Language Model is Not a Magic.

A guide to understanding how language models actually work - because being amazed by some GPT is fine, but understanding it is better.

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Technical Depth

Learn the actual algorithms, architectures, and training processes behind modern language models

Research-Based

Built from foundational research papers and authoritative sources in machine learning and NLP

Clear Explanations

Honest about limitations and complexity, with clear explanations that build understanding step by step

Why Understanding Language Models Matters

You've used ChatGPT and Claude, but do you understand how they actually work? This isn't just academic curiosity—understanding the mechanics gives you the power to build better AI systems, debug when things go wrong, and make informed decisions about AI implementations.

We bridge the gap between popular AI articles and dense research papers, giving you the technical depth needed to understand and implement production AI systems.

Built on Solid Foundations

Key Research Papers

"Attention Is All You Need" (Vaswani et al., 2017)

The paper that introduced the Transformer architecture powering GPT, BERT, and everything else

"Language Models are Few-Shot Learners" (Brown et al., 2020)

The GPT-3 paper that showed what happens when you scale language models to 175B parameters

"Deep Learning" (LeCun, Bengio & Hinton, 2015)

The Nature review that laid out the foundations of modern deep learning

Essential Books

"Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

The definitive textbook - dense but comprehensive

"Speech and Language Processing" by Dan Jurafsky and James H. Martin

The NLP bible that covers everything from n-grams to neural networks

Comprehensive learning resource for understanding how language models actually work
Feedback and suggestions welcome • Created by M Fachri • 2025