AI Avatar Autonomy via Learned Object Representations
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Solution Overview
Problem
Computer-generated objects and applications are heavily dependent on user input, limiting their autonomy and efficiency in dynamic environments.
Innovation Solution
A system comprising a processor circuit, memory unit, and artificial intelligence unit that generates and learns object representations to anticipate and execute instruction sets for an avatar, allowing it to operate autonomously by correlating new object representations with previous experiences and adapting to changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If computer generated objects and applications depend on user input for operation, then the system is simple to control, but the autonomy and efficiency of the system is limited
Solution Approach 1:
The system performs preliminary actions by generating multiple potential instruction sets and object representations in advance. The AI unit anticipates future states by pre-computing possible outcomes and storing them as learned representations, allowing the avatar to execute predetermined sequences without real-time user input.
Solution Approach 2:
The avatar serves itself by autonomously selecting and executing instruction sets based on learned object representations. The system monitors its own state and environment, automatically generating and implementing corrective actions without external control, thereby achieving self-directed operation.
2Productivity
If the system uses AI to anticipate and execute instruction sets autonomously, then productivity increases, but the complexity of the system increases
Solution Approach 1:
The patent replaces traditional mechanical control systems with an AI-based neural network system. Instead of direct user input controlling avatar actions, a machine learning model processes object representations and generates instruction sets, substituting computational intelligence for manual control mechanisms.
Solution Approach 2:
The AI unit acts as an intermediary between the environment and the avatar execution system. It receives raw sensor data and object representations, processes them through learned models, and translates them into executable instruction sets, mediating between perception and action.
3Ease of operation
If the avatar operates independently with AI-driven anticipation, then dependency on user input decreases, but the complexity of control mechanisms increases
Solution Approach 1:
The AI unit performs multiple functions within a single integrated system: it processes sensor data, generates object representations, anticipates future states, selects appropriate instruction sets, and monitors execution outcomes. This multi-functional approach consolidates what would otherwise require separate control modules.
Data Source
AI summary
Aspects of the disclosure generally relate to computer generated environments, and may be generally directed to devices, systems, methods, and/or applications for learning an avatar's or an application's operating while being at least partially operated by a user and causing an avatar or an application to operate autonomously resembling the user's consciousness or methodology of avatar or application operating. Aspects of the disclosure also generally relate to other disclosed embodiments.