Home › Encyclopedia › Fundamentals

fundamental icon

Artificial Intelligence (AI)

Latest update: 26/04/28

Back to › Fundamentals

Definition

Artificial Intelligence (AI) is software that can do things that normally require human thinking – like understanding language, recognizing images, making decisions, or generating new content.

What Is Artificial Intelligence?

AI is a broad term for computer systems that can perform tasks humans would typically handle with their brains. Writing an email, translating a sentence, spotting a cat in a photo – until recently, only people could do those things reliably. Now software can too.

The term goes back to the 1950s, coined by computer scientist John McCarthy. But the AI most people interact with today – the chatbots, writing assistants, and image generators – only became possible in the last few years thanks to a specific type of AI called machine learning, and more recently, large language models.

Without AI, every software interaction would require explicit rules written by a programmer. AI replaces those rules with patterns learned from data.

How Does It Work?

Modern AI systems learn from examples instead of following hand-coded instructions. Feed a system millions of emails labeled “spam” or “not spam,” and it learns to tell them apart. Feed it billions of sentences, and it learns how language works.

Think of it like training a new employee. You don’t give them a 500-page manual for every situation. You show them examples, let them practice, and correct their mistakes. Over time, they build judgment. AI training works the same way – just faster and at a much larger scale.

The AI you interact with today – like a chatbot – has already been trained. When you type a prompt, it’s using everything it learned during training to generate a response

Why It Matters for Your Prompts

AI systems don’t think the way humans do. They don’t have opinions, memories between sessions, or common sense the way you do. They produce responses based on patterns in their training data and the text you give them right now.

That gap matters when you’re writing prompts. A human colleague can fill in blanks from shared context – “you know the project we discussed last week.” An AI can’t. It only knows what’s in front of it.

The more you treat an AI like a capable but context-free collaborator – giving it role, background, goal, and format – the better its output gets. Most frustrating AI results trace back to a mismatch between what the user assumed the AI knew and what the AI actually had to work with.

Understanding that AI is pattern-matching on your words (not reading your mind) changes how you write prompts entirely.

Real-World Example?

A marketing manager asks an AI: “Write me a product description.“

The result is generic – vague adjectives, no specifics, nothing usable.

She tries again: “Write a 100-word product description for a sustainable water bottle targeting gym-goers aged 25–40. Tone: energetic but not over-the-top. Highlight that it keeps drinks cold for 24 hours and is made from recycled ocean plastic.“

Same AI. Completely different result. The AI didn’t get smarter – she gave it the context it needed to do the job well.

Related Terms

  • Large Language Model (LLM) – The specific type of AI that powers most text-based tools like ChatGPT and Claude.
  • Prompt – The input you give an AI; the starting point for everything it generates.
    Prompt Engineering – The practice of writing better prompts to get better results from AI.
  • Hallucination – What happens when an AI generates confident-sounding but incorrect information.
  • Temperature – A setting that controls how creative or predictable an AI’s output is.

Frequently Asked Questions

Is AI actually intelligent, or is it just autocomplete?

It’s somewhere in between, and that’s genuinely debated. Today’s AI doesn’t understand the world the way humans do – it doesn’t have goals, feelings, or awareness. But calling it “just autocomplete” undersells it. It can reason through problems, write code, and produce work that requires real skill. Whether that counts as intelligence depends on how you define the word.

What’s the difference between AI and a regular app or search engine?

A regular app follows fixed rules- search for “pizza” and it looks for that word. AI generates responses based on patterns in training data, so it can answer questions it’s never seen before, handle ambiguous requests, and produce entirely new content. It’s flexible in a way rule-based software isn’t.

Can AI learn from my conversations?

Most AI tools don’t learn from individual conversations in real time. The model you’re using was trained before you talked to it. Some platforms let you save preferences or memories, but the underlying model itself doesn’t update based on what you type today.

Why does the same prompt give different answers each time?

AI models include a randomness setting called temperature. Even with the same prompt, the model doesn’t always pick the same next word – it samples from a range of likely options. That’s why you get variation. You can turn the randomness down if you need consistent output.

References

Further Reading