GPT, or Generative Pre-trained Transformer, is an AI model developed by OpenAI that has revolutionized natural language processing. It is based on a deep learning architecture called Transformers, which excels at processing sequential data like text.
Here’s how GPT works:
- Pre-training: GPT is pre-trained on a large corpus of text data from the internet, such as books, articles, and websites. During this phase, the model learns the relationships between words, phrases, and context.
- Fine-tuning: Once pre-training is complete, GPT can be fine-tuned on specific tasks, datasets, or domains to improve its performance for a particular application.
- Generation: When given a prompt or input text, GPT generates a response by predicting the next word based on the context provided. It uses a technique called autoregressive generation to produce coherent and contextually relevant output.
- Attention mechanism: GPT utilizes an attention mechanism to focus on relevant parts of the input text when generating output. This allows the model to capture long-range dependencies and produce high-quality responses.
