ChatGPT learns from massive text datasets to understand language patterns and context. 

Built on a transformer-based neural network, it processes and generates human-like text. 

ChatGPT analyzes your prompt or your input to grasp intent, context, and specific details. 

ChatGPT breaks sentences into smaller chunks to process and generate responses. 

ChatGPT uses the conversation history to provide contextually relevant answers of questions. 

The model predicts the most likely next word in a sentence to generate coherent responses. 

Developers refine the model using feedback and specific use cases for better performance. 

Parameters control the balance between creative responses and factual accuracy. 

ChatGPT has protections to avoid inappropriate replies but may still have knowledge gaps. 

Ongoing updates improve ChatGPT’s performance, making it helpful and relevant.