RAI

RAI, or Residual Artificial Intelligence, generally refers to AI systems designed to continue functioning and providing useful outputs even after the original training or deployment phase has ended. It involves maintaining, updating, or adapting AI models in real-world environments with minimal human intervention. This ensures the AI remains relevant, accurate, and effective over time, accommodating new data, changing conditions, or tasks. In essence, RAI emphasizes sustaining AI system performance sustainably and efficiently in dynamic settings.