Perplexity functions as an answer engine that uses AI language models like GPT-4 to summarize information collected by browsing the web. It retrieves relevant links, reads paragraphs, and generates concise answers for user queries. The system, known as retrieval augmented generation (RAG), aims to provide accurate information sourced from the web. Although perplexity minimizes hallucinations, it can still produce incorrect answers due to imperfections in the AI model. This raises concerns about the reliability and accuracy of AI search engines in providing correct responses to user inquiries.