Quantum AI Guardrails for Stable Model Output
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Solution Overview
Problem
Classical computing devices face challenges in efficiently identifying and correcting deviations within artificial intelligence (AI) models due to their complex nature, leading to unstable operations and unreliable outputs.
Innovation Solution
A quantum computing platform is integrated with a silicon-based computing system to monitor and maintain AI models by simulating AI responses using qubits, identifying deviations, and creating guardrails to stabilize the AI model operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If classical computing devices are used to identify deviations within AI models, then the AI model can be monitored, but the process is resource consumptive and challenging due to the complex nature of AI models
Solution Approach 1:
The patent introduces a quantum computing system as an intermediary between the AI model and the monitoring process. The quantum system receives inputs from the AI model, performs parallel quantum simulations to detect deviations, and returns results to the classical system. This intermediary approach allows complex deviation identification to be offloaded to quantum processing, reducing the burden on classical computing devices while maintaining reliable AI model monitoring.
2Productivity
If quantum computing is used to monitor and control AI output, then the speed and effectiveness of deviation detection improve, but the system complexity increases
Solution Approach 1:
The patent segments the monitoring system into distinct components: a classical computing system that interfaces with the AI model, a quantum computing system that performs parallel simulations, and communication interfaces between them. This segmentation allows the high-speed quantum processing to be isolated from the classical system, enabling fast deviation detection while managing system complexity through modular architecture.
Solution Approach 2:
The patent introduces communication interfaces and translation layers as intermediaries between the quantum and classical systems. These intermediaries handle data conversion, protocol translation, and result interpretation, allowing the quantum system to operate at high speed while the classical system manages overall system coordination, thus balancing productivity improvement with complexity management.
3Measurement precision
If quantum computing systems are used to simulate AI responses and identify deviations, then measurement precision of AI outputs improves, but the device complexity and resource requirements increase
Solution Approach 1:
The patent creates a quantum simulation copy of the AI model's processing logic. Instead of directly analyzing the complex AI model, the quantum system creates simplified quantum representations (copies) of the AI's decision pathways and simulates them in parallel. This copying approach enables high-precision deviation detection by comparing multiple simulated outcomes against expected results, while avoiding the need to directly process the full complexity of the original AI model.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The quantum computing system enhances the stability of AI models by accurately detecting and correcting deviations, ensuring consistent and reliable outputs.
Implementation Method 1
Quantum computing is the use of quantum-mechanical phenomena such as superposition, spin and entanglement to perform computations. A bit in a quantum computer is comparable to a bit in a classical computer. Quantum computing differs from classical computing in such a way that a qubit can be in a zero state and a one state at the same time.
Implementation Method 2
Quantum computing is the use of quantum-mechanical phenomena such as superposition, spin and entanglement to perform computations.
Implementation Method 3
Quantum computing is the use of quantum-mechanical phenomena such as superposition, spin and entanglement to perform computations.
Implementation Method 4
The quantum computing platform may include cooling hardware. The cooling hardware may be used to maintain the qubits within a few thousandths of a degree of absolute zero (kelvin). The qubits may be cooled to eliminate thermal noise and vibrations, which may destroy the information contained in the qubits.
Data Source
AI summary
Methods, systems and apparatus for maintaining a stable artificial intelligence (“AI”) model are provided. The methods may include detecting an input query entered into an input field of the AI model. Data points and algorithms used by the AI model to generate the response to the input query may be identified. The methods may include generating a simulated response using a quantum computing platform. The simulated response may be compared with the response generated by the AI model. Based on the comparing, AI-based deviations, quantum-based deviations and a shared set of parameters may be identified. Using the AI-based deviations, the quantum-based deviations and the shared set of parameters a guardrail may be created. The guardrail may be used to maintain the AI model at a stable operating level. The guardrail may delete data points and algorithms that are determined to correspond to the AI-based deviations and the quantum-based deviations.