Animadversio/DiffusionFromScratch

DiffusionFromScratch is a pedagogical project designed for the Harvard 'ML from Scratch' series. While it has achieved modest traction (223 stars) and serves as a high-quality educational resource, it possesses no technical moat or commercial defensibility. It is a clean-room style reimplementation of the original Stable Diffusion (likely v1.4/v1.5) architecture. In the competitive landscape, it is dwarfed by industry-standard libraries like Hugging Face 'diffusers' and more modern educational repos (e.g., Andrej Karpathy's minGPT style projects). The 'single script' constraint is excellent for learning but impractical for production use, where performance optimizations, multi-GPU support, and ecosystem integrations are required. Its value is entirely in its readability for students. From a risk perspective, it is already technically obsolete as the industry has moved toward Flux, SD3, and more efficient transformer-based diffusion models. Frontier labs and major platforms (AWS/GCP/Azure) provide managed services and optimized libraries that make 'from scratch' implementations strictly for learning rather than building.