3. How do Large Language Models work?

Introduction

When a question is entered into a chat bot, the sentence is broken down into words or tokens and each word is mapped to numerical embeddings. Large language models then begin computations for each word in parallel. This process involves predicting the next word at each processing step based on the input prompt. The model utilizes components like attention heads and multi-layer perceptrons to understand the query, predict the next word, and generate accurate responses. This article delves into the detailed workings of large language models and how they process information to provide answers.

Keywords:

• Large language models
• Tokens
• Numerical embeddings
• Attention heads
• Multi-layer perceptrons
• Predictions
• Queries
• Keys and values
• Machine learning algorithms

FAQ:

• How do large language models process input sentences?
• What components are utilized in large language models to understand queries and generate responses?
• How do attention heads assist in the functioning of large language models?
• What role do numerical embeddings play in the computations of large language models?
• How do large language models learn to predict the next word in a sentence accurately?