ChatGPT is based on the GPT (Generative Pre-trained Transformer) architecture, which is a part of a broader family of AI models known as transformers. It became very popular in late 2022, it is widely used in customer service to automate responses, in education for tutoring, and in gaming for developing interactive narratives.

In terms of AI core concepts, ChatGPT falls under several categories:

• Deep Learning: GPT models, including ChatGPT, are built using deep learning techniques. They utilize multiple layers in their neural network architecture to understand and generate human-like text based on the patterns they’ve been trained on.
• Natural Language Processing (NLP): ChatGPT’s primary function is understanding and generating human language, which places it squarely within the domain of NLP. It can comprehend context, generate coherent responses, and even emulate different writing styles.
• Generative AI: GPT models are generative in nature. They can generate entirely new, coherent, and contextually relevant text based on the input they receive. This is why they’re effective for tasks like conversation, content creation, and more.

• Transfer Learning (specific to “pre-trained” in GPT): GPT models are “pre-trained” on massive datasets to understand language patterns, context, and semantics. Once this pre-training is done, they can be “fine-tuned” on specific tasks, like answering questions or having conversations, using smaller, task-specific datasets. This approach leverages the concept of transfer learning.