Hybrid AI is an approach that combines different artificial intelligence techniques, models, or systems to solve problems more effectively. It may integrate machine learning with rule-based reasoning, symbolic AI, natural language processing, computer vision, or human expertise. By combining complementary capabilities, Hybrid AI can handle tasks that require both pattern recognition and logical reasoning, producing more adaptable and reliable results.
Hybrid AI is commonly used in healthcare, finance, robotics, cybersecurity, manufacturing, and decision-support systems. Its purpose is to combine the strengths of different approaches while reducing their individual limitations. For example, machine learning can identify patterns in large datasets, while rule-based systems can apply defined conditions or constraints. This combination can improve accuracy, explainability, flexibility, and decision-making in complex real-world applications.
