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Artificial Intelligence for Musicians

  1. Introduction
  2. Emergent Harmonic Structures | Software 1.0
  3. Pythagoras and the Music of the Spheres
  4. Building the Modes from Ancient Theory
  5. Harmonic Ratios in Nature and Music
  6. Musical Mathematics
  7. Exploring Chance and Randomness
  8. Statistics of Sound
  9. Software 2.0 | Deep Learning: Teaching Computers to See
  10. Software 2.0 | Deep Learning: Teaching Computers to Hear
  11. Software 3.0 | Generative AI: Teaching Computers to Read & Write
  12. Software 3.0 | NotebookLM as RAG

Introduction

Who This Book Is For

This book begins where music, math, and artificial intelligence (AI) intersect. It’s for musicians, composers, producers, sound designers, and any creative who wants to collaborate with AI instead of just typing a prompt, pressing a button, and accepting whatever the model gives you.

With Python you’ll learn hands-on how music and math converge, from the physics of the Big Bang to today’s neural networks, and you’ll walk away with the skills you need to navigate generative AI safely and get the most out of it.

Best of all, you choose your own adventure. I walk through everything in the videos, so you can type along with me to really understand the concepts and skills, or just watch the videos and read the book for a high level overview. If you have questions, ask in the Slack or Discord groups (coming soon), or ask Grok, Claude, ChatGPT, or Colab’s built-in AI to explain anything and even invent practice examples or quizzes. By the final chapter you’ll be using AI as a true creative partner that accelerates the way you think, practice, and compose.

Software 1.0, 2.0, and 3.0

In this book we explore AI through Andrej Karpathy’s three kinds of software:

  • Software 1.0 – traditional programming (Python). That’s where we begin.
  • Software 2.0 – deep learning (training neural networks on data).
  • Software 3.0 – natural-language programming (ChatGPT, Grok, etc.).

That’s the arc of this book: you’ll write the rules, then watch machines learn the rules, then just talk to them.

A practical understanding of all three gives you the AI skills you’ll need to augment your musicianship, and so much more. We do explore how generative AI makes music, since that's a critical skill to understand, but we won't suggest you use it to make your music for you. If there's one thing we hope you take away from this book, it's the relationship between you and AI. You stay the artist, all the time. Augment, don’t generate. AI does the chores; you make the music.

Physicist Stephon Alexander, in The Jazz of Physics, describes the Big Bang itself as a single frequency expanding outward, the same kind of patterns we find in scales, rhythms, and modern AI algorithms. My own path from stage to classroom to production AI led me to start Barrios AI and to write this book so you can see and use those connections in your own work.

Full disclosure: you don’t need any programming experience. Chapter 1 teaches Python from zero, all through music, and the code deepens as the book goes. When it runs ahead of you, that’s by design: Chapter 3 gives you a method for using AI as a tutor that never tires of your questions. Along the way you’ll pick up skills that carry well beyond music: Python, data analysis with Pandas and NumPy, statistics on real recordings, and a working understanding of how neural networks and chatbots actually work. You’ll generate soundscapes in code, turn Bach into data, train a model that hears the difference between major and minor chords, and finish by grounding an AI in your own sources so it stops guessing. I’ll keep everything practical: 100% musical and 100% understandable.

Software & Google Colab Notebooks

When you buy the book you receive a collection of ready-to-run notebooks for every chapter (code-along + completed versions). All you need is a free Google account.

If you’ve never heard of it, a Colab notebook is a free coding environment from Google that runs entirely in your browser. Nothing to install, nothing to configure, it just works. You open a link, press the play button next to a block of code, and it runs on Google’s computers, not yours. Each notebook mixes short explanations with runnable code, so you read a little, run a little, and hear or see the result right away.

That makes Colab the easiest way ever to get started with programming for AI. The heavy libraries we use (NumPy, Pandas, TensorFlow) come pre-installed, it’s the same tool real AI researchers use every day, and it even has AI built in: if a cell confuses you, ask Colab’s AI to explain it right there. Type along with the videos, change the numbers, break things, and rerun. That’s the whole workflow, and it’s how you’ll go from printing frequencies to generating soundscapes you can actually hear.

AI Musician Certification

This book is Stage 1 of the four-stage AI Musician Track, and each stage stands on its own:

  • Stage 1 · Foundations: Artificial Intelligence for Musicians (this book). Understand what AI is (Software 1.0/2.0/3.0) and wield a little Python as a force multiplier.
  • Stage 2 · Literacy: Prompt Engineering for Musicians. Become AI literate with the hottest new programming language: English.
  • Stage 3 · Agency: Vibe Coding for Musicians. Agency > intelligence. Once you know prompt engineering, vibe coding takes you to the next level.
  • Stage 4 · Architect: Augmented Intelligence for Musicians. AI engineering foundations: build custom AI systems to help you do almost anything.

Own all four books and you unlock the capstone: a real project that shows you can put AI to work as a musician. This isn’t an auto-graded quiz or a certificate mill. I personally review every capstone, so you get feedback you can actually grow from, and when yours passes, you earn the AI Musician certification, a real credential you can post on LinkedIn and social media. Showcase the project itself wherever you want: your vibe-coded website, your portfolio, your self-published work. The sky’s the limit. Full details at barrios.ai/certification.

Thank You for Buying This Book!

Artificial Intelligence for Musicians is the first volume in a growing series that also covers composition, practicing, and advanced musicianship with AI.

Let’s get to work.

Author: Jonathan Barrios
Editor: Constance Howes