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AIAI Wranglers
Foundation

Modern AI, from the mathematics up.

A 5,546-page reference covering the mathematics and practice of modern generative AI, from first principles through frontier capabilities. Read clean HTML or the original PDF, then ask the built-in AI tutor when you want to go deeper.

47 chapters

I Foundations

5 chapters

II Probabilistic Generative Models

3 chapters

III Generative Adversarial Networks

5 chapters

IV Variational and Transport Methods

3 chapters

V Autoregressive Models and Flows

2 chapters

VI Diffusion Models

4 chapters

VII Reasoning and Recursive Computation

1 chapter

VIII Memory for Large Language Models

1 chapter

IX Fine-Tuning and Alignment

1 chapter

X Continual Learning

1 chapter

XI Agentic AI and Multi-Agent Systems

1 chapter

XII Neural Network Tricks

1 chapter

XIII Privacy and Security

1 chapter

XIV Neural Architecture Search and Adaptive Networks

1 chapter

XV Evolutionary AI: Coevolution, Open-Ended Search, and Autonomous Discovery

1 chapter

XVI Applications of Generative Models in Retrieval

1 chapter

XVII Generative Models for Structured Data

1 chapter

XVIII Generative Models for Mathematics

1 chapter

XIX Generative Models for PDE-Based Simulation

1 chapter

XX Generative Models for Medical Image Segmentation

2 chapters

XXI Interpretability and Explainability of Generative Models

1 chapter

XXII Generative Models for Weather Prediction

1 chapter

XXIII Federated Learning for Generative Models

1 chapter

XXIV Generative AI for Accessibility and Disabilities

1 chapter

XXV Distributed Generative AI

5 chapters

Experiments

1 chapter