How ChatGPT Works: A Simple Overview
4.6 billion people visited ChatGPT in Mar 2025, as per latest data by Semrush. Interestingly, 78.6% of these users accessed the platform via desktop, while 21.4% used mobile devices. With an average session duration of nearly 14 minutes, it’s clear that ChatGPT is not only drawing massive traffic but also successfully engaging users. What makes the platform so effective? How does it actually work behind the scenes? In this blog, we break down the workings of ChatGPT in the simplest terms to help you understand the technology powering one of the world’s most visited AI tools. Let’s dive in.
LLM (Large Language Model) and NLP (Natural Language Processing) two core technologies form the backbone of how ChatGPT functions. While closely connected, they are not identical.
What is a Large Language Model (LLM)?
An LLM is a type of artificial intelligence trained on vast volumes of text data including books, articles, websites, and more. Its purpose is to recognize language patterns, enabling it to predict the next word in a sentence, understand questions, and generate coherent responses.
ChatGPT is built on one of the most advanced LLMs to date: GPT (Generative Pretrained Transformer). This model is designed to produce human-like responses by calculating the most likely sequence of words based on the context it receives.
What is Natural Language Processing (NLP)?
NLP is a field of artificial intelligence that focuses on enabling machines to comprehend, interpret, and generate human language. It allows ChatGPT to understand input, interpret meaning, grasp grammar, and recognize nuances such as tone or sarcasm.
In summary, LLM is the technology behind the scenes, while NLP is the discipline that shapes how language is processed and understood.
Still technical? A real-life example might help to clear your doubts:
Imagine you’re training a customer support agent:
You give them thousands of previous customer conversations (this is like the LLM training on lots of text).
You also teach them how to pick up on polite or angry tones, understand what the customer really wants, and respond clearly (this is like NLP helping with interpretation and interaction).
Below is an example of a prompt, which will make the implication of LLM and NLP in ChatGPT even more clear:
How Does ChatGPT Handle Indexing of Pages?
Unlike search engines such as Google, ChatGPT does not crawl or index the internet. It does not have a live database of websites. Instead, it relies entirely on its pre-trained knowledge base. Therefore, it cannot guarantee that its responses reflect the most current information unless it’s connected to real-time tools or data sources.
Key differences between ChatGPT and Search Engines
⦿ Search Engines and Indexing:
- Search engines like Google have web crawlers that go through the internet, read web pages, and store the content (like a big library). This is called indexing.
- They use that index to quickly find the most relevant pages when you search for something.
⦿ ChatGPT and Indexing:
- ChatGPT does not actively crawl the web to index pages like Google. Its knowledge is based on the data it was trained on, which includes a large amount of text up to a certain point (until mid-2024 was the latest update).
- It does not fetch real-time or live data from the internet. So, for example, if you ask ChatGPT about a product or news event that happened after its last update, it won’t have access to the latest information.
Having said that, ChatGPT excels at providing generalized knowledge, language-based tasks, content generation, summaries, and explanations with human-like fluency.
Absolutely! Here’s the same step-by-step breakdown but tailored to a business example, specifically for a dentist asking ChatGPT a question. This version will work well for professional audiences, such as clinic owners or marketing teams exploring how ChatGPT might help their practice.
How ChatGPT Works (Step-by-Step Process)
Below is the process of how ChatGPT functions, to make it simpler we have explained it with an example:
Step 1. Input (your question)
A user enters a clear, goal-oriented request.
Example Prompt: “Can you suggest some content ideas for promoting my dental clinic on Instagram?”
Step 2. Understanding (using NLP)
Using Natural Language Processing (NLP), ChatGPT analyzes the input to determine:
- Keywords: “content ideas,” “promoting,” “dental clinic,” “Instagram”
- Context: The user is likely a business owner or marketer looking for social media marketing strategies.
- Intent: They want creative, relevant, and practical content suggestions that align with their profession and platform (Instagram).
Interpretation: The model understands this is about generating social media marketing content specifically for a healthcare business.
Step 3. Processing (using LLM knowledge)
Using its training data, the LLM (Large Language Model) references tons of examples for dental social media marketing best practices..
It matches patterns from previous texts, blog posts, and campaign ideas to create high-value suggestions tailored to a dental clinic.
Step 4. Generating Response
The model crafts a response based on what it has “learned,” aiming for engaging, practical, and platform-appropriate content.
Step 5. Output (the final answer)
The user receives a natural, helpful response that can be directly used or adapted in real business activities.
Answer : Here are some Instagram content ideas for your dental clinic:
– ‘Before and after’ smile transformations (with patient consent)
– Oral hygiene tips in carousel format
– Meet-the-team posts to build trust
– Behind-the-scenes of procedures or tools
– Patient testimonials and review highlights
– Fun dental facts or myths debunked
– Seasonal promotions or appointment reminders”
Want to create visibility on ChatGPT for your business?
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