Introducing the revamped project now operating under "GPU Poor Continuous Learning" — a fresh take on intelligent systems designed for resource-conscious environments.

Here's what powers it: a streamlined system-level feedback loop that learns and adapts autonomously, anchored by persistent memory architecture and a hybrid search mechanism. The combination lets the model improve iteratively without demanding excessive computational overhead.

What makes this approach practical? It sidesteps the need for expensive GPU clusters while maintaining learning efficiency through smart memory management and dual-layer search capabilities.

Coded, tested, and ready for deployment — the implementation details and full codebase are available for developers looking to explore lightweight AI systems.