Rick Jacobs explores the integration of OpenAI's ChatGPT with Apache Druid to create a sentiment analysis application capable of processing large datasets in real-time. Leveraging the natural language processing capabilities of ChatGPT, particularly its advanced models like GPT-3 and GPT-4, the application can accurately analyze sentiments from vast sources like social media. Apache Druid, known for its high-performance analytics on large volumes of data, complements ChatGPT by enabling efficient querying and visualization of sentiment data. This integration allows businesses to make quick, data-driven decisions based on real-time insights into customer feedback or market trends. Jacobs outlines a four-step process involving data gathering through Twitter's API, sentiment determination using ChatGPT, data ingestion into Druid, and visualization of results. He emphasizes the scalability and speed of Druid, particularly in environments requiring rapid analysis of streaming data, and suggests potential applications across various domains such as customer feedback analysis, brand monitoring, political analysis, social media marketing, and crisis management.