So What Exactly Is AI?
Artificial intelligence is a broad term for computer systems capable of performing tasks we associate with aspects of human intelligence.
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AI can do many different kinds of tasks.
Artificial intelligence is a broad category. Different AI systems can perform very different kinds of work.
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Your phone groups photos by the people in them, and your bank app reads the check you photograph for mobile deposit.
A support chatbot understands “I need to push my flight to Friday” even when you phrase it casually.
A retailer notices that customers who buy running shoes often buy water bottles within the next week.
A weather app forecasts afternoon rain, and a hospital system flags patients at higher risk of returning.
Drafting a first version of an email, a product description, or a slide outline in seconds.
Delivery software working out the most efficient order for a driver’s 40 stops.
AI isn't actually new.
You've probably interacted with forms of it for years.
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Spam filters
Help identify and block unwanted messages.
“You’ve WON a free cruise!” lands in your spam folder before you ever see it.
Recommendation systems
Suggest movies, music, products and other content.
You finish three crime dramas, and your streaming service suggests a fourth one you end up loving.
Fraud detection
Spot unusual patterns that may signal fraud.
Your bank texts you to confirm a purchase made overseas minutes after you used your card at home.
Navigation
Help identify routes and adjust to changing conditions.
Your map app reroutes you around an accident that happened five minutes ago.
Voice assistants
Understand spoken requests and respond to them.
You say “Set a timer for ten minutes” while cooking, and it’s done — no hands needed.
Predictive text
Suggest words and complete text as you type.
You type “Running five minutes” and your phone suggests “late.”
Ordinary people gained direct access to powerful generative AI.
In the 2020s, interacting directly with these systems became dramatically more accessible.
AI that creates.
Generative AI creates new output based on patterns learned from enormous amounts of data.
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A polished follow-up email to a client, written from your meeting notes.
A custom illustration for a presentation slide, created from a one-line description.
A natural-sounding voiceover for a short training video.
A brief product demo clip generated from a written script.
A spreadsheet formula or small script that automates a weekly report.
A summary of the top themes in a year of customer feedback.
One important kind of generative AI is an LLM.
Programs like ChatGPT, Claude, Gemini, and others use large language models.
An LLM is an AI system trained on large amounts of text so it can recognize language patterns and generate responses.
Understanding the technical workings of an LLM can be useful, but it is not a prerequisite for using one effectively.
At a simplified level, an LLM learns patterns and relationships in language and uses those patterns to generate an appropriate continuation or response.
One critical fact.
An AI language model does not know things in the same way you do.
Its results can be extraordinary. They can also be wrong — and sometimes wrong while sounding extremely confident.
We'll learn how to deal with that.
Quick check.
Which is the best description of generative AI?
The key idea: AI is a broad category. Generative AI is the part that creates new output, and large language models are one important kind of generative AI.
So What Exactly Is AI?
You can now distinguish AI, generative AI and large language models — and explain why human judgment still matters.
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