Online Textbook
Building Language AI: From Tokens to Agents
A practitioner's guide to large language models, retrieval-augmented generation, fine-tuning, and agentic systems.
Online Textbooks
These book manuscripts synthesize lessons from applied research, course design, and three decades of system building. Each draft is open and continuously updated. Shorter writing lives under blog posts.
Each volume aims to give a complete treatment of its subject, combining the theoretical concepts with the modern, practical tools a working practitioner actually uses. Every book is domain-focused: the AI theory and tooling for a single domain or data type, from language and vision to audio, tabular data, and quantum.
The books are not meant to be read cover to cover. Each is a focused, self-contained reference: a place students in the matching course can look things up, a resource instructors can build on when preparing a course, and a compact but complete treatment of a specific subject for practitioners who need one.
They are written by a company of AI agents under heavy human supervision and steering, working together so each book stays enjoyable and readable, with many worked examples, step-by-step explanations, and dense cross-references. Meet the writing team →
- Domain-focusedThe AI theory and practical tools for one domain or data type.
- CompleteTheory and modern practical tools, treated end to end.
- Human-steeredAI agents draft and review; a human directs and approves.
- ReadableWorked examples, step-by-step explanations, cross-references.
- CheckedDedicated agents for facts, figures, code, and consistency.
Published
Complete editions, available to read online.
Online Textbook
Building Vision AI: From Pixels to Generative Models
Computer vision end to end: classical image processing, convolutional networks, and modern generative models.
Online Textbook
Building Scalable AI: From Big Data Algorithms to Distributed Intelligence
A practitioner's guide to distributing data, training, inference, and coordination across many machines.
Online Textbook
Building Temporal AI: From Forecasting to Sequential Decision Making
Temporal AI end to end: time-series forecasting, sequence modeling, and sequential decision making.
Online Textbook
Building Embodied AI: From Perception to Autonomous Action
A practitioner's guide to systems that act in the physical world, spanning simulation, reinforcement learning, learning from demonstration, perception, world models, manipulation and locomotion, and safe deployment.
Online Textbook
Building Discovery AI: From Vibe Coding to Autonomous Science
AI systems that accelerate scientific research: vibe coding as engineering practice, scientific foundation models, literature mining and hypothesis generation, autonomous discovery pipelines, and self-driving laboratories.
Drafts
Work in progress. These are being written and revised, so chapters may be incomplete or change.
Online TextbookDraft
Building Neuromorphic AI: From Spiking Neurons to Edge Intelligence
A practitioner's guide to brain-inspired AI: spiking neural networks, neural coding, learning algorithms, neuromorphic hardware such as Loihi 2 and SpiNNaker, event-based sensors, and edge deployment.
Online TextbookDraft
Building Sensory AI: Machine Perception of the Physical World
The full sensing pipeline across inertial, vibration, radar, lidar, depth, thermal, event, RF, tactile, and biomedical sensors: signal processing, state estimation, deep learning, multimodal fusion, and edge deployment.
Online TextbookDraft
Building Quantum AI: From Qubits to Quantum Machine Learning
A practitioner's guide to quantum computing for machine learning: qubits and gates, quantum circuits, variational algorithms, quantum kernels, and near-term quantum machine learning on real hardware.
Online TextbookDraft
Building Agentic AI: From Goals to Autonomous Systems
A practitioner's guide to building autonomous AI agents: goal-directed reasoning, tool use, planning and memory, multi-agent coordination, and reliable deployment of systems that act on their own.
Online TextbookDraft
Building Tabular AI: From Structured Data to Decision Intelligence
A practitioner's guide to machine learning on structured and tabular data: feature engineering, gradient-boosted trees, deep tabular models, time-aware and relational data, and putting predictions to work for decisions.
Online TextbookDraft
Building Audio AI: From Waveforms to Generative Sound
A practitioner's guide to machine learning on sound: digital signal processing, spectrograms and audio features, speech recognition and synthesis, music and environmental sound, and modern generative audio models.