Natural Language Processing (NLP) is an AI field that enables computers to interact with human language. NLP applications are diverse: chatbots and virtual assistants provide customer support and recommendations, sentiment analysis monitors social media and customer sentiment, and NLP powers language translation for global communication. NLP's impact is far-reaching, facilitating efficient language processing and enhancing various aspects of human-computer interaction. 

Machine vision AI utilizes AI and computer vision techniques to interpret visual data. It finds applications in object detection, quality control, facial recognition, gesture recognition, medical imaging analysis, and agriculture. By automating tasks such as object recognition, defect detection, and facial authentication, machine vision AI improves efficiency and decision-making in various industries.

Optimization AI leverages AI techniques to efficiently solve complex optimization problems in areas like supply chain management, resource allocation, and production planning. It improves efficiency, minimizes costs, and enhances decision-making processes. 

Structured data AI applications in data science involve using AI techniques to analyze structured datasets. It enables predictive analytics, customer segmentation, fraud detection, risk assessment, process optimization, recommender systems, and health monitoring. By deriving insights from structured data, these applications enhance decision-making and improve efficiency in diverse domains.

Reinforcement Learning (RL) AI applications include training intelligent agents to excel in complex games, developing robots for real-world tasks, and teaching autonomous vehicles to make effective decisions for safety and efficiency. RL's ability to learn from interaction with the environment enables it to optimize behavior in various domains, from healthcare to finance and resource management.