5 AI terms you keep hearing and what they actually mean

Whether it's powering your phone’s autocorrect or helping someone create a new recipe with a few words, artificial intelligence (AI) is everywhere right now. But if you're still nodding along when someone mentions "neural networks" or "generative AI," you're not alone.

Today I am breaking down five buzzy AI terms that you've probably seen in headlines, group chats or app updates, minus the tech talk. Understanding these basics will help you talk AI with confidence, even if you’re not a programmer.

Stay tuned for more in this series as we dive deeper into privacy-related tech terms and other essential concepts, answering the top questions we get from readers like you.

1. Artificial intelligence (AI)

The big umbrella term

Artificial Intelligence is a broad term for computer systems that can do tasks normally requiring human intelligence. That includes understanding language, recognizing images, making decisions and even learning from experience.

You’re using AI when:

• Your email suggests replies
• Your phone transcribes your voice
• Netflix recommends what to watch next

Think of AI as the category; everything else on this list is a branch of it. It’s the foundation for all the smart tools we use today, from voice assistants to facial recognition. As AI continues to evolve, it has the power to make everyday tasks easier, faster and more personalized. But as it becomes more embedded in our lives, understanding the basics is key to using it wisely and protecting your digital autonomy.

2. Machine learning (ML)

How AI learns patterns

Machine Learning is a type of AI that learns from data instead of being explicitly programmed. It improves over time by finding patterns and making predictions.

For example: You like action movies. You watch a few. Over time, the algorithm learns your preferences and recommends similar titles, even if you didn’t say anything directly.

Common uses of ML:

• Spam filters in email
• Fraud detection in banking
• Personalized playlists

ML is how AI "gets smarter" by itself, and it's a big part of how tech becomes more helpful and intuitive. From catching suspicious charges on your credit card to curating your favorite music, machine learning can make life more seamless and even safer.

But as with any technology, it’s important to stay aware of how your data is being used and who’s doing the learning. The more we understand how it works, the better we can decide how and when to trust it.

3. Neural network

The tech that mimics your brain

Neural Networks are a special kind of machine learning designed to mimic how the human brain works, at least loosely. They're made up of layers of "neurons" that process data and make decisions.

They’re particularly good at recognizing complex patterns, like identifying faces in photos or translating languages.

Use cases include:

• Face ID unlocking your phone
• Speech-to-text apps
• Translating text in real time

If AI is the brain, neural networks are the brain cells doing the work. Neural networks are the part of AI that actually processes information. They’re designed to mimic how human brains work, taking in data, learning patterns and making decisions. So, when AI recognizes a face, writes a sentence or makes a suggestion, it’s neural networks making that happen behind the scenes.

4. Generative AI

AI that creates, not just predicts

Generative AI doesn’t just analyze data, it creates new stuff: text, images, videos, code, music, even voices. It’s trained on huge amounts of content and learns how to generate something new that mimics the original.

You’ve seen it in action if you’ve used:

• ChatGPT or similar bots to write messages
• AI art generators like Midjourney or DALL·E
• Auto-generated captions or social media copy

It’s like giving a machine a vibe and watching it invent something that fits. Generative AI is creative, fast and sometimes uncannily realistic, which is what makes it both exciting and a little unsettling.

Think you can tell the difference?

Be sure to play my game to guess which photo is AI and which one is real. It’s harder than you think and a good reminder that as these tools get more advanced, staying alert and informed is more important than ever.

5. Prompt

The magic words that make AI work

A prompt is the input you give to an AI system, usually a question, command or description. It’s how you talk to tools like ChatGPT or image generators. The better your prompt, the better the result.

Examples:

• "Write a birthday message in the style of Shakespeare"
• "Create a recipe using only chickpeas and chocolate"
• "Make an image of a robot drinking coffee in Paris, 1920s style"

Prompts are to AI what questions are to Google, but with more creativity and conversation. Unlike a search engine that simply points you to existing content, AI can generate entirely new ideas, images and text based on what you ask. It’s more than a search box; it’s a creative tool. Whether you’re drafting a story, designing a logo or planning a vacation, learning how to prompt effectively lets you tap into AI’s full potential as a collaborator, not just an information source.

Kurt’s key takeaways

You don’t need a computer science degree to understand AI, just a few solid definitions. From machine learning and neural networks to generative AI and prompts, these tools are no longer reserved for tech labs; they're becoming part of your everyday life. Whether it’s helping you write an email, organize your photos or get dinner ideas based on what’s in your fridge, AI is already working behind the scenes to make life a little easier (and sometimes a lot more interesting).

Now that you’ve got the lingo down, you’ll be better equipped to navigate the AI-powered world with confidence and curiosity.

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