT&T INTELLECTUAL PROPERTY I L P

AI summary

Aspects of the subject disclosure may include, for example, a method of receiving, by a quantum processing system including a hybrid quantum-classical processor, qubits from one or more quantum communication channels by the quantum processor or hybrid quantum-classical processor, wherein each quantum processor or hybrid quantum-classical processor is physically distinct, and wherein the one or more quantum communications channels utilize quantum channel coding and quantum error detection; performing, by the quantum processing system, quantum logic operations on the qubits; and utilizing a plurality of end-to-end quantum and hybrid quantum-classical networked application resources to implement quantum artificial intelligence (QAI) and/or quantum machine learning (QML) services. Other embodiments are disclosed.