System Design: ChatGPT System

What is ChatGPT?

ChatGPT is an advanced conversational application built on a sophisticated artificial intelligence language model developed by OpenAI. It is designed to understand natural language and generate human-like text, making it a highly effective tool for various communication tasks. Clear and effective communication is crucial in many situations, such as explaining complex concepts, brainstorming ideas, or writing professional content. In these cases, ChatGPT can help by:

• Simplifying technical subjects

• Proposing innovative ideas

• Composing clear, well-structured text

ChatGPT-like systems are particularly noteworthy because they can interpret various inputs, even when prompts are incomplete or ambiguous. They can respond to complex, abstract, or open-ended questions with clarity and relevance. These capabilities result from sophisticated generative AI techniques, extensive training on large datasets, and advanced language modeling. Rather than relying on predefined answers, such systems analyze context, identify patterns in language, and generate responses that align with the intent and structure of the input.

In this chapter, we’ll design a text-to-text generation system similar to ChatGPT. While OpenAI has not publicly disclosed the exact architecture and design details of ChatGPT, the approach covered in this lesson is based on general principles, established techniques, and best practices commonly used in building such systems.

Let’s start by defining the core requirements, which play a critical role in shaping the overall design:

Requirements

Building the backend of a text-to-text generation system like ChatGPT requires careful attention to both functional and nonfunctional requirements:

Functional requirements

• Dialogue management: The system must enable context-aware, text-based conversations by interpreting user input, maintaining context, and generating relevant, human-like ...