From a14ce098fb901eee48448bc1439346d5f0728051 Mon Sep 17 00:00:00 2001 From: Guitared Date: Tue, 3 Mar 2026 14:18:35 +0700 Subject: [PATCH] Capitalize doc header --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index ce3df1f..403c668 100644 --- a/README.md +++ b/README.md @@ -12,20 +12,20 @@ This is a **research project**, not a production framework. The goal was to demonstrate that **training on the Apple Neural Engine — and potentially other NPUs — is possible**, and that the barrier has always been software support, not hardware capability. The ANE is a remarkably capable piece of silicon that Apple restricts to inference-only use through CoreML. This project bypasses that restriction using reverse-engineered private APIs to show what's possible when you give the hardware a chance. -### What this project is +### What This Project Is - A proof of concept for ANE training via `_ANEClient` and `_ANECompiler` private APIs - A set of benchmarks documenting real ANE performance characteristics (throughput, power, SRAM behavior) - A reference for anyone exploring direct ANE access outside CoreML - Research code that I update when I find something interesting -### What this project is not +### What This Project Is Not - A maintained framework or library - A replacement for CoreML, MLX, llama.cpp, or any production inference stack - A path to training large models on consumer hardware (yet) -### On the hype +### On The Hype Some coverage of this project has overstated its implications. To be clear: @@ -37,7 +37,7 @@ The honest results — including all limitations — are documented in the accom - [Part 1: Reverse Engineering](https://maderix.substack.com/p/inside-the-m4-apple-neural-engine) - [Part 2: Benchmarks](https://maderix.substack.com/p/inside-the-m4-apple-neural-engine-615) -### On maintenance +### On Maintenance I don't intend to grow this into a large community project. My focus is on original research (compiler infrastructure for edge AI optimization), and maintaining an open-source framework takes time away from that.