SmartAI: Enhancing Scene Understanding by Combining Different AI Technologies

Abstract

This paper introduces SmartAI, a novel framework that integrates Machine Learning (ML) and Knowledge Representation and Reasoning (KRR) to enhance AI capabilities in reasoning and adaptability. Inspired by Daniel Kahneman's Thinking, Fast and Slow theory, SmartAI leverages ML for rapid, intuitive processing (System 1) and KRR for deliberate, analytical reasoning (System 2). The framework emphasizes modularity, enabling seamless orchestration of these technologies without altering their core components. A case study on scene understanding demonstrates SmartAI's effectiveness in combining fast pattern recognition with in-depth contextual reasoning, achieving superior interpretive outcomes. Beyond scene understanding, SmartAI lays the foundation for context-aware AI applications in diverse fields such as healthcare, education, and autonomous systems. This work sets a precedent for integrating specialized AI technologies to achieve human-like cognitive flexibility. However, it introduces new challenges in effectively managing and orchestrating interactions between these complementary technologies, opening avenues for future research.

Keywords: Machine Learning, Knowledge Representation and Reasoning, scene understanding, semantic networks

DOI: 10.54941/ahfe1005968