The Importance of Context in AI: Garbage In, Garbage Out

Introduction

When communicating with large language models (LLMs) like ChatGPT, the adage “garbage in, garbage out” holds true. The quality of the AI-generated output and its susceptibility to hallucinations are highly dependent on the quality of the input data. This means that if we provide poorly defined or ambiguous information, we are more likely to receive unsatisfactory responses and potentially face AI-generated hallucinations. Despite the seemingly obvious conclusion that providing more context leads to better output and fewer hallucinations, there is a notable presence of AI tools that promise to “magically” generate useful content based on just a short sentence or a keyword.

This phenomenon might seem counterintuitive, as one would expect AI tools to prioritize generating content with sufficient context to ensure accuracy, relevance, and reduced hallucinations. However, as we explore this topic, we will uncover the reasons behind the popularity of such AI tools and discuss their implications for the future of AI content generation.

Throughout this blog post, we will delve into the importance of context when interacting with AI systems, particularly large language models like ChatGPT, and provide examples of how insufficient context can lead to suboptimal results and increased…