AI GLOSSARY
AI Glossary
A comprehensive reference for the most common AI terms and abbreviations, helping you understand reviews, news, and technical documentation.
A
AGI (Artificial General Intelligence)
An AI system capable of performing any intellectual task that a human can. Not yet achieved — it remains the ultimate goal of AI research.
API (Application Programming Interface)
A set of protocols that allows different software systems to communicate. AI APIs let developers integrate AI capabilities into their own applications.
Attention Mechanism
A core component of the Transformer architecture. It allows models to focus on different parts of the input sequence, capturing contextual relationships.
C
Context Window
The maximum amount of text (measured in tokens) a language model can process in a single interaction. Larger windows allow processing of longer documents.
Claude
A family of large language models developed by Anthropic, known for safety, long-context handling, and strong reasoning. Competes directly with ChatGPT.
F
Fine-tuning
Further training a pre-trained model on domain-specific data to improve performance on targeted tasks.
Foundation Model
A large AI model trained on massive datasets that serves as the base for downstream tasks. GPT-5, Claude, and Gemini are all foundation models.
G
GPT (Generative Pre-trained Transformer)
A series of language models developed by OpenAI. GPT-4 and GPT-5 are among the most widely used AI models in the world.
Generative AI
AI systems that can generate new content — text, images, audio, or video. Emphasizes creative capability, unlike traditional analytical AI.
L
LLM (Large Language Model)
An AI model trained on massive amounts of text data, capable of understanding and generating human language. ChatGPT and Claude are both built on LLMs.
Latency
The time it takes for an AI model to return its first token after receiving a request. Low latency is especially important for real-time chat applications.
M
Multimodal
AI models that can process multiple types of input (text, images, audio, video). GPT-5 and Gemini are both multimodal models.
P
Prompt
The instruction or question you give to an AI model. High-quality prompts significantly improve the relevance and quality of AI outputs.
Prompt Engineering
The practice of designing and optimizing prompts to get better AI outputs. Good prompt engineering can dramatically increase productivity.
R
RAG (Retrieval-Augmented Generation)
A technique combining external knowledge retrieval with LLM generation, allowing models to answer questions beyond their training data while reducing hallucinations.
T
Token
The smallest unit of text processed by a language model — typically a word or a few characters. Pricing and context limits are usually measured in tokens.
Transformer
A deep learning architecture introduced by Google in 2017, now the foundation of all major LLMs. The “T” in GPT stands for Transformer.