2.1 ChatGPT: How It Works

You type a question into ChatGPT and within seconds, you get a thoughtful, well-written answer. It feels like magic, but it's actually a carefully engineered process that happens in three main stages. Let's walk through what happens behind the scenes, using simple analogies that anyone can understand.

The Three-Step Process: Understanding, Thinking, Speaking

Imagine ChatGPT as a very smart librarian who works in three distinct phases:

Phase 1: How ChatGPT "Reads" Your Question

When you type "Tell me about the history of pizza," ChatGPT doesn't see words as you do. It sees numbers. Every word, phrase, and even punctuation mark gets converted into a unique number code. This is similar to how computers store everything as 1s and 0s, but for language.

But here's the clever part: ChatGPT doesn't just look at individual words. It looks at relationships between words. In the sentence "The cat sat on the mat," it understands that:

• "cat" is the thing doing the action
• "sat" is the action
• "on" shows position
• "mat" is where the cat sat

Phase 2: The "Thinking" Process (Pattern Matching)

Once ChatGPT understands your question, it starts searching through its "mental library"—which is actually all the patterns it learned during training. This isn't like searching Google. ChatGPT doesn't have a database of facts to look up. Instead, it recalls patterns of how words go together.

For "history of pizza," it might recall patterns like:

• "Pizza originated in" often connects to "Italy" or "Naples"
• "Traditional pizza toppings include" often connects to lists of ingredients
• "The word pizza means" often connects to explanations about Italian words

Think of this like how your brain works when someone asks you about your favorite movie. You don't recite a memorized script. You pull together memories, feelings, and facts, then organize them into a coherent story.

Phase 3: "Speaking" - Generating the Response

This is where the real magic happens. ChatGPT builds its response one word at a time, like a very smart version of your phone's text prediction.

Let's say it starts with "Pizza". Next, it calculates: what word comes after "Pizza" in similar contexts? Based on its training, it might choose "originated". Then "originated" in "Pizza originated" often connects to "in". And so on, word by word, until it has a complete response.

But it's not just guessing randomly. At each step, it considers:

1. Context: Everything that's been said so far in the conversation
2. Grammar rules: Learned patterns of proper sentence structure
3. Topic relevance: What's appropriate for this subject
4. Style: Should this be formal, casual, technical, etc.

The Training That Made This Possible

Before ChatGPT could answer any questions, it went through an intensive "education" process that involved two main stages:

The scale of this training is mind-boggling. If a human tried to read everything ChatGPT was trained on, reading 24/7 without breaks, it would take them thousands of years. And unlike humans, ChatGPT never forgets what it reads.

What ChatGPT Can and Can't Do

Understanding how ChatGPT works helps explain its strengths and limitations:

The "Temperature" Setting: Creativity vs. Consistency

One fascinating aspect of ChatGPT is something called "temperature." This isn't about heat—it's about how predictable or creative the responses are.

Think of it like cooking:

• Low temperature (0.2): Like following a recipe exactly. Responses are consistent, predictable, and safe.
• Medium temperature (0.7): Like cooking with experience. You know the basics but improvise a little. Responses are balanced.
• High temperature (1.0+): Like experimental cooking. Responses can be creative, surprising, but sometimes bizarre.

Most ChatGPT interfaces use a balanced medium temperature, which is why responses are usually helpful but not too wild.

Putting It All Together: A Real Example

Let's trace what happens when you ask: "Why is the sky blue?"

1. Input processing: Each word gets converted to numbers, and ChatGPT understands this is a science question about color perception.
2. Pattern matching: It recalls patterns from science texts: "sky appears blue because" often connects to explanations about light scattering.
3. Response building: It starts with "The" (safe beginning), then "sky" (topic), then "appears" (common in explanations), building step by step.
4. Scientific accuracy: It checks patterns from reliable science sources to ensure accuracy.
5. Completion: It decides when the explanation is complete based on patterns of how such explanations usually end.

The entire process takes seconds, but involves billions of calculations and pattern comparisons.

In our next article, we'll explore how similar principles apply to creating images with tools like Midjourney. The same pattern-recognition approach that generates text can also generate stunning visual art!