LAYA RUNS 45 DECISIONS/SEC ON MAC M4 OFFLINE

Laya brings on-device machine learning inference to Mac M4 processors through CoreML optimization. The open-source project demonstrates practical performance for offline AI applications, executing 45 decision cycles per second without cloud dependencies. The implementation leverages Apple's CoreML framework to compile models for native execution on M4 silicon. This approach reduces latency and eliminates reliance on external servers, making it suitable for privacy-sensitive applications. The technical details were shared via a GitHub gist by developer fordnox, generating discussion on Hacker News where the post accumulated 110 points and 21 comments. The broader Laya project announcement earlier gained 210 points across 33 comments. The release underscores growing interest in edge AI for consumer hardware. Running inference locally on M4 chips enables developers to build responsive applications without network overhead or cloud infrastructure costs.