Ace AI Interview Series 20-Understanding Reinforcement Learning from Human Feedback (RLHF) in Large Language Models

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Feb 25, 2025

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For the complete list of AI interview prep topics, check out the Table of Contents for this comprehensive AI interview prep series : https://medium.com/@aisagescribe/ace-ai-interview-series-table-of-content-052f78a25ab2

Introduction

Large Language Models (LLMs) have transformed how artificial intelligence (AI) understands and generates text. Despite their impressive capabilities, aligning these models with human preferences remains a critical challenge. Reinforcement Learning from Human Feedback (RLHF) has emerged as a key technique to fine-tune LLMs, ensuring they generate more desirable, safe, and contextually relevant responses. Here we review the core concepts of RLHF, explores the difficulties associated with it, and provides example interview questions and answers for professionals in the field.

What is RLHF?

Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that integrates human preferences into the training process of reinforcement learning agents. In the context of LLMs, RLHF is used to align model outputs with human expectations, reducing biases and improving response quality. The primary workflow consists of the following steps:

1. Pretraining the Model: The LLM is initially trained using supervised learning on a vast corpus of text data to understand language…