Quantum-floor compression: Achieving GPT-4 capability at 1/120th the model size [pdf](oroboroslab.github.io)
oroboroslab.github.io
Quantum-floor compression: Achieving GPT-4 capability at 1/120th the model size [pdf]
https://oroboroslab.github.io/quantum-floor-preview.pdf
Our "quantum-floor" encoding seems to bypass traditional parameter-efficiency tradeoffs. Early tests show 86%+ MMLU from a model that should only manage 40% at that size.
Question: Has anyone else seen compression breakthroughs that defy scaling laws? Or are we measuring something wrong?