How to Use This Guide
This guide is designed to be read both linearly and as a reference. Here are some tips for getting the most out of it.
Navigation
Section titled “Navigation”Use the sidebar on the left to browse topics by category. Each section is organized from foundational concepts to more advanced topics:
- Getting Started — You are here. Orientation and overview.
- AI Research — Start with Transformers, then move to LLMs and Prompt Engineering.
- Machine Learning — Begin with Supervised Learning, explore Neural Networks, then Optimization.
- Neuroscience — Start with Computational Neuroscience, then Neural Coding, and finally Brain-Computer Interfaces.
Reading Order
Section titled “Reading Order”If you are new to these fields, we recommend starting with the Machine Learning section to build foundational knowledge, then exploring AI Research for modern applications, and finally Neuroscience for biological perspectives.
If you already have a background in one area, feel free to jump directly to the topics that interest you. Each article is written to be self-contained, with cross-references where relevant.
Conventions
Section titled “Conventions”Throughout this guide, you will encounter:
- Key Concepts sections that summarize the most important ideas in each article
- Further Reading sections with links to seminal papers, textbooks, and online resources
- Mathematical notation where necessary, kept as accessible as possible
Contributing
Section titled “Contributing”This guide is a living document. If you would like to suggest corrections, additions, or new topics, please reach out to the I2 team or open an issue on our GitHub repository.