GPT
GPT (Generative Pre-trained Transformer) is a series of large language models developed by OpenAI that generate human-quality text. GPT models are trained to predict the next token and can perform a wide range of language tasks.
Understanding GPT
GPT (Generative Pre-trained Transformer) is a family of large language models developed by OpenAI that have become synonymous with the generative AI revolution. Starting with GPT-1 and scaling dramatically through GPT-2, GPT-3, and GPT-4, these models demonstrated that transformer architectures pre-trained on massive text corpora can perform a remarkable range of natural language processing tasks with minimal fine-tuning or through few-shot learning via prompting alone. GPT models generate text autoregressively, predicting the next token based on context, and have been applied to chatbots, content creation, code generation, translation, and reasoning tasks. ChatGPT, built on the GPT architecture with reinforcement learning from human feedback, brought AI to mainstream adoption. The GPT series competes with models like Google's Gemini and open-source alternatives, driving innovation in foundation model capabilities, alignment research, and embedding-based applications.
Category
Generative AI
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Chain of Thought
Chain of thought is a prompting technique that encourages large language models to break down complex reasoning into intermediate steps. This approach significantly improves performance on math, logic, and multi-step reasoning tasks.
ChatGPT
ChatGPT is an AI chatbot developed by OpenAI that uses large language models to generate human-like conversational responses. It became one of the fastest-growing consumer applications in history after its launch in November 2022.
Claude
Claude is an AI assistant developed by Anthropic, designed to be helpful, harmless, and honest. It is built using Constitutional AI techniques and competes with models like GPT-4 and Gemini.
Diffusion Model
A diffusion model is a generative AI model that creates data by learning to reverse a gradual noise-adding process. Diffusion models power state-of-the-art image generation systems like Stable Diffusion and DALL-E.
Discriminator
A discriminator is the component of a GAN that learns to distinguish between real and generated data. It provides feedback to the generator, creating an adversarial training dynamic that improves output quality.
Few-Shot Prompting
Few-shot prompting provides a language model with a small number of input-output examples in the prompt to demonstrate the desired task format. This technique helps models understand task requirements without any fine-tuning.
Foundation Model
A foundation model is a large AI model trained on broad data that can be adapted to a wide range of downstream tasks. GPT-4, Claude, Gemini, and DALL-E are examples of foundation models that serve as bases for specialized applications.
GAN
A GAN (Generative Adversarial Network) is a generative model consisting of two competing neural networks — a generator and a discriminator. GANs produce realistic synthetic data by training these networks in an adversarial game.