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AI cheat sheet
The important stuff from your two worksheet pages.
🤖 AI & Machine Learning
Artificial Intelligence: Machines performing tasks needing human-like intelligence.
Machine Learning: Learning from data to spot patterns and make decisions.
Algorithm: Step-by-step instructions to solve a problem.
Training: Examples + feedback improve a model.
🧠 Neural Networks
ANN: Connected artificial neurons inspired by the human brain.
Training cycle: Input → Prediction → Error → Adjust weights → Repeat.
Deep Learning: Learning with neural networks that have many layers.
👁️ Vision & Robotics
Computer Vision: Extracting and understanding information from images.
Image Recognition: Identifying objects or features in pictures.
Edge Detection: Finding outlines of objects.
Robotics: Physical hardware + programmed or AI-driven behaviour.
Autonomous: Making decisions with limited human control.
⚖️ Ethics & Safety
Training Bias: Unbalanced data can produce unfair results.
Ethics: Fairness, privacy, jobs and responsibility.
Safety: Reducing the risk of harm caused by AI.
Legal Liability: Who is legally responsible if AI causes harm.
📖 More key words
Chatbot: A program you can talk to.
LLM: Large Language Model; AI trained to process and create language.
Generative AI: Creates content such as text, pictures or songs.
Pattern Recognition: Finding patterns in data.
Self-learning: Improving using experience or feedback.
🌟 Extra test terms
Turing Test: Can a machine imitate human conversation convincingly?
AI Pioneer: Someone who made major contributions to AI; e.g. Alan Turing.
Genetic Algorithm: Inspired by evolution and natural selection.
Two AI characteristics: Learn from data; solve problems/make decisions.