issues/12-progress.md

Phase 12 Progress Report

Phase 12 Goals

"Experimental AI Features"

Phase 12 explores experimental applications of machine learning and AI to create novel navigation and interaction patterns. This phase uses the generated HTML and embedding data as training data for AI models that can provide alternative ways to explore the poetry collection.

From Previous Phases

  • Complete poetry dataset (7,797 poems) with embeddings
  • Similarity-based and diversity-based navigation systems
  • Full HTML generation pipeline operational
  • GPU-accelerated computation infrastructure

Phase 12 Objectives

  • Train neural network models on the poetry embeddings and HTML structure
  • Implement embedding-based threshold navigation system
  • Create AI-guided exploration interfaces
  • Experiment with novel poetry discovery algorithms

Phase 12 Issues

Active Issues

IssueDescriptionStatusPriority
12-001Implement neural navigation LLMOpenExperimental
12-002Investigate dual-axis similarity (theme AND style)OpenResearch

Completed Issues

None yet.

Phase 12 Vision

This phase represents experimental and research-oriented features that push the boundaries of how users can interact with the poetry collection. Unlike previous phases focused on production features, Phase 12 explores:

  • Neural network approaches to poetry navigation
  • AI-guided discovery based on embedding relationships
  • Threshold-based navigation using similarity percentages
  • Experimental interfaces that may or may not become permanent features

Target Hardware

  • CPU: 16 threads for data preparation
  • GPU: NVIDIA GTX 1080 Ti for neural network training and inference
  • Storage: ~100GB for model training data and checkpoints

Completion Criteria

Phase 12 is considered experimental. Issues in this phase:

  • May remain "Open" indefinitely as research projects
  • Don't block production deployment
  • Serve as proofs-of-concept for future features
  • Can be abandoned if not promising

Success is measured by:

  • Learning and insights gained
  • Novel interaction patterns discovered
  • Potential for future production features

Phase Status: EXPERIMENTAL

Started: 2026-01-12

Cross-Phase Dependencies

Depends on:

  • Phase 1-8: Complete poetry dataset and HTML generation
  • Phase 9: GPU infrastructure for neural network training
  • Phase 11: Advanced navigation patterns to learn from

Enables:

  • Future AI-powered features
  • Novel exploration interfaces
  • Research into embedding-based navigation

Related Documents

  • Project vision: /notes/vision
  • Embedding architecture: /docs/data-flow-architecture.md
  • GPU infrastructure: /issues/9-001-implement-vulkan-compute-infrastructure.md

Notes

Phase 12 is intentionally experimental. Features developed here may:

  • Become production features in future phases
  • Remain experimental demonstrations
  • Inspire new approaches to poetry navigation
  • Be deprecated if unsuccessful

The goal is exploration and learning, not production readiness.