ABCD of AI Explained in 5 Minutes | ABCD of AI for Beginners | Bhavesh Ki Pathshala

Here’s your, A–Z words of AI with simple one-line explanations A – Agent: AI that can think and act on its own to complete tasks. B – Bias: When AI gives unfair or incorrect results due to bad data. C – Context Window: The amount of text AI can remember at one time. D – Diffusion: A method AI uses to create images from noise step by step. E – Embedding: Turning text into numbers so AI can understand meaning. F – Fine-tuning: Improving an AI model by training it on specific data. G – GPT: A powerful AI model that generates human-like text. H – Hallucination: When AI makes up information that is not true. I – Inference: Using a trained AI model to get answers or predictions. J – Jailbreak: Trying to trick AI into ignoring its safety rules. K – Knowledge Base: A collection of information AI uses to answer questions. L – LLM: A large AI model trained to understand and generate language. M – Multimodal: AI that can understand text, images, audio, and more. N – Neural Net: A system designed like the human brain to process data. O – Open Source: AI models that are free for anyone to use and modify. P – Prompt: The instruction or question you give to AI. Q – Quantization: Making AI models smaller and faster by reducing precision. R – RAG: AI that uses external data to give more accurate answers. S – Supervised Learning: Training AI using data with correct answers. T – Tokens: Small pieces of text that AI reads and processes. U – Unsupervised: AI learning patterns without labeled examples. V – Vector DB: A database that stores data in a way AI can search meaningfully. W – Weights: Values inside AI that help it make decisions. X – XGBoost: A fast algorithm that improves predictions using many small models. Y – YOLO: A real-time system that detects objects in images or videos. Z – Zero-shot: When AI solves a task without being trained on it before.

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