How does real-time search, when enabled, alter ChatGPT's answer-generation strategy compared to using its internal knowledge base?

When real-time search is enabled, ChatGPT's answer-generation strategy shifts from primarily relying on its internal knowledge base to incorporating dynamically retrieved information from the web. This alters several key aspects of the response. Using only the internal knowledge base, ChatGPT formulates answers based on the data it was trained on, leading to responses that reflect the knowledge and biases present in that training data. When real-time search is enabled, ChatGPT first queries the web for relevant information based on the user's prompt. This allows it to access up-to-date information that may not be present in its internal knowledge base. The model then integrates this real-time information into its responses, supplementing or even overriding information from its internal knowledge base. The source of information becomes more varied, including news articles, blog posts, and other web content. The responses become more timely and reflect current events or trends. The criteria for determining credibility are broadened to include factors like website authority, recency, and user engagement metrics. Therefore, real-time search enables ChatGPT to provide more current and comprehensive answers, but it also introduces the risk of incorporating misinformation or biased information from unreliable sources.