ChatGPT Is Built With Millions of These (Sort of): Understanding the OG Perceptron
Last Updated on December 9, 2025 by Editorial Team
Author(s): Sayan Chowdhury
Originally published on Towards AI.
Understanding the OG Perceptron
Neural networks look complex from the outside, but at their core they are built from one simple unit. This unit is called the perceptron.

The article explains the perceptron, the simplest form of a neural network, which serves as a tiny decision maker by taking a set of inputs to decide between two outcomes. It discusses how perceptrons inspired modern deep learning systems, focusing on their structure, operation, and learning processes. Practical examples illustrate perceptron’s ability to classify data and highlights the limitations of perceptrons in handling complex problems that are not linearly separable. Overall, it emphasizes the perceptron’s foundational role in understanding neural networks and modern AI systems like ChatGPT.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Get your free Agents Cheatsheet here. Our proven framework for choosing the right AI architecture.
3 years of hands-on work with real clients into 6 pages.
Take our 90+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!
Discover Your Dream AI Career at Towards AI JobsTowards AI has built a jobs board tailored specifically to Machine Learning and Data Science Jobs and Skills. Our software searches for live AI jobs each hour, labels and categorises them and makes them easily searchable. Explore over 40,000 live jobs today with Towards AI Jobs!
Note: Content contains the views of the contributing authors and not Towards AI.