What is AI

Model Training

Companies gather billions of documents—books, every Wikipedia article, websites, research papers—and feed them through thousands of powerful computers for months. But what the computer is actually doing isn't memorizing facts, it's learning patterns: understanding how human language works and the patterns of human thought.

By the end of training, the AI has developed an intuitive understanding of language, context, and reasoning—not by storing information, but by recognizing the deep patterns that make human communication work.

Fine Tuning

After initial training, the raw AI model is like a brilliant student who knows everything but doesn't know how to have a conversation. Fine tuning teaches it to be helpful, accurate, and appropriate.

This involves training the model on thousands of examples of good AI conversations—how to answer questions clearly, when to admit uncertainty, how to be helpful without being harmful. Human trainers create examples of ideal responses as additional learning material.

It's the difference between reading every customer service book versus actually working with customers. Fine tuning gives AI practical conversational skills.

Alignment

Alignment is about making sure the AI behaves according to human values and doesn't cause harm. After fine tuning, teams of human reviewers test the model extensively, looking for problems like biased responses, harmful advice, or inappropriate content.

They run thousands of test conversations, checking whether the AI gives dangerous instructions, spreads misinformation, or exhibits unwanted behaviors. When problems are found, the model gets additional training to fix these issues.

Think of it as quality control meets ethics review. The goal is ensuring that when millions of people start using the AI, it consistently behaves in ways that are helpful, harmless, and honest.

Response Generation

When you send a request to the AI, it generates responses one word at a time. For each word, it thinks "Based on all the patterns I learned and our current conversation, what word should come next?"

Think of it as super-powered autocomplete. The AI chooses each word based on the patterns it learned during training, building responses word by word until it determines the answer is complete. It's not retrieving pre-written responses—it's constructing new text by predicting what should come next in the conversation.