# Preface {.unnumbered}

Welcome to {{< var title.long >}}. This book is your gateway to the fast-paced world of AI systems through the lens of embedded systems. It is an extension of the course, TinyML from [CS249r](https://sites.google.com/g.harvard.edu/cs249-tinyml-2023) at Harvard University.

Our aim is to make this open-source book a collaborative effort that brings together insights from students, professionals, and the broader community of applied machine learning practitioners. We want to create a one-stop guide that dives deep into the nuts and bolts of AI systems and their many uses.

> "If you want to go fast, go alone. If you want to go far, go together."
> -- African Proverb

This isn't just a static textbook; it's a living, breathing document. We're making it open-source and continually updated to meet the ever-changing needs of this dynamic field. Expect a rich blend of expert knowledge that guides you through the complex interplay between cutting-edge algorithms and the foundational principles that make them work. We're setting the stage for the next big leap in tech innovation.

# Why We Wrote This Book

We're in an age where technology is always evolving. Open collaboration and sharing knowledge are the building blocks of true innovation. That's the spirit behind {{< var title.long >}}. We're going beyond the traditional textbook model to create a living knowledge hub. 

The book covers principles, algorithms, and real-world application case studies, aiming to give you a deep understanding that will help you navigate the ever-changing landscape of embedded AI. By keeping it open, we're not just making learning accessible; we're inviting new ideas and ongoing improvements. In short, we're building a community where knowledge is free to grow and light the way forward in global embedded AI tech.

# What You'll Need to Know

You don't need to be a machine learning whiz to dive into this book. All you really need is a basic understanding of systems and a curiosity to explore how embedded hardware, AI, and software come together. This is where innovation happens, and a basic grasp of how systems work will be your compass.

We're also focusing on the exciting overlaps between these fields, aiming to create a learning environment where traditional boundaries fade away, making room for a more holistic, integrated view of modern tech. Your interest in embedded AI and low-level software will guide you through a rich and rewarding learning experience.

# Book Conventions

For details on the conventions used in this book, check out the [Conventions](./contents/conventions.qmd) section.

# Want to Help Out?

If you're interested in contributing, you can find the guidelines [here](https://github.com/harvard-edge/cs249r_book).

# Get in Touch

Got questions or feedback? Feel free to [e-mail Prof. Vijay Janapa Reddi]({{< var email.info >}}) directly, or you are welcome to [start a discussion thread](https://github.com/harvard-edge/cs249r_book/discussions) on GitHub.

# Contributors

A big thanks to everyone who's helped make this book what it is! You can see the full list of individual contributors [here](./contents/contributors.qmd) and additional GitHub style details [here](https://github.com/harvard-edge/cs249r_book/graphs/contributors). Join us as a contributor!