GPT, which stands for Generative Pre-trained Transformer, is a family of large language models developed by OpenAI that use the transformer architecture to generate human-like text. GPT models are pre-trained on enormous datasets of text from the internet, learning grammar, facts, reasoning patterns, and even stylistic nuances, before being fine-tuned for specific applications such as chatbots, content generation, and code assistance.
The "pre-trained" aspect of GPT is key to its effectiveness. During pre-training, the model learns to predict the next word in a sequence across billions of text samples, building a deep statistical understanding of language. This foundation is then adapted through fine-tuning and reinforcement learning from human feedback (RLHF) to produce outputs that are helpful, accurate, and aligned with user intent.
Since the release of GPT-3 and subsequently GPT-4, these models have reshaped how industries approach conversational AI assistants, automated writing tools, programming aids, and enterprise search solutions. GPT's versatility has made the transformer architecture the dominant paradigm in natural language processing, inspiring competing models and pushing rapid progress across the AI field.