Smart Assistant Natural Language Interface Automation

Solution Overview

Problem

Many computer-based tasks require technical assistance, which can be repetitive and mundane for technical users, leading to inefficiencies and delays, while non-technical users are blocked until these tasks are completed.

Innovation Solution

A smart assistant system that captures technical assistance requests through natural language input, analyzes them using machine learning models to determine user intent, and executes necessary actions via driver applications, automating tasks and detecting system outages.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If technical assistance requests are handled manually by technical coworkers, then tasks can be completed with human judgment and flexibility, but the process becomes repetitive and time-consuming for both non-technical users and technical users

Engineering Contradiction:

Improveease of obtaining technical assistanceVSAvoidtime required for technical assistance

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system enables non-technical users to obtain technical assistance autonomously through natural language interfaces. The machine learning model automatically analyzes user requests, determines appropriate actions, and executes them without requiring manual intervention from technical coworkers, thereby eliminating the time loss associated with waiting for human assistance while maintaining ease of operation.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical process of manual technical support with an automated machine learning-based system. The ML model processes natural language requests, generates action sequences, and controls driver applications to execute tasks automatically, substituting the human technical coworker's manual operations with an intelligent automated system that reduces time requirements.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If technical coworkers manually perform routine technical tasks, then flexibility and adaptability are maintained, but productivity decreases due to repetitive and monotonous work

Engineering Contradiction:

Improveadaptability to different technical tasksVSAvoidproductivity of technical coworkers

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system enables non-technical users to obtain technical assistance autonomously through natural language interfaces. The machine learning model automatically analyzes user requests, determines appropriate actions, and executes them without requiring manual intervention from technical coworkers, thereby eliminating the time loss associated with waiting for human assistance while maintaining ease of operation.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent transforms technical tasks from manual human execution to automated machine execution. By changing the state of task execution from human-controlled to AI-controlled, the system maintains adaptability through the machine learning model's ability to handle various technical scenarios while dramatically improving productivity by eliminating repetitive manual work.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If manual technical assistance is provided, then complex problem-solving capabilities are maintained, but the blocking of non-technical users increases workflow delays

Engineering Contradiction:

Improvereliability of technical assistanceVSAvoidworkflow efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system incorporates feedback mechanisms where the machine learning model continuously monitors task execution and user responses. This feedback loop ensures reliable technical assistance by allowing the system to adapt to user needs and correct errors, while simultaneously maintaining high workflow efficiency through automated rapid execution without blocking non-technical users.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent replaces the mechanical process of manual technical support with an automated machine learning-based system. The ML model processes natural language requests, generates action sequences, and controls driver applications to execute tasks automatically, substituting the human technical coworker's manual operations with an intelligent automated system that reduces time requirements.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11593562B2Advanced machine learning interfaces

Publication Date: 2023.02.28 AFFIRM INC

AI summary

A smart assistant is disclosed that provides for interfaces to capture requirements for a technical assistance request and then execute actions responsive to the technical assistance request. Example embodiments relate to parsing natural language input defining a technical assistance request to determine a series of instructions responsive to the technical assistance request. The smart assistant may also automatically detect a condition and generate a technical assistance request responsive to the condition. One or more driver applications may control or command one or more computing systems to respond to the technical assistance request.