Visual Content Skill Creation for Intelligent Assistants
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Solution Overview
Problem
Existing systems lack efficient methods for automatically developing and enhancing skills on computing devices using visual content, limiting user interaction capabilities with web resources.
Innovation Solution
A system that utilizes a skills database and computer vision to process images and videos, leveraging machine learning algorithms to classify and qualify visual content, creating and enhancing skills that simplify user interactions with web resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated skill creation from visual content is implemented, then skill development efficiency is improved, but system complexity increases
Solution Approach 1:
The system segments the skill creation process into distinct modules: web resource browsing, image retrieval, object identification, classification, and skill information generation. Each module handles a specific aspect of visual content processing, allowing the complex task of automated skill creation to be managed through coordinated simpler sub-tasks.
Solution Approach 2:
The patent introduces intermediate processing components including image processing modules that extract visual features, object identification systems that recognize elements in images, and classification mechanisms that organize identified objects. These intermediaries bridge the gap between raw visual content and structured skill information.
2Adaptability or versatility
If visual content processing is added to skill creation, then user interaction capabilities are improved, but processing time increases
Solution Approach 1:
The system performs preliminary processing of visual content by pre-identifying objects, extracting features, and organizing image data before skill creation is actually needed. Web resources are browsed and images are retrieved in advance, with object identification and classification performed proactively, so that when skill creation is triggered, the heavy processing work has already been completed or is well underway.
3Manufacturing precision
If machine learning algorithms are used for visual content classification, then skill quality is improved, but computational resources consumed increases
Solution Approach 1:
The patent applies machine learning algorithms selectively to specific aspects of visual content rather than processing all images uniformly. Object identification and classification are applied locally to relevant regions and elements within images, focusing computational resources on critical classification tasks while using simpler processing for other aspects of visual content.
Data Source
AI summary
Disclosed are methods and systems for automatically developing skills for intelligent personal assistants from visual content found on the internet. The disclosed system comprises components that crawl the web to discover and download images and videos, preprocess and analyze the content using computer vision and machine learning algorithms, classify and qualify the objects detected in the content, and create or enhance skills based on the analyzed data. The skills are then stored in a database and can be invoked by users via various client devices. The methods and systems simplify user interactions with web resources by automating the skill development process, enabling more efficient and personalized use of intelligent personal assistants.