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Programmer.ie Book

Models From First Principles

Build a working understanding of modern AI models by tracing the mechanisms from representations and learning through attention and transformer architectures.

Understand models by constructing the ideas in layers, keeping the mathematical and computational mechanisms connected to working code.

Contents

Chapters

Models From First Principles 08: Preference Rankers — Learning Which Answer Is Better

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Models From First Principles 08: Which Model Should You Use? MR.Q, EBT, SICQL, HRM, Tiny and PACS Compared

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Models From First Principles 07: PACS — Building an Optimizer From Gradient Statistics

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Models From First Principles 06: Inside Tiny — Residual Blocks, Attention and Sparse Autoencoders

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Models From First Principles 05: Tiny — Recursive Reasoning With a Small Neural Network

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Models From First Principles 04: HRM — Hierarchical Reasoning With Fast and Slow Recurrent State

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Models From First Principles 03: SICQL — Building a Model From Q, V and Policy Networks

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Models From First Principles 02: EBT — From One Score to Q, V, Policy and Advantage

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Models From First Principles 01: MR.Q — Building a Neural Quality Model From Two Embeddings

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Models From First Principles 00: The Model Inside the Model

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Programmer.ie

Technical library for the AI era.

Understand what is changing. Learn how it works. Use it.

© 2026 Ernan Hughes
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