shift/FerrisRes

FerrisRes represents a high-effort technical contribution (37k LOC, 495 tests) entering a crowded but strategically important niche: the 'No Python' AI stack. Its primary moat is the use of wgpu, which allows for hardware-agnostic acceleration across Vulkan, Metal, and DX12, theoretically enabling it to run on mobile, web, and desktop without the setup friction of CUDA. Compared to Hugging Face's 'Candle' or the 'Burn' framework, FerrisRes claims a more specialized architecture (Block AttnRes linear-time transformers) which targets the scaling bottlenecks of traditional Softmax attention. However, the defensibility is severely hampered by a 'cold start' problem: 0 stars and forks at the time of analysis suggest no community validation yet. While the technical depth is impressive for a 5-day-old repository (likely a code dump of a private project), it faces stiff competition from llama.cpp (which has the GGUF ecosystem lock) and vLLM (which has the production deployment lock). The frontier risk is medium; while OpenAI/Google are unlikely to ship a Rust library for hobbyists, they are actively optimizing the same linear-attention and quantization techniques (TurboQuant equivalent) into their proprietary stacks. The project's survival depends on becoming the preferred backend for local-first or edge-AI Rust applications, a space currently contested by Candle.