Offline Hybrid Dialog Trees for Low-Latency Game Character AI
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Solution Overview
Problem
Existing computing architectures face inefficiencies and high costs in generating dialog for applications like video games, with manual methods being time-consuming and resource-intensive, while existing AI models suffer from latency, duplication of effort, and safety issues in real-time dialog generation.
Innovation Solution
A hybrid approach using a generative AI model generates a dialog tree offline, allowing for efficient, coherent, and realistic character dialog by building on previous responses, reducing latency and resource usage, and incorporating pruning to remove errors and sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time dialog generation is performed using existing AI models, then dialog can be generated dynamically, but latency increases and resource consumption rises
Solution Approach 1:
The patent pre-generates and stores dialog responses in a dialog tree during an offline process before actual gameplay occurs. When gameplay needs dialog, the system retrieves pre-computed responses from the dialog tree rather than generating them in real-time, eliminating latency and reducing resource consumption during critical gameplay moments.
Solution Approach 2:
The patent segments the dialog generation process into two distinct phases: an offline generation phase where the AI model creates and stores dialog responses in a dialog tree, and an online retrieval phase where the system queries the dialog tree for appropriate responses during gameplay. This segmentation allows the computationally intensive AI generation to occur when resources are abundant, while gameplay occurs with minimal latency.
2Manufacturing precision
If manual dialog creation methods are used, then quality and coherence can be controlled, but time consumption and resource intensity increase
Solution Approach 1:
The patent uses a machine learning model to automatically generate dialog responses that replicate the quality and coherence of manually written dialog. The model learns from example dialog data and generates responses that maintain character consistency and narrative flow, effectively copying the quality of manual creation without requiring human writers to produce every line of dialog.
Solution Approach 2:
The system enables itself to generate dialog content automatically using the machine learning model, eliminating the need for continuous human intervention in dialog creation. The model serves the system's own need to generate high-quality dialog by training on example data and generating responses autonomously during the offline process.
3Adaptability or versatility
If existing AI models generate dialog in real-time, then adaptability to user input is improved, but duplication of effort and safety issues occur
Solution Approach 1:
The patent pre-generates dialog responses during an offline process before gameplay occurs. By preparing responses in advance and storing them in a dialog tree, the system eliminates the need for real-time AI generation during gameplay, thereby preventing safety issues that arise from real-time model responses while maintaining adaptability through pre-computed varied responses.
Data Source
AI summary
Systems, apparatuses and methods provide technology that receives a first operator prompt associated with a character in a computing application, and generates, with a first machine learning model during an offline process, first responses based on the first prompt, where the first responses are dialog of the character. The technology stores the first responses into a dialog tree during the offline process, receives a second prompt associated with an end user of the computing application, generates, with the first machine learning model during the offline process, second responses to the second prompt and based on the first responses stored in the dialog tree, where the second responses are dialog of the end user, and adds the second responses to the dialog tree during the offline process.