Glossary

AI-driven instruction that adjusts content, difficulty, and pace based on each student’s performance and needs.

The use of AI to collect, process, and analyze data provides insights to optimize operations, marketing, or decision-making.

A system that combines algorithms, neural networks, and ML to deliver personalized, interactive outputs such as recommendations or insights.

Guiding principles to ensure responsible and fair integration of AI in classrooms, prioritizing transparency and student well-being.

The use of AI technologies to enhance learning, instruction, and educational administration.

The knowledge and skills needed to understand, use, and critically evaluate AI tools and technologies.

Software that rewrites or rephrases text automatically, often used for academic or content creation purposes.

AI software that supports sales tasks like lead scoring, meeting scheduling, and customer follow-up.

A system of AI-driven agents performing tasks traditionally done by humans, improving scalability and efficiency.

Using AI to tailor content, services, or experiences to individual users, increasing relevance and engagement.

Tools that automate marketing workflows, analyze data, and generate personalized campaigns.

Systems that adapt to student progress and deliver tailored instruction and support.

AI for IT Operations—automates infrastructure monitoring, issue detection, and system optimization.

A specific set of rules or instructions followed by a computer to perform tasks or solve problems.

A theoretical form of AI that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks at a human-like level of intelligence.

The simulation of human intelligence processes by machines, especially computer systems. AI encompasses reasoning, learning, perception, problem-solving, and language understanding, aiming to perform tasks that typically require human intelligence.

A hypothetical AI that surpasses human intelligence across all fields, including creativity, problem-solving, and social intelligence.

AI that automates grading, feedback, and evaluation to improve consistency and efficiency.

Technology that overlays digital content onto the real world, enhancing visual perception.

Automated Machine Learning processes that simplify model training and deployment.

An AI system’s ability to operate independently without human input.

A training method in neural networks that adjusts model weights based on errors.

A technique that normalizes layer inputs in neural networks, improving performance and stability.

A probabilistic approach to problem-solving using Bayesian inference.

Large datasets that require advanced tools to process and analyze for insights.

Automated software that performs routine tasks, often used in chat, scheduling, or support roles.

Systems and tools that collect and analyze business data for strategic decisions.

A conversational large language model (LLM) by OpenAI capable of generating human-like responses.

An AI model connecting images and text, enabling image captioning and visual understanding.

AI systems that simulate human thinking to aid in decisions, analytics, or automation.

Combining multiple AI techniques (e.g., NLP + ML) to create more powerful systems.

AI designed to engage in conversations with users, often employed in virtual agents or voice assistants.

A neural network model optimized for image and visual data recognition.

Software enhanced with AI to optimize sales, service, and customer experience.

The process of increasing the diversity and amount of training data by creating modified versions of existing data, improving model robustness.

Analyzing large datasets using AI to discover patterns, relationships, and trends that inform business strategy.

A multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract insights from structured and unstructured data.

Deep learning is a subfield of machine learning that mimics how the human brain processes information.

Synthetic media created using AI, particularly deep learning, to produce highly realistic but fake images, audio, or video.

A Chinese AI company known for developing open-source large language models capable of coding, content generation, and multilingual understanding.

AI systems designed for large-scale business operations, integrating with enterprise software (like CRM or ERP) to support decision-making and workflow automation.

AI systems that monitor transactions and behaviors to identify potential fraud in real time, protecting business assets and customers.

AI systems that generate new content—such as text, images, or audio—by learning patterns from large datasets.

Analyzing student data to personalize learning paths, identify gaps, and improve educational outcomes.

A powerful AI model trained on vast text data to generate human-like text.

A broad term encompassing various AI learning algorithms, including machine learning and deep learning.

A subset of AI focused on developing algorithms that allow computers to learn from and make predictions or decisions based on data, without being explicitly programmed.

The branch of AI that enables machines to understand and generate human language.

A computational model inspired by how the human brain processes information.

An artificial intelligence research organization and company founded in 2015, responsible for developing cutting-edge AI models such as GPT, DALL·E, and Codex.

AI techniques that analyze historical data to forecast future trends, customer behavior, or market shifts, supporting proactive business decisions.

AI-driven tools that suggest products or services based on customer behavior, preferences, and purchase history, increasing sales and engagement.

AI models that adjust instructional content based on student behavior and performance.

AI software that automates highly repetitive, rule-based business processes, such as data entry or invoice processing.

AI tools that analyze customer feedback, reviews, or social media to gauge public sentiment and brand perception.

A machine learning approach where models are trained on labeled data, learning to map inputs to known outputs.

Instruction focused on AI fundamentals, ethics, and its role in society.

Equipping learners with the mindset and skills needed to thrive in an AI-augmented world.

Incorporating AI tools into instruction to support engagement and automate tasks.

The datasets used to teach AI models in educational applications such as student essays for automated grading or language samples for translation tools.

A technique where a model developed for one task is reused as the starting point for a model on a second task.

A test proposed by Alan Turing to determine whether a machine can exhibit intelligent behavior indistinguishable from that of a human.

A machine learning approach where models find patterns or groupings in data without labeled outputs.

AI-driven software that performs tasks or services for users, such as scheduling, answering queries, or managing emails, often used by business professionals.

An AI tool that helps students manage coursework through reminders, study suggestions, and performance insights.

Improves grammar, style, and clarity with AI-powered writing suggestions.