AI Basics
This is the technology that enables computers to think, learn and solve problems.
Artificial Intelligence
This is a way for computers to learn from data without being explicitly programmed for every task.
Machine Learning
This AI can create new content such as text, images, music or code.
Generative AI
This is a computer system inspired by the human brain.
Neural Network
This structure consists of nodes connected by edges and can be used to represent relationships and paths.
Graph
This is information collected and used by computers.
Data
This is the data used to teach an AI system how to learn and make predictions.
Training Data
This AI model is trained on a large amount of text to understand and generate human language.
Large Language Model(LLM)
This AI can identify and understand objects, people or scenes in images.
Image Recognition
This machine-learning method is used to predict continuous values such as prices or temperatures.
Regression
This is a set of steps or rules used to solve a problem.
Algorithm
In this type of learning, the model is trained using labelled data with known answers.
Supervised Learning
This is the skill of writing clear instructions to get better results from an AI system.
Prompt Engineering
This AI can understand and interpret images or videos.
Computer vision
This algorithm finds the shortest path using heuristics, including an estimate of the distance to the goal.
A* Algorithm
Give the AI one of these when you type a question or instruction into an AI tool.
Prompt
In this type of learning, the system searches for patterns without labelled answers.
Unsupervised Learning
This AI field helps computers understand, interpret and generate human language.
Natural Language Processing(NLP)
This type of machine learning uses many layers of neural networks.
Deep Learning
This algorithm finds the shortest path between nodes in a graph.
Dijkstra's Algorithm
This computer program is designed to communicate with people through conversation.
Chatbot
In this type of machine learning, an agent learns through trial and error and receives rewards for good actions.
Reinforcement learning
AI gives you an answer that sounds believable, but the information is actually wrong or made up. What is this called?
Hallucination
This computing system is inspired by the human brain and consists of layers of connected nodes, or neurons.
Artificial Neural Network (ANN)
This is the process of training a neural network by adjusting weights to reduce errors.
Backpropagation