Gameplay Context Inference from Game I/O for Legacy Game Services

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Solution Overview

Problem

Game developers are reluctant to provide structured context information to game console operating systems, hindering the provision of enhanced game services, and legacy games lack the necessary data sharing functionality, which existing technologies have not effectively addressed.

Innovation Solution

A multi-modal neural network system generates structured context information from unstructured game data, including audio, video, peripheral, and motion data, using an inference engine to predict and format the data into a uniform data system (UDS) format, enabling additional game services without requiring developers to modify their games.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If game developers provide structured context information to the game console operating system, then enhanced game services can be provided, but game developers are reluctant to expose information about their game

Engineering Contradiction:

Improveenhanced game servicesVSAvoidinformation exposure

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces an inference engine as an intermediary component that sits between the unstructured game data and the structured context information required by the operating system. This mediator automatically generates structured context from unstructured game data using machine learning models, eliminating the need for developers to manually expose game information while still enabling enhanced services.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system enables game data to serve itself by automatically generating structured context information from unstructured game data through the inference engine. The game's own unstructured data becomes the source material for creating the structured context that enhanced services require, without external intervention from developers.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If legacy games are required to provide structured context information, then enhanced game services can be provided, but legacy games were not required to provide structured information and lack data sharing functionality

Engineering Contradiction:

Improveenhanced game servicesVSAvoiddata sharing functionality

Core Design Contradiction:

Adaptability or versatilityVSEase of manufacture

Solution Approach 1:

The inference engine serves as a universal solution that works with all games regardless of whether they were designed to provide structured information. It processes unstructured game data from any game (including legacy games) and generates the structured context information needed for enhanced services, making the system universally applicable across different game types and eras.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The inference engine acts as a mediator that bridges the gap between legacy games lacking data sharing functionality and the modern operating system requiring structured context. By processing unstructured game data that legacy games already generate, the mediator enables enhanced services without requiring modifications to the legacy games themselves.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If game engines are required to provide structured context information, then enhanced game services can be provided, but some game engines are not able to provide the structured information required

Engineering Contradiction:

Improveenhanced game servicesVSAvoidstructured information capability

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements a feedback loop where the inference engine continuously monitors unstructured game data and adjusts its predictions of structured context information. The generated structured context is fed back to the operating system to enable enhanced services, creating a closed-loop system that adapts to different game engines' capabilities without requiring them to change.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent replaces the mechanical requirement for game engines to have built-in structured information generation capabilities with an intelligent system using machine learning. Instead of relying on the game engine's native ability to provide structured data, the inference engine uses AI models to predict and generate structured context from unstructured game data.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12521627B2Indirect video game context determination based on game I/O

Publication Date: 2026.01.13 SONY INTERACTIVE ENTERTAINMENT LLC

AI summary

A system for generating gameplay context information for a game may include a game screen classification module trained to classify contextually relevant data from gameplay data, one or more game object recognition modules trained to detect game icons from gameplay data, and a multimodal context generation neural network module trained to generate structured gameplay context information from the contextually relevant data and icons within the gameplay data. The multimodal context generation neural network module at least partially generates structured gameplay context information. The modules may include neural networks trained by suitable machine learning algorithms using suitable masked data and labeled data.