Montbleau.ca Academic Press
Bookshelf
The Textbook, Reborn for the Pace of Tech.
Being Published
AI Foundation
AI Foundations by Pierre Montbleau is a comprehensive, beginner-friendly yet robust guide to the fundamental concepts, theories, and technologies that drive modern artificial intelligence. The book explores AI through five major pillars—mathematics, computer science, machine learning, logic & reasoning, and cognitive science & neuroscience—showing how each discipline contributes to building intelligent systems.
It introduces readers to essential mathematical tools like linear algebra, probability, calculus, information theory, and optimization, explaining how they support neural networks, deep learning, and decision-making systems. The computer science section covers algorithms, data structures, computational complexity, and optimization strategies crucial for scalable AI systems.
The book dedicates substantial focus to machine learning, walking through supervised, unsupervised, and reinforcement learning, core algorithms, model training, evaluation, and real-world applications. It also examines symbolic AI, knowledge representation, automated reasoning, and probabilistic models, highlighting how logic underpins explainable and structured AI methods.
From a biological perspective, the book draws inspiration from cognitive science and neuroscience to explain the origins of neural networks, reinforcement learning, perception, and decision-making in machines. A full chapter is devoted to AI ethics, addressing fairness, bias, transparency, alignment, accountability, and the philosophical debates around consciousness and AGI.
Throughout, Montbleau connects theory to practice with examples from healthcare, finance, robotics, NLP, autonomous systems, climate modeling, and other domains. Each chapter concludes with summaries, exercises, and practice tests to reinforce comprehension.
In essence, AI Foundations serves as an accessible yet thorough roadmap for students, professionals, and curious readers who want to understand how AI works, why it matters, and how to apply or evaluate it responsibly in the real world.
It introduces readers to essential mathematical tools like linear algebra, probability, calculus, information theory, and optimization, explaining how they support neural networks, deep learning, and decision-making systems. The computer science section covers algorithms, data structures, computational complexity, and optimization strategies crucial for scalable AI systems.
The book dedicates substantial focus to machine learning, walking through supervised, unsupervised, and reinforcement learning, core algorithms, model training, evaluation, and real-world applications. It also examines symbolic AI, knowledge representation, automated reasoning, and probabilistic models, highlighting how logic underpins explainable and structured AI methods.
From a biological perspective, the book draws inspiration from cognitive science and neuroscience to explain the origins of neural networks, reinforcement learning, perception, and decision-making in machines. A full chapter is devoted to AI ethics, addressing fairness, bias, transparency, alignment, accountability, and the philosophical debates around consciousness and AGI.
Throughout, Montbleau connects theory to practice with examples from healthcare, finance, robotics, NLP, autonomous systems, climate modeling, and other domains. Each chapter concludes with summaries, exercises, and practice tests to reinforce comprehension.
In essence, AI Foundations serves as an accessible yet thorough roadmap for students, professionals, and curious readers who want to understand how AI works, why it matters, and how to apply or evaluate it responsibly in the real world.
Writing
From Data to Intelligence -
Building Secure and Adaptive Systems
From Data to Intelligence: Building the Convergent Stack is a practical guide to designing, building, and operating modern data and AI systems. It moves beyond siloed treatments of databases, cybersecurity, data science, and artificial intelligence to explore how these layers integrate into a cohesive stack—the convergent stack.The book is structured as a journey through the layers of intelligence:
1. Database Management: The foundation—how data is stored, versioned, and streamed.2. Data Types: The raw materials—how structure dictates processing and value.3. AI & Machine Learning: The autonomous layer—how models are built, deployed, and integrated.4. Cybersecurity: The protective layer—how intelligent systems are secured.5. Further Layers: Covering orchestration, governance, and human-in-the-loop design.
Each chapter blends theory with practice, featuring real-world cases, interactive exercises, and clear summaries. The book is designed for practitioners—data engineers, scientists, ML engineers, and architects—as well as leaders and students seeking a unified view of the data-to-intelligence pipeline.
Fiction
Shadow in the wire
Shadow in the Wire is a gripping cyber-thriller that follows Ethan Cole, a former hacker dragged back into the world he tried to escape when a devastating cyberattack cripples a global bank. The attack bears the signature of Phantom Cell, a ruthless hacker collective with ambitions far beyond theft—they aim to dismantle the global financial system.
Teaming up with Lena Reyes, a rogue FBI agent with her own shadowy past, and Cipher, a brilliant young hacker driven by a personal vendetta, Ethan races to uncover Phantom Cell’s true motive. As the attacks escalate—from power grids to hospitals—Ethan discovers the mastermind is Orpheus, a legendary hacker from his past he thought was dead. The final revelation shakes him to his core: Orpheus is his ex-fiancée, Anna, who faked her death and now seeks to burn the system to the ground.
In a high-stakes climax, Ethan must confront Anna in a battle that costs lives and sacrifices, ending with her fall but leaving the door open for a new, even more dangerous threat. The novel blends cutting-edge cyber realism with themes of redemption, betrayal, and the haunting weight of the past, setting the stage for an ongoing war in the shadows.
Teaming up with Lena Reyes, a rogue FBI agent with her own shadowy past, and Cipher, a brilliant young hacker driven by a personal vendetta, Ethan races to uncover Phantom Cell’s true motive. As the attacks escalate—from power grids to hospitals—Ethan discovers the mastermind is Orpheus, a legendary hacker from his past he thought was dead. The final revelation shakes him to his core: Orpheus is his ex-fiancée, Anna, who faked her death and now seeks to burn the system to the ground.
In a high-stakes climax, Ethan must confront Anna in a battle that costs lives and sacrifices, ending with her fall but leaving the door open for a new, even more dangerous threat. The novel blends cutting-edge cyber realism with themes of redemption, betrayal, and the haunting weight of the past, setting the stage for an ongoing war in the shadows.