AI Glossary
Master the language of artificial intelligence. From RAG to Transformers, understand the terms that shape modern AI tools.
📚 21 terms defined • Updated January 2026
Written for humans,
by AI enthusiasts
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A 2 terms
Agentic AI
🟡AI systems that can autonomously plan, make decisions, and take actions to accomplish goals with minimal human intervention—the next evolution beyond chatbots.
API (Application Programming Interface)
🟢A set of rules and protocols that allows software applications to communicate with AI services, enabling developers to integrate AI capabilities into their products.
C 1 term
E 1 term
F 2 terms
Fine-Tuning
🟡The process of further training a pre-trained AI model on specific data to customize its behavior, knowledge, or style for particular use cases.
Foundation Model
🟡A large AI model trained on broad data that can be adapted to many tasks—the base layer upon which specialized AI applications are built.
H 1 term
I 1 term
K 1 term
L 2 terms
Latency
🟢The time delay between sending a request to an AI system and receiving the response—critical for real-time applications and user experience.
LLM (Large Language Model)
🟢An AI system trained on massive amounts of text data that can understand, generate, and manipulate human language for tasks like writing, coding, and conversation.
M 1 term
O 1 term
P 1 term
R 2 terms
RAG (Retrieval-Augmented Generation)
🟡A technique that enhances AI responses by retrieving relevant information from external documents before generating an answer, reducing hallucinations and enabling real-time knowledge access.
RLHF (Reinforcement Learning from Human Feedback)
🔴A training technique that uses human preferences to fine-tune AI models, teaching them to generate responses that humans find helpful, harmless, and honest.
S 1 term
T 3 terms
Temperature
🟢A parameter that controls the randomness and creativity of AI outputs—lower values produce more predictable responses, while higher values increase creativity and variation.
Tokens
🟢The basic units of text that AI models process—typically word pieces or characters. Token count determines pricing, speed, and context limits in AI tools.
Transformer
🟡The neural network architecture that powers modern AI language models, using 'attention' mechanisms to understand relationships between all words in a text simultaneously.