--- collection: lessons slug: what-is-ai locale: en title: "What is AI?" summary: "Why does ChatGPT give you a different reply every time you send the same request? Four terms explain it: AI, Model, LLM and Chatbot." publishedAt: 2026-09-22 status: live tags: ["AI","Model","LLM","Chatbot","ChatGPT"] canonical: https://codebelkalam.com/en/learn/what-is-ai --- # What is AI? Why does ChatGPT give you a different reply every time you send the same request? Four terms explain it: AI, Model, LLM and Chatbot. > **Note:** > > The video for this lesson is in Arabic. You can [watch it on YouTube](https://www.youtube.com/watch?v=Z25MNGd5-sg). ## The short version Send ChatGPT the same request twice and you will most likely get two different replies. That can look like a glitch, but it is actually the clearest sign of how these systems work: they don't look up a ready-made answer they have stored. They write a new reply every time. Four terms are all you need to follow what is going on: **AI**, **Model**, **LLM** and **Chatbot**. After that you will know who is actually answering you, and where the words come from. ## Key terms - **AI**: software that does tasks that used to need human intelligence, such as understanding language and writing text. - **Model**: the trained system that generates the replies. The app is only a front end for it. - **LLM**: a large language model, trained on huge amounts of text to generate language. - **Chatbot**: the chat interface you use to talk to the model. ## The explanation ### AI is bigger than ChatGPT Artificial intelligence, or **AI**, is not another name for ChatGPT. When your phone camera recognizes your face and improves the photo around it, that is **AI**. When your maps app picks the least crowded route for you, that is **AI** too. In other words, we have been using it for years without noticing. What is new is that it can now talk with you in plain language, the way you would talk to anyone. ### A counter at a government office Picture yourself at a government office, standing at a service counter. You write your request on a slip of paper and hand it over. Behind the counter, a clerk takes the slip, reads it, and starts writing a reply. - The clerk sitting behind the counter is the **Model**: the mind that understands your request and writes the reply. - The counter itself, the place where you write your request, is the **Chatbot**. - This clerk is no ordinary clerk: they have read millions of letters and books. That kind of **Model** is called an **LLM**, short for Large Language Model. - And a program doing all of this work instead of a person: that is **AI**. > **Note:** > > The counter is not part of the clerk, and the clerk is not part of the counter; each has its own place in the picture. The only "this is a kind of that" relationship among the four terms is that an **LLM** is a kind of **Model**. ### It read to learn, not to memorize You might ask: if this clerk has read millions of letters, aren't they just keeping them on file, waiting for your question so they can hand you one? No. The clerk has nowhere to keep copies of old letters. They didn't read in order to memorize. They read to learn how letters are written, how words are put in order, and how a reply is built. So when your slip arrives, they don't search for an old reply to hand over. They pick up a blank sheet and start writing from scratch. Hand in the same request twice and you won't get a ready-made reply pulled from a desk drawer. It gets written again, every time. > **Warning:** > > The common mistake here is treating a **Chatbot** like a search engine that retrieves a stored answer, and then taking a different reply the second time as proof the first one was wrong. Different wording is expected, because an **LLM** writes the reply from scratch every time. ## Try it yourself ### 1. Open ChatGPT and start a new chat. The experiment in the video was recorded without signing in, with web search turned off. ### 2. Copy the request below and send it exactly as it is. ```prompt Give me 3 gift ideas for my friend who loves reading ``` ### 3. Open a second new chat and send the exact same request, word for word. ### 4. Compare the two replies. Don't stop at the general meaning; look at the words themselves. Are the ideas the same or different? Is the order the same? Are the sentences alike? In the video's experiment, each reply came back with three ideas completely different from the other, even though the request was identical. > **Tip:** > > If the two replies come out close, that doesn't mean the idea is wrong. Sometimes a request is simple enough that the answers converge. Try a slightly longer request and the difference will show more clearly. > **Note:** > > If you are signed in and memory or personalization settings are on in your account, the replies may be closer than they were in the video. For a comparable result, try it signed out, or turn those settings off for a while. ### In Claude The same steps work in Claude, but it requires signing in. So use a clean session: turn off memory and personalization, don't attach any files, don't pick a project, then send the same request in two new chats and compare them. ## Why this matters to you When you later start building real things just by talking, like a page or a small tool, the same thing will happen: the same request can give you a different result each time. So don't assume that what you got the first time is the only possible answer. Keep the result that works, and test it yourself before you rely on it.