Yuval Avidani
Author
If you feel like the whole world is talking about AI and you're the only one who doesn't fully get what's going on, take a breath, because you are absolutely not alone and you are absolutely not behind. This is the point I want to start from, because it's the most important one. This glossary is written for anyone who has never touched AI, feels like the world is racing ahead without them, and is a little embarrassed to ask "wait, what actually is this thing?"
Let's break it down slowly, in plain language, no big words and no embarrassment. There are no stupid questions here, just terms nobody bothered to explain to us properly.
First things first: what is AI, and what is an LLM
Let's start from the absolute basics. AI, artificial intelligence, is simply software that learned to recognize patterns from tons of examples, so it can do things only humans used to be able to do, like understand language, write, or recognize what's in an image. It's not a robot from the movies and it's not consciousness. It's a machine that has seen so many examples that it learns to guess what the next logical thing is.
And the tool everyone's talking about is called an LLM. A large language model, LLM for short, is a type of AI that has read an enormous amount of text from the internet and learned from it how language works, which is why it can write, summarize, translate and answer us. Think of it like someone who's read almost every book, article and forum out there, and every time we ask it something, it guesses the most probable answer, word after word. ChatGPT, Claude and Gemini are all LLMs.
Gen AI: when the machine also creates — text, image, voice and video
Now here's a term you hear everywhere. Gen AI, short for Generative AI, is any AI that doesn't just recognize or classify, but generates something new: a paragraph, an image, a song or a video. The difference is simple: the computer used to know how to search for an existing image for us — today it knows how to paint us an image that never existed before.
And this happens across four worlds worth knowing. The first is text, which writes us an email, summarizes a document and drafts a message.
The second is image, which generates an illustration, a logo or a product photo out of a sentence we wrote, like "an astronaut cat in oil painting style." The third is voice, which turns text into a human voice, reads us a book, or generates narration for a podcast. And the fourth is video, which generates a short clip from a description, no camera and no crew needed. The cool part is that all of these work the same way: we describe in words what we want, and the machine generates it.
Prompt and token: two words worth knowing
There are two words we hear all the time, and both are simple. A prompt is simply what we write or ask the AI. That's it. The instruction, the question, the request. "Write me a birthday message for mom" — that's a prompt. There's no magic here, it's just a fancy word for "our request."
And the second word is token. A token is a small piece of text, roughly a chunk of a word, and the machine reads and writes in these pieces instead of whole letters. Why should we care? Because both the price and how much text the machine can hold in its head at once are measured in tokens. Instead of explaining, let's just show you: type a sentence in Hebrew or English, and watch how it breaks down into tokens.
So why bother learning this at all — and not because of the herd effect
Now for the real question. There's a lot of noise, and a lot of people approach AI just because everyone around them is doing it — the herd effect. But in my view, the real reason is completely different, and it has proof behind it. In controlled studies, where people were randomly split into a group with AI and a group without, those who got AI finished real tasks much faster and to a higher quality.
Look at the numbers — all from real studies:
And here's the detail I love the most: in every single one of these studies, it was specifically the beginners and the less experienced people who gained the most. Meaning, if you feel like you're "behind," you're exactly the person with the most to gain. This isn't a comforting slogan — it's a result that keeps repeating study after study.
And that's also why this isn't a passing fad. Look how fast this became part of everyday life:
When something becomes the fastest tool in history to reach a billion people, it's no longer a trend — it's infrastructure, the same way the internet and the smartphone were in their time.
Where this helps you, starting tomorrow morning
Let's get concrete, because this is where it becomes tangible. Here are uses anyone can start doing today, both the obvious and the less obvious ones. For writing and phrasing: a gentle note to the neighbor, an official letter to the municipality, or a Facebook post — we write two lines and the AI drafts it. For summarizing: paste a long article or a meeting transcript and ask "sum this up in five bullet points for me." For translating and explaining: "explain this letter from the bank to me in plain words," or "translate this into polite English for me."
And here are the less obvious uses that tend to surprise people. Photograph an invoice, a receipt or a menu, and ask "turn this into a table for me" or "how much did I pay for each item," and the AI reads the image and pulls out the data. Upload an insurance policy or a pension document dozens of pages long and ask "what's my coverage in case of an accident?" instead of spending an hour searching. Or simply learn: "teach me what compound interest is with a real-life example," at your own pace, no embarrassment. None of this requires any technical knowledge, just writing in plain language what you want. (For anyone who wants to go deeper, I also wrote an advanced guide that gets into heavier uses: connecting AI to your emails, analyzing campaigns, and even building an app.)
What AI does not know — and it's completely fine not to know that
It's important we also know the limits, because that's exactly what turns us into smart users. Sometimes AI simply makes things up: it writes a fully confident answer that sounds right but simply isn't correct, and this is called a "hallucination." This happens because it's guessing the logical continuation, and sometimes the guess is wrong. So for anything important — a fact, a date, a number or a legal clause — always double-check.
And here's the most important message I have for you. Nobody is born "understanding AI," and all of us, including the tech people, are learning as we go. Anyone who makes you feel stupid for asking a question simply didn't understand the topic well enough to explain it simply. Let's be the crowd that helps, not the one that looks down on others. So let's test ourselves, no pressure at all:
Your first step, right now
Enough theory, let's begin. Here are three simple steps for your first conversation:
Bottom line, as I see it
So in short: AI is a machine that learned patterns from tons of examples; an LLM is one that specializes in language; and Gen AI is when it creates text, image, voice or video for us, all from a simple request we write in our own words. Price and memory are measured in tokens, and sometimes it confidently gets things wrong, so on anything important, double-check.
In my view, the most important thing isn't memorizing all the terms — it's simply starting to play around. There's no test here, no "you failed," and no question too embarrassing. The one honest limitation worth naming: these tools are impressive but not perfect, they make mistakes, and they don't replace human judgment — they amplify it.
So here's the question I'll leave you with: if it's specifically the people who feel most "behind" who stand to gain the most, what's that one small, annoying task from your day that you'd be thrilled to have someone — or something — just do for you?