By Prakash Pandey | Data & AI Expert | Agile Leader | GenAI Evangelist
As GenAI rapidly reshapes how we work, it's crucial to grasp the foundational terms that drive this revolution. Whether you're a techie, a business leader, or just GenAI-curious — this guide gives you the clarity you need.
Here are 12 essential Generative AI terms simplified for everyone:
LLM (Large Language Model) – The brain of GenAI tools, trained on massive datasets to understand and generate text like a human.
Transformers – The neural network architecture powering LLMs with self-attention for deep language understanding.
Prompt Engineering – The art of crafting instructions to get accurate, contextual responses from AI models.
Fine-Tuning – Customizing pre-trained models for specific domains for better precision.
Embeddings – Numeric representations of text/images that help in comparison and semantic understanding.
RAG (Retrieval-Augmented Generation) – Merges search with generation to produce accurate, grounded answers.
Tokens – The smallest unit of input text (words or subwords) that models process.
Hallucination – When AI makes things up — plausible but false information.
Zero-shot – AI performing tasks with no prior examples, using general intelligence.
Chain-of-Thought – Prompting technique that encourages step-by-step logical reasoning.
Context Window – The amount of input text an AI can “see” at once.
Temperature – A setting that controls how creative or focused the AI’s responses are.
These terms aren't just buzzwords — they're building blocks for anyone working with or alongside GenAI.
Let’s keep learning, experimenting, and transforming together.
Which of these terms was new to you? Drop it in the comments!
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