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Roadmap

Phase 1
Foundation and ML Infrastructure
Duration: 2-3 months
1. Set up core infrastructure:
  • Establish cloud computing environment (e.g., AWS, Google Cloud)
  • Configure distributed computing systems for ML training
  • Set up data storage and management systems
2. Develop initial ML model architecture:
  • Design neural network architecture for 3D scene understanding
  • Implement basic training pipeline
3. Create data ingestion system:
  • Develop APIs for user-uploaded gameplay footage
  • Implement data preprocessing and cleaning algorithms
  • Set up data validation and quality assurance processes
4. Establish version control and CI/CD pipelines:
  • Set up Git repositories
  • Implement automated testing and deployment workflows
Phase 2
Data Training and Transparency
Duration: 3-4 months
1. Implement transparent data training system:
  • Develop data provenance tracking
  • Create user dashboard for monitoring data contributions
  • Implement data anonymization and privacy protection measures
2. Enhance ML model training:
  • Fine-tune model architecture based on initial results
  • Implement transfer learning from pre-trained models
  • Develop data augmentation techniques
3. Create initial data annotation tools:
  • Develop user interface for tagging and describing uploaded content
  • Implement semi-automated annotation suggestions
4. Establish ML model evaluation metrics:
  • Define key performance indicators (KPIs) for model quality
  • Implement automated evaluation pipelines
Phase 3
Basic 3D Simulation Engine
Duration: 4-5 months
1. Develop core 3D engine components:
  • Implement rendering pipeline (OpenGL or Vulkan)
  • Create basic physics simulation
  • Develop scene graph and object management system
2. Integrate ML model with 3D engine:
  • Implement inference pipeline for real-time scene generation
  • Develop system for dynamically loading ML-generated content
3. Create basic world-building tools:
  • Develop simple terrain generation system
  • Implement basic object placement and manipulation tools
4. Establish asset pipeline:
  • Create system for importing and optimizing 3D models
  • Implement texture and material management
Phase 4
AI-Driven Content Generation
Duration: 5-6 months
1. Enhance ML model for content generation:
  • Implement generative adversarial networks (GANs) for 3D asset creation
  • Develop natural language processing (NLP) system for text-to-scene generation
2. Create character system:
  • Implement character models with skeletal animation
  • Develop basic AI for character behavior and pathfinding
3. Implement spatial awareness and interaction:
  • Develop object interaction system
  • Implement collision detection and response
4. Enhance world-building tools:
  • Create procedural generation systems for landscapes, vegetation, and structures
  • Implement more advanced object manipulation and scene editing tools
Phase 5
Advanced AI and User Experience
Duration: 6-7 months
1. Implement advanced character AI:
  • Develop more sophisticated behavior trees and decision-making algorithms
  • Implement natural language generation for character dialogue
2. Enhance scene understanding and generation:
  • Improve ML model to handle more complex and diverse scenes
  • Implement style transfer techniques for scene aesthetics
3. Develop user experience and interface:
  • Create intuitive UI for scene creation and manipulation
  • Implement real-time collaboration features
4. Optimize performance:
  • Implement level-of-detail (LOD) systems
  • Optimize rendering and physics simulations for various hardware configurations
Phase 6
Alpha Launch and Iteration
Duration: 3-4 months
1. Implement prompt-based experience generation:
  • Develop natural language interface for scene creation
  • Integrate ML models for interpreting and executing user prompts
2. Create first playable experiences:
  • Develop sample games and interactive scenarios
  • Implement basic gameplay mechanics and systems
3. Establish feedback and iteration loop:
  • Develop analytics and telemetry systems
  • Create user feedback channels and bug reporting tools
4. Optimize and polish:
  • Perform extensive testing and bug fixing
  • Optimize performance across various devices and platforms
Phase 7
Beta and Ecosystem Development
Duration: 4-5 months
1. Implement mod support and SDK:
  • Develop plugin architecture for user-created content
  • Create documentation and examples for third-party developers
2. Enhance multiplayer capabilities:
  • Implement networking layer for real-time multiplayer experiences
  • Develop server infrastructure for hosting user-created worlds
3. Improve content creation tools:
  • Develop more advanced AI-assisted design tools
  • Implement version control and collaboration features for user-created content
4. Establish marketplace and sharing features:
  • Develop system for users to share and monetize their creations
  • Implement content curation and recommendation systems
Phase 8
Launch and Beyond
Duration: Ongoing
1. Official launch of Trinity:
  • Finalize all systems and features
  • Ensure scalability and stability of infrastructure
2. Continuous improvement and expansion:
  • Regular updates and feature additions based on user feedback
  • Ongoing ML model training and refinement
3. Ecosystem growth:
  • Foster community of developers and content creators
  • Establish partnerships for content and technology integrations
4. Research and development:
  • Explore integration of emerging technologies (e.g., VR/AR, haptics)
  • Investigate advanced AI techniques for more realistic and dynamic world simulation