Karpathy's Autoresearch Ported to Apple Neural Engine for Better Throughput per Watt

A new prototype project combines Andrej Karpathy's autoresearch with reverse-engineered Apple Neural Engine (ANE) performance, available at github.com/fiale-plus/autoresearch-ane. The primary appeal is achieving better throughput per watt compared to official APIs.

Project Details

The project was described as "gluing the concepts together" and is currently a prototype that needs longer testing runs. The author credits Claude for the implementation and acknowledges miolini for the original MacOS port idea.

Technical References

• Autoresearch: github.com/karpathy/autoresearch - Andrej Karpathy's original project
• ANE Project: github.com/maderix/ANE - Reverse-engineered Apple Neural Engine performance
• MacOS Port: github.com/miolini/autoresearch-macos - Original MacOS implementation

The project represents an experimental approach to hardware utilization optimization, with the expectation that performance will improve as the underlying ANE project matures. This is particularly relevant for developers working on Apple silicon hardware who want to maximize local inference efficiency.