What is Chat GPT
As ChatGPT becomes more widely used, many people treat it like a search engine — typing in questions and expecting reliable answers, much like they would with Google. But while the user experience may feel similar, the underlying technology is fundamentally different.
Can You Use ChatGPT Like Google?
What’s the Same — and What’s Different?
Many people use ChatGPT the way they used to use Google — by typing in a question and expecting an answer. But while the two might feel similar on the surface, they work in very different ways.
We’re often asked: What exactly does ChatGPT do? Here’s the answer — in both non-technical and technical terms.
The Non-Technical Answer
ChatGPT isn’t a traditional database like Google or Wikipedia. It’s a language model trained on a huge amount of text from books, websites, and other sources. It doesn’t store facts or documents the way a search engine does. Instead, it has learned patterns - how words, concepts, and ideas tend to appear together.
When you ask a question, ChatGPT doesn’t “look up” the answer.
Instead, it generates a response by predicting what words are most likely to come next, based on the patterns it has learned.
Think of it like this:
ChatGPT doesn’t “remember” - it “guesses very intelligently.”
This means it can give very fluent and convincing answers - but it can also get things wrong. It doesn’t know facts in the same way a database or search engine does, so sometimes it will sound confident while being inaccurate.
Some versions of ChatGPT (including those with access to browsing or custom data) use something called RAG - Retrieval-Augmented Generation. This lets the model pull in real information from external sources (like the internet or uploaded documents) to make its answers more accurate and up to date.
Helpful Analogies: How Google and ChatGPT Differ
1. Navigator vs. Autopilot
- Google is like a navigator: it gives you a list of routes (websites) and lets you choose which one to follow.
- ChatGPT is like an autopilot: it tries to take you straight to the answer — but it can sometimes take a wrong turn.
2. Librarian vs. Storyteller
- Google is like a librarian: it helps you find the right book or article.
- ChatGPT is like a storyteller: it reads widely, then tells you a version of the answer in its own words.
3. Cookbook vs. Chef
- Google gives you the cookbook: a selection of recipes from different sources.
- ChatGPT is like a chef: it uses what it has learned (ingredients) to create a new recipe just for you — though the result might still need a taste test.
In short: Google retrieves. ChatGPT generates.
The Technical Answer
ChatGPT is a large language model (LLM) developed by OpenAI, built on the transformer architecture. It was trained using unsupervised learning on a massive dataset of text from books, websites, articles, and other publicly available sources.
Rather than storing facts in a database, ChatGPT learns statistical patterns in language — specifically, the probabilities of words and phrases occurring in different contexts. During inference (when you ask it something), the model generates responses by predicting the next most likely token, one at a time, based on the input and previous tokens.
This makes ChatGPT generative, not retrieval-based. It doesn’t access live data or know where its information originally came from. As a result, it can produce fluent, human-like responses — but also hallucinate facts or give outdated information.
To improve factual reliability, some implementations use RAG (Retrieval-Augmented Generation). In this setup, a retrieval system fetches relevant documents or web content based on the query, and that information is passed to the model as context. This helps ground the generated responses in real-time or domain-specific knowledge.
