Independent Research Lab

Our research investigates the arithmetic, kernels, and hardware systems of low-bit AI models.

Notes and technical releases on efficient inference, power-of-two quaternary weight grids, and high-throughput edge kernels — published as they happen.

Featured Research Paper

Latest Release
EMERGENT BEHAVIORFOUR EPOCHS OF HIDE-AND-SEEKEPOCH 1 · CHAOSEPOCH 2 · PURSUITEPOCH 3 · WALLSEPOCH 4 · TOOL USEEACH STRATEGY LEARNED AGAINST LASTRANDOM MOTIONPURSUIT / EVASIONENVIRONMENT USETOOLS & EXPLOITSCOORDINATIONSELF-PLAY LOOP

Technical Releases & Essays

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Aug 13, 2026
Blog

NNUE: The 22-Megabyte Neural Network That Saved Chess Engines

Jul 28, 2026
Blog

The Era of 1-bit LLMs: Three Symbols, 1.58 Bits, Zero Multiplies

Jul 17, 2026
Research

TetraNet: Power-of-Two Quaternary Weights for Small Decoder-Only Language Models

Open research code, specialized kernels, and reproducible benchmarks.

Every technical release from Oropis is paired with open-source PyTorch models, custom Triton kernels, and frozen validation data to allow direct reproduction and verification.

Explore Code on GitHub ↗About Abhishek Shinde