GPT (Generative Pre-trained Transformer)
A family of language models that generate human-like text using transformer architecture.
Detailed Definition
GPT (Generative Pre-trained Transformer) is a family of large language models developed by OpenAI that has fundamentally changed the landscape of natural language processing and AI applications. GPT models use the transformer architecture and are trained through a two-stage process: pre-training on vast amounts of text data to learn language patterns, followed by fine-tuning for specific tasks. The 'generative' aspect means these models can produce coherent, contextually relevant text, while 'pre-trained' indicates they've learned general language understanding before being adapted for specific applications. The GPT series has evolved from GPT-1 through GPT-4, with each iteration showing dramatic improvements in capability, reasoning, and versatility. GPT models power various applications including ChatGPT, content generation tools, coding assistants, and educational platforms. Their ability to understand and generate human-like text has made them invaluable for tasks ranging from creative writing to complex problem-solving.
Core TechnologiesMore in this Category
Autoregressive Model
A type of model that predicts the next element in a sequence based on previous elements.
BERT
Bidirectional Encoder Representations from Transformers - a pre-trained language model.
Deep Learning
A subset of machine learning using neural networks with multiple layers to learn complex patterns.
Embedding
A numerical representation of data that captures semantic meaning in a high-dimensional vector space.
Large Language Model (LLM)
AI models with billions of parameters trained on vast text datasets to understand and generate human language.
Neural Network
A computing system inspired by biological neural networks that learns to perform tasks by analyzing examples.