gaow0007/ATSPrivacy

ATSPrivacy is a dormant research repository (last updated over 5 years ago) that attempts to bridge AutoML and Federated Learning. With only 26 stars and zero recent velocity, it functions as a static reference implementation rather than a living project. In the time since this repo was active, the Federated Learning ecosystem has matured significantly with production-grade frameworks like Flower (flwr.dev), OpenMined's PySyft, FedML, and NVIDIA Flare. These projects offer superior documentation, security audits, and hardware acceleration. Furthermore, frontier labs and major platform holders (Google, Apple) have already internalized these capabilities for their own ecosystem (e.g., Gboard's FL, Apple's Private Cloud Compute). The project lacks any defensibility moat—no community, no data gravity, and its technical approach has been superseded by more modern Neural Architecture Search (NAS) and Secure Multi-Party Computation (SMPC) techniques. It is effectively obsolete in the current market.