AI Glossary (A-Z)
A-C
- Algorithm
Definition: A set of rules or instructions for solving a problem or performing a task.
Example: A recommendation algorithm that suggests products based on user preferences, like how Netflix suggests movies. - Artificial Intelligence (AI)
Definition: The simulation of human intelligence processes by machines, especially computer systems.
Example: Siri and Alexa are examples of AI that perform tasks like voice recognition and answering questions. - Artificial Neural Network (ANN)
Definition: A network of artificial neurons used in machine learning to model complex patterns and relationships.
Example: Image recognition systems, like those used in Facebook for tagging photos, use neural networks. - Big Data
Definition: Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations.
Example: Social media platforms analyze big data to understand user behavior and improve engagement. - Chatbot
Definition: An AI-powered software that can simulate conversation with users via text or voice.
Example: Customer service chatbots on websites that help answer customer queries. - Clustering
Definition: A machine learning technique that groups similar data points together based on certain characteristics.
Example: Grouping customers by purchasing behavior to personalize marketing. - Convolutional Neural Network (CNN)
Definition: A deep learning algorithm primarily used for analyzing visual imagery.
Example: CNNs are used in facial recognition systems. - Computer Vision
Definition: A field of AI that trains computers to interpret and understand the visual world.
Example: Self-driving cars use computer vision to recognize traffic signs and obstacles.
D-F
- Data Mining
Definition: The process of discovering patterns in large data sets.
Example: Retailers use data mining to discover purchasing trends from customer data. - Deep Learning
Definition: A subset of machine learning involving neural networks with many layers, allowing for more complex models.
Example: Deep learning is used in voice recognition technologies like Google Assistant. - Decision Tree
Definition: A tree-like model used to make decisions or predictions based on a set of rules.
Example: A decision tree can predict loan approval by considering factors like income, credit score, and loan amount. - Fuzzy Logic
Definition: A form of logic used to handle uncertainty and imprecision by considering all possible values between 0 and 1.
Example: A temperature control system that adjusts settings based on varying degrees of “hot” or “cold.” - Feature Extraction
Definition: The process of transforming raw data into usable features for machine learning models.
Example: Extracting edges and shapes from an image before feeding it to a computer vision model. - Federated Learning
Definition: A decentralized machine learning approach where models are trained across multiple devices without sharing raw data.
Example: Google uses federated learning to improve keyboard suggestions on mobile devices while keeping data private.
G-I
- Generative Adversarial Network (GAN)
Definition: A deep learning model that consists of two networks, a generator and a discriminator, that compete to create new data.
Example: GANs are used to generate realistic images, like creating deepfake videos. - Gradient Descent
Definition: An optimization algorithm used in machine learning to minimize a cost function.
Example: Gradient descent is used to adjust weights in a neural network during training. - Hybrid AI
Definition: The combination of multiple AI techniques, such as machine learning and symbolic AI, to solve complex problems.
Example: Hybrid AI is used in advanced robotics to combine learning-based actions with logical reasoning. - Inference
Definition: The process of making predictions based on a trained machine learning model.
Example: A trained AI model for medical image analysis performs inference to diagnose diseases from X-rays. - Intelligent Agent
Definition: An AI system that can perceive its environment and take actions to maximize its chances of achieving a goal.
Example: A personal assistant like Google Assistant is an intelligent agent that can set reminders, answer questions, and control devices.
J-L
- Knowledge Representation
Definition: A field of AI concerned with how to represent information about the world in a form that a computer system can use to solve complex tasks.
Example: Ontologies used in AI systems to represent relationships between concepts, such as “dog” and “animal.” - LSTM (Long Short-Term Memory)
Definition: A type of recurrent neural network (RNN) designed to avoid the vanishing gradient problem, commonly used in sequence data.
Example: LSTMs are used for natural language processing tasks like text generation. - Logic Programming
Definition: A programming paradigm based on formal logic, used for knowledge representation and reasoning in AI.
Example: Prolog is a language often used in AI for logical reasoning and expert systems.
M-O
- Machine Learning (ML)
Definition: A subset of AI where systems learn patterns from data and improve their performance over time without explicit programming.
Example: A spam filter learning to identify junk emails based on historical data. - Model Training
Definition: The process of teaching a machine learning model using data so that it can make accurate predictions.
Example: Training a neural network on labeled images of cats and dogs to classify new images. - Natural Language Processing (NLP)
Definition: A field of AI that focuses on enabling computers to understand, interpret, and generate human language.
Example: Chatbots and voice assistants like Siri use NLP to process user input and generate responses. - Overfitting
Definition: A modeling error that occurs when a machine learning model learns the details of the training data too well, causing it to perform poorly on new, unseen data.
Example: A model that memorizes specific data points rather than learning general patterns will struggle with new inputs.
P-S
- Predictive Analytics
Definition: The use of statistical algorithms and machine learning techniques to identify the likelihood of future outcomes.
Example: Retailers use predictive analytics to forecast future sales based on past purchasing trends. - Reinforcement Learning
Definition: A type of machine learning where agents learn to make decisions by receiving rewards or penalties for actions taken.
Example: In video game AI, reinforcement learning allows characters to improve performance by learning from their actions. - Robot Process Automation (RPA)
Definition: The use of AI to automate repetitive tasks or business processes, often using software robots.
Example: RPA can automate tasks like data entry in accounting systems. - Supervised Learning
Definition: A machine learning technique where models are trained on labeled data to make predictions.
Example: Spam detection in emails, where labeled examples of spam and non-spam emails are used to train the model.
T-Z
- TensorFlow
Definition: An open-source machine learning framework developed by Google that allows for building and deploying AI models.
Example: TensorFlow is widely used for tasks such as image classification, speech recognition, and natural language processing. - Turing Test
Definition: A test for determining whether a machine can exhibit intelligent behavior indistinguishable from that of a human.
Example: If a computer can hold a conversation with a human without the human realizing it’s not another person, it passes the Turing test. - Unsupervised Learning
Definition: A machine learning technique where models learn from data without labeled responses, identifying patterns or structures.
Example: Clustering customer data to identify groups with similar buying behavior. - Vision AI
Definition: A subset of AI that enables machines to interpret and make decisions based on visual data, often used in image recognition and computer vision tasks.
Example: Vision AI is used in quality control systems in manufacturing to identify defects in products. - Token
Definition: A unit of input to a model, such as a word or character, that a language model processes.
Example: In language models, the sentence “I love AI” might be broken down into tokens like “I”, “love”, and “AI”. - LLM (Large Language Model)
Definition: A type of AI model that uses deep learning techniques to understand, generate, and translate human language by processing vast amounts of text data.
Example: GPT-4 is a powerful LLM that can generate text, answer questions, and perform complex language-related tasks. - Retriever
Definition: A component in AI systems that searches large datasets or knowledge bases to find relevant information based on a query.
Example: In a question-answering system, the retriever finds the most relevant documents or passages to answer a user’s question. - Embeddings
Definition: A method of representing words, phrases, or other data in a continuous vector space, allowing models to understand the relationships between them.
Example: Word embeddings like Word2Vec map words with similar meanings to nearby points in the vector space. - Model
Definition: A mathematical or computational representation of a system that learns from data to make predictions or decisions.
Example: A machine learning model might predict house prices based on features like square footage, location, and condition. - Vector
Definition: An array or list of numbers used to represent data in machine learning, particularly in the context of embeddings.
Example: A vector might represent a word or document in a way that captures its meaning or content for use in a machine learning model.
