What happens when you talk to AI

An AI model writes one word at a time, but it doesn’t think one word at a time. Jane from Anthropic’s user experience team breaks down the prediction process behind every AI output, and how to better interpret the responses you get back.

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Chapters

0:00 What happens when you talk to AI?

1:07 How AI training works

2:32 How the model thinks

3:37 Four habits for better results

Jane Leibrock from Anthropic explains the underlying mechanics of AI models like Claude. By examining how these systems utilize predictive patterns, training data, and fine-tuning, the presentation offers practical strategies to help users effectively prompt models and interpret their generated outputs.

No, an AI model is not a search engine (0:05). While they might seem similar, they function in fundamentally different ways:

How AI Works: AI models function by prediction (0:21). When you send a message, the model draws on patterns it learned during its training to generate a response word-by-word (0:24–0:34). It is generating new content rather than retrieving pre-existing answers from a database or the internet (0:315-0:322).
The Difference: A search engine retrieves and displays links or information that already exists. In contrast, an AI model builds its response based on the context of your prompt and its internal patterns, which allows it to create unique text that has never existed before (0:315-0:320).
Accuracy Considerations: Because AI is generating answers based on probability, it can sometimes state false information with total confidence (0:323-0:327). This is why it is essential to use your own judgment and double-check facts when the stakes are high (0:333-0:412).

What happens when you talk to an AI? A journey into the heart of a prompt - Dimension Internet

When you talk to an AI chatbot, a complex, multi-step calculation happens in seconds to translate your words into a statistical prediction. [1]

Here is exactly what happens under the hood the moment you press send:

1. Breaking Down Your Text (Tokenization)

The AI cannot read whole words like a human. It instantly breaks your message down into tokens, which are small chunks of text, syllables, or individual characters. [1, 2, 3]

2. Converting Words to Math (Embedding)

The AI turns these tokens into a grid of numbers called vectors. These numbers represent the concepts and meanings behind your words, mapping how they relate to millions of other ideas. [1, 2]

3. Analyzing the Context

A core technology called a transformer neural network scans the numbers. It evaluates your current prompt, your conversation history, and any uploaded documents to understand your core intent. [1, 2, 4]

4. Predicting the Next Word

Instead of looking up an answer in a database, the AI acts like a highly advanced predictive keyboard. It calculates a probability distribution to guess the single most logical next token. [2, 4, 5]

5. Assembling the Response

The AI selects the highest-probability token and adds it to the text. It then reruns the entire calculation, factoring in the word it just wrote, to predict the next one. This rapid loop repeats until the sentence is complete. [1, 2, 4]

6. Training and Resources

Your conversation helps train the model for future updates, and the massive cloud computing required consumes significantly more electricity and water than a standard web search. [6]

Because the system relies entirely on statistical probability rather than conscious fact-checking, it can sometimes confidently generate.