OpenAI Glossary

Every important OpenAI term explained.


Artificial Intelligence (AI)

A computer science field dedicated to developing intelligent machines capable of human-like thought processes.

Artificial General Intelligence (AGI)

A form of AI exhibiting broad, human-like intelligence, capable of learning and understanding diverse tasks and solving problems across various domains.

Application Programming Interface (API)

A framework of rules and tools for building software applications, acting as an intermediary to enable different software programs to interact seamlessly.

API Keys

Unique identifiers provided to users to access a service’s API, ensuring secure and controlled usage.

Assistants API

A specialized API that allows the integration of AI functionalities into applications, enabling interactive features like chatting and question-answering.

AI Safety

The practice of ensuring AI systems are safe and beneficial for human use.

AI Regulation

The set of rules and guidelines governing the application and deployment of AI technology.

AI Policy and Governance

The process of formulating rules and policies to guide AI development and application.

Autoregressive Models

Predictive tools in AI that analyze past data to forecast future events.


Bias in AI

The phenomenon where AI systems exhibit unfairness due to learning from biased data.



A specialized version of the GPT model excelling in conversational interactions and responses.

ChatGPT Plugins

Software enhancements that add real-time chat capabilities to websites or applications, facilitating user interaction and automated responses.

Computer Vision

An AI domain where computers are trained to interpret and understand visual data from images and videos.



An AI tool that generates visual images from textual descriptions, functioning like a digital artist.


An enhanced version of DALL·E capable of creating more realistic and detailed images from text.


A further advanced version of DALL·E, specializing in producing highly accurate and detailed images.

Data Privacy in AI

The practice of ensuring personal information remains secure and private within AI systems.


A compilation of data used for training or evaluating AI models.

Deep Learning (DL)

An advanced machine learning technique utilizing layered neural networks to learn complex patterns.


Ethics in AI

The application of moral principles and values in the creation and use of AI technologies.


Federated Learning

A decentralized approach to AI training where learning occurs across multiple devices or systems.

Few-Shot Learning

An AI’s ability to learn and adapt from a limited amount of labeled data.


The process of refining an AI model, often by training it on a specific dataset, to enhance its performance.

Fraud Detection

The use of AI in identifying and preventing fraudulent activities.


Generative Pre-trained Transformer (GPT)

An AI model proficient in language processing, capable of generating human-like text.

GPT base

The foundational architecture and model underpinning the GPT series, known for its text generation and language processing capabilities.


The third iteration of the GPT series, noted for its size and versatility in language processing.


An advanced version of GPT-3, offering improved language understanding and generation.


A more sophisticated and larger version of the GPT model, succeeding GPT-3.


Language Models

AI tools designed for processing, understanding, and generating human language.


Machine Learning (ML)

A subset of AI where computers enhance their performance by learning from large datasets.

Model Training

The process of teaching an AI model to perform specific tasks or make predictions.


The practice of overseeing and managing user-generated content on digital platforms to ensure compliance with set standards.


Natural Language Processing (NLP)

An AI field focused on enabling computers to understand and communicate in human language.

Neural Networks

Computational models that mimic the human brain’s structure, aiding machines in pattern recognition and decision-making.



A research organization dedicated to creating innovative AI technologies with a commitment to ensuring their beneficial use.


A tool provided by OpenAI that allows developers to incorporate advanced AI models into their applications.



Instructions or queries given to an AI model to elicit specific responses or outputs.

Prompt Engineering

The craft of designing prompts to guide AI, particularly language models, towards desired outputs.


Reinforcement Learning

A machine learning approach where an agent learns to make decisions through trial and error in a given environment.


The technological field involving the design, construction, and operation of robots capable of performing autonomous or semi-autonomous tasks.

Rate limits

Restrictions set on the frequency of data requests a user or application can make to a server or API, ensuring equitable resource usage.


Scalability in AI

The capacity of an AI system to handle increased workloads or expand to accommodate growth.

Software Bugs

Errors or faults in computer programs that lead to incorrect or unexpected outcomes.

Supervised Learning

A machine learning paradigm where algorithms are trained using labeled data.

Synthetic Media

Media content generated or altered by AI, often indistinguishable from human-created content.


Text-to-Image Generation

The AI-driven process of creating visual images from textual descriptions.

Text-to-Speech (TTS)

A technology that converts written text into audible speech, enabling computers to read aloud.


In NLP, the process of breaking down text into smaller, analyzable units such as words.

Transfer Learning

The practice of applying a model trained for one task to a different but related task.

Transformer Models

A novel neural network architecture introduced for enhancing language understanding and generation.


Unsupervised Learning

A machine learning technique where algorithms learn from unlabeled data, identifying patterns without explicit guidance.



An AI tool that converts spoken language into written text, effective in various accents and noisy environments.


Zero-Shot Learning

An AI’s ability to recognize and understand new concepts it has not been explicitly trained on, useful in scenarios with limited data availability.