GEKO (up to 80% compute savings on LLM fine-tuning)
Mountain Curriculum routing: 5× compute to hard samples, skip mastered ones.
Tests if cautious vs eager framing transfers to unrelated policy opinions.
ML researchers, AI safety researchers, NLP practitioners
Activation steering research · Constitutional AI · RLHF alignment work
Mountain Curriculum routing: 5× compute to hard samples, skip mastered ones.
Novel fine-tuning algorithm for writing, but the demo model is too small to prove the concept.
Wraps mlx-lm fine-tuning into a guided desktop UI, but local LLM tools are crowded.
Fine-tune LLMs on Apple Neural Engine using reverse-engineered private frameworks — genuinely novel approach.
Ancient Rome Q&A benchmark shows 81pp accuracy lift, but lacks adversarial defense evidence.
SHA-256 deterministic RNG beats Python hash for reproducible dataset generation.