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AI Terms Glossary

The key AI terms that keep showing up in the news, explained in plain language.

Basic Concepts

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Artificial Intelligence (AI)

Explanation

The broadest term for technology that reproduces human learning, reasoning, and problem-solving abilities in computers. Machine learning and deep learning are the leading approaches used to build it.

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Machine Learning

Explanation

A core AI approach in which a system learns from large amounts of data to find patterns and make predictions on its own, instead of following rules programmed by hand.

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Deep Learning

Explanation

A machine learning technique that stacks many layers of artificial neural networks modeled on the human brain, dramatically improving performance in areas like image recognition and natural language processing.

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Algorithm

Explanation

A step-by-step procedure or set of rules for solving a problem. In AI, it refers to the specific computational method used to learn from data and make predictions.

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Training Data (Dataset)

Explanation

The large collection of data an AI model uses to learn patterns. The quantity and quality of this data is one of the biggest factors determining how well an AI performs.

Generative AI

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Generative AI

Explanation

AI that learns from existing data to create entirely new content β€” text, images, music, video, and more. ChatGPT and image-generation AI are well-known examples.

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Large Language Model (LLM)

Explanation

A massive AI language model trained on huge amounts of text data, capable of holding natural conversations and writing text much like a human.

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Prompt

Explanation

The instruction or question you enter to get a desired output from generative AI. The skill of crafting effective prompts is called "prompt engineering."

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Transformer

Explanation

A neural network architecture introduced in 2017 that uses an "attention" mechanism to capture relationships between words in a sentence simultaneously β€” the foundation of most large language models today.

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Deepfake

Explanation

Fake video or audio content that uses deep learning to convincingly synthesize a specific person's face or voice. Alongside its uses, the potential for misuse is a widely discussed social concern.

AI Issues & Ethics

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AI Hallucination

Explanation

When an AI confidently states false information as if it were true. It's a key reason you should always verify anything important that generative AI tells you.

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AI Bias

Explanation

When prejudice or imbalance present in training data carries over into an AI's decisions, producing results that are unfair or skewed against certain groups.

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Artificial General Intelligence (AGI)

Explanation

A future form of AI that, unlike today's task-specific systems, could think and learn across any domain the way a human can.

Why bother learning AI terms?

As generative AI like ChatGPT rapidly weaves itself into everyday life, AI vocabulary is no longer just for specialists β€” it now shows up constantly in the news and everyday conversation. Knowing what the key terms mean makes it much easier to follow AI-related news and technology trends.

Frequently Asked Questions

Are "artificial intelligence" and "generative AI" the same thing?

No. Artificial intelligence is a very broad concept, while generative AI is a more specific subfield focused on creating new content.

Should I trust an AI's answer as-is?

No β€” as explained under "AI Hallucination," generative AI can present false information as if it were fact, so it's best to independently verify anything important.