A
AI (Artificial Intelligence)
Technology that enables machines to simulate human-like learning, reasoning, and decision-making.
AI Agent
An autonomous system that performs tasks, makes decisions, and adapts to user goals without constant input.
Anthropic
An AI company known for developing the Claude LLM, focused on safety and alignment.
B
Bias
Systematic error in AI results, often caused by unbalanced or non-representative training data.
Business Intelligence (BI)
Use of data analysis tools (often AI-enhanced) to support better business decision-making.
C
ChatGPT
A widely used AI chatbot developed by OpenAI for generating text, answering questions, and more.
Computer Vision
AI that interprets and processes visual inputs like images or video.
Cloud Computing
Using remote servers (e.g. AWS, Azure) to store data and run AI models.
D
DALL·E
An image-generating AI from OpenAI that creates visuals from text prompts.
Data Labeling
Tagging or annotating data so it can be used to train AI models.
Deep Learning
A subfield of machine learning based on neural networks that solves complex problems.
E
Embedding
Numeric vector representation of text, images, or audio that allows AI to compare and process content.
Ethical AI
The practice of building AI systems that are fair, transparent, and aligned with human values.
F
Fine-Tuning
Adapting a pre-trained AI model to perform better on a specific domain or task.
Foundation Model
A large general-purpose model (like GPT or LLaMA) that can be customized for many applications.
G
Generative AI
AI that creates new content such as text, images, code, or audio based on inputs.
GPU (Graphics Processing Unit)
Hardware used to train and run deep learning models efficiently.
H
Hallucination
When an AI generates content that sounds correct but is factually false or made up.
Hugging Face
A popular platform for open-source AI models and tools.
I
Inference
The stage where a trained model is used to generate outputs or predictions.
Integration
Connecting AI systems with tools like CRMs, email, or other software to create seamless workflows.
J / K / L
LangChain
A framework for building AI applications by combining LLMs with tools, APIs, or databases.
LLM (Large Language Model)
AI models trained on massive text datasets to understand and generate human-like language.
M
Model Drift
Decline in model accuracy over time as the data it sees diverges from its training data.
MLOps
The practice of managing and deploying machine learning models in production environments.
Meta LLaMA
A family of open-source LLMs developed by Meta (Facebook).
N
NLP (Natural Language Processing)
The field of AI focused on understanding and generating human language.
Neural Network
The architecture behind deep learning, inspired by the structure of the human brain.
O
OCR (Optical Character Recognition)
AI that reads printed or handwritten text from images or scanned documents.
OpenAI
Leading AI research company behind GPT, ChatGPT, and DALL·E.
P
Prompt Engineering
Crafting effective inputs to guide AI models toward accurate or useful outputs.
Predictive Analytics
Using AI to forecast future trends or behaviors based on past data.
Q / R
RAG (Retrieval-Augmented Generation)
Combines document search with text generation to produce informed AI responses.
S
Scalability
The ability of an AI system to handle more users or data without loss in performance.
Sentiment Analysis
Detecting emotional tone (positive, negative, neutral) in text using AI.
Stable Diffusion
A generative AI model that creates high-quality images from text prompts.
T / U / V
Token
The basic unit of text (word piece or character) that AI models process.
Training
The process of teaching an AI model using large datasets.
Vector Database
Specialized databases optimized for searching vector representations (embeddings) based on similarity.
W / X / Y / Z
Workflow Automation
Using AI to automate repetitive tasks across systems, like email replies or document classification.