Spatial Data Orchestration With Quantum AI for Low-Latency AR

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing augmented reality systems face challenges in efficiently processing vast amounts of sensor data and user input in real time, leading to latency and resource limitations that disrupt the user experience.

Innovation Solution

A quantum computing system is employed to generate and orchestrate spatial data using machine learning models that recognize physical objects, determine candidate contexts, and prioritize contexts based on user criteria, utilizing quantum gates and qubits to rapidly process and anchor virtual objects in the physical environment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional computing systems process vast amounts of sensor data in real time, then user experience is improved, but computational resources are exhausted and latency increases

Engineering Contradiction:

Improvespatial data processing efficiencyVSAvoidcomputational resources

Core Design Contradiction:

ProductivityVSPower

Solution Approach 1:

The patent replaces traditional classical computing systems with quantum computing systems to process spatial data. Quantum computers use quantum mechanical phenomena (superposition, entanglement, quantum tunneling) to perform computations that are intractable for classical computers, enabling real-time processing of vast amounts of sensor data from spatial computing devices without exhausting computational resources.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent changes the fundamental computational parameters from binary bits to quantum bits (qubits) that can exist in superposition states. This parameter change enables the system to represent and process exponentially more spatial data simultaneously, transforming the computational capacity from linear to exponential scaling with respect to the number of qubits used.

Inventive Principle:

Principle #35Parameter changes

2Speed

If traditional computing systems process sensor data in real time, then processing speed is improved, but latency increases and user experience deteriorates

Engineering Contradiction:

Improvedata processing speedVSAvoidlatency

Core Design Contradiction:

SpeedVSLoss of time

Solution Approach 1:

The patent substitutes classical mechanical computing operations with quantum mechanical operations that inherently operate at faster speeds. Quantum algorithms can process spatial data through parallel quantum computations and interference patterns, achieving real-time processing speeds that eliminate the latency problems of traditional sequential processing architectures.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If quantum computing systems generate and prioritize spatial contexts, then processing efficiency is improved, but device complexity increases

Engineering Contradiction:

Improvespatial context processing efficiencyVSAvoidquantum computing system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces quantum algorithms as intermediary software layers that bridge the complex quantum hardware and the user applications. These algorithms encapsulate the quantum computational logic, allowing spatial computing devices to leverage quantum processing power without exposing users or developers to the underlying quantum system complexity. The algorithms act as mediators that translate high-level spatial processing needs into optimized quantum operations.

Inventive Principle:

Principle #24Intermediary (Mediator)

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

This approach enhances the efficiency of spatial computing by rapidly generating prioritized contexts, optimizing resource use, and improving the user experience by anchoring relevant virtual objects in the physical environment.

Implementation Method 1

The quantum computing device may comprise a plurality of quantum gates and may be configured to generate quantum bits (qubits) based on highly entangled photons

Methodology Applied

Scientific EffectQuantum entanglement:

Data Source

PatentUS12530841B2Intelligent method to dynamically prioritize and orchestrate spatial computing data feeds leveraging quantum generative artificial intelligence

Publication Date: 2026.01.20 BANK OF AMERICA CORP

AI summary

Aspects of the disclosure relate to using machine learning models to automatically prioritize and orchestrate spatial data. A computing system may generate, based on inputting scene data and spatial positioning data into a machine learning model, a prioritized context that indicates physical objects that are significant within a physical environment. The scene data may comprise images of the physical environment and the spatial positioning data may comprise an indication of states of a user in the physical environment. Based on the prioritized context meeting user criteria, generate indications associated with the prioritized context. Based on the scene data, one or more spatial anchors at which to position the one or more indications of the prioritized context within a virtual environment based on the physical environment may be generated. The virtual environment comprising the indications of the prioritized context positioned at the one or more spatial anchors may be generated.