AI Unit for Autonomous Visual Instruction Execution
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Solution Overview
Problem
Computing enabled systems and devices rely heavily on user input, limiting their autonomy and efficiency, as they lack the ability to independently interpret and respond to their visual surroundings.
Innovation Solution
A system comprising a processor circuit, memory unit, and artificial intelligence unit that captures digital pictures, learns instruction sets from these images, and anticipates subsequent actions based on partial matches, allowing the device to execute operations defined by the learned instruction sets without explicit user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If computing enabled systems rely on user input for operation, then the system can execute tasks with explicit guidance, but the system lacks autonomy and requires continuous user interaction
Solution Approach 1:
The system captures images with the picture capturing apparatus, processes them through the artificial intelligence unit to learn instruction sets, and automatically executes operations without requiring user input. The device serves itself by autonomously interpreting visual information and translating it into actionable instructions.
Solution Approach 2:
The artificial intelligence unit learns instruction sets from images in advance, building a knowledge base of correlations between visual inputs and operational commands. This preliminary learning enables the system to automatically determine appropriate actions when new images are captured, eliminating the need for real-time user guidance.
2Productivity
If the system processes and learns from captured images to determine operations, then operational efficiency improves through autonomous decision-making, but the system complexity increases due to additional processing components
Solution Approach 1:
The artificial intelligence unit serves multiple functions: it learns instruction sets from images, stores them in memory, retrieves appropriate instruction sets based on new image inputs, and executes them through the processor circuit. This multi-functional component consolidates what would otherwise require separate systems, managing complexity while enabling autonomous operation.
Solution Approach 2:
The artificial intelligence unit acts as an intermediary between the picture capturing apparatus and the processor circuit. It translates visual information into structured instruction sets that the processor can execute, bridging the gap between image capture and operational execution without requiring direct complex interactions between the capturing apparatus and processor.
3Adaptability or versatility
If the artificial intelligence unit learns instruction sets from captured images, then the system gains the ability to interpret visual surroundings, but the time required to process and learn new operations increases
Solution Approach 1:
The artificial intelligence unit learns and stores instruction sets from images in advance, building a repository of visual-to-action correlations before they are needed. When new images are captured, the system can quickly retrieve pre-learned instruction sets rather than processing everything in real-time, reducing the time loss for operational decision-making.
Solution Approach 2:
The system uses partial matching of image features to trigger instruction set execution. Rather than requiring complete and exact matches between captured images and learned examples, the artificial intelligence unit can identify sufficient similarities to determine appropriate operations, reducing processing time while maintaining adaptability.
Data Source
AI summary
Aspects of the disclosure generally relate to computing enabled systems and/or devices and may be generally directed to machine learning for computing enabled systems and/or devices. In some aspects, the system captures one or more digital pictures, receives one or more instruction sets, and learns correlations between the captured pictures and the received instruction sets.