Dr. Yves J. Hilpisch

A Short History of Computer Science: From Commodore C64 to Cloud AI

A narrative-technical tour of computer science that traces ideas, machines, software, and networks from early calculators and mainframes through home computers and the cloud era, giving readers a coherent map of how modern computing evolved.

HCS Workbook: C64 From Hardware to Pong

A hands-on workbook that pairs with the history book's C64 chapters, guiding you through emulator setup, BASIC and assembly experiments, and building a simple Pong-style game on the Commodore 64.

HCS Manual: VICE C64 Emulator for macOS

A practical macOS guide to the VICE C64 emulator covering installation, configuration, loading software, input settings, and troubleshooting so you can smoothly run the HCS C64 workbooks.

HCS Workbook: AI Chats & Pong in 2025

A companion workbook that mirrors the C64 Pong build using modern AI tools, documenting how large language models help design, code, and iterate a browser-based Pong game.

HCS Workbook: Deep Q-Learning for Pong

A Colab-ready reinforcement learning lab that installs the Atari toolchain, builds a modern DQN agent with replay buffers and AMP, and walks through training, evaluating, and checkpointing a Pong policy.

HCS Workbook: Cellular Automata & Life

A cellular-automata lab for the history book that takes you from the formal definition of Conway’s Game of Life to your own implementations and experiments with patterns, rules, and emergence.

HCS Workbook: Tensors & the AI Revolution

A tensor-focused workbook that connects linear algebra, NumPy, and PyTorch code to the inner workings of modern deep-learning models and hardware, with self-attention built from first principles.

LLM Workbook: Architecture and Breakthroughs Behind Modern Generative AI

A diagram- and code-driven workbook that explains the core building blocks and system-level breakthroughs behind modern decoder-style LLMs, from tokenisation and attention to scaling, inference-time tools, and evaluation.

Introduction to the Philosophy of Science: Concepts, Practice, and Case Studies

A practitioner-friendly introduction to philosophy of science that connects classic debates about induction, falsification, and explanation with today's data-driven research and AI systems, giving quants, engineers, and scientists a toolkit for reasoning about models, evidence, and scientific progress without getting lost in jargon.

POS Lab: Simulation Hypothesis

A Philosophy of Science lab module that turns the Simulation Hypothesis into a structured research dossier exercise, using measurement, evidence, causality, and complexity tools from the main book to evaluate Bostrom-style arguments and real-world implications.

POS Lab: Algorithmic Trading

A lab for quant and philosophy-of-science readers that walks through building and stress-testing an algorithmic trading research pipeline, focusing on measurement error, overfitting, market microstructure, and evidence standards for alpha claims.

POS Lab: Biotech Research

A lab centred on biomarker-guided cancer therapy, guiding readers through measurement, trial design, and failure modes in biotech research while tying each step back to the Philosophy of Science book's frameworks.

Special Relativity: A Self-Contained Introduction with Mathematical Foundations

Builds on the Newtonian volume to introduce Einstein's postulates, spacetime diagrams, Lorentz transformations, and four-vectors in a learner-friendly, fully worked mathematical narrative.

Newtonian Physics: A Self-Contained Introduction with Mathematical Foundations

A from-first-principles tour of classical mechanics that builds the mathematical language alongside the physics. Combines visual intuition, worked examples, and just-enough formalism to make Newtonian ideas concrete for motivated learners across disciplines.

Read the HTML version (e.g. on your phone).

Deep Q-Life: Markov, Bellman, and Habits

Recasts everyday habit building as a compact reinforcement learning problem. Using the MDP lens and the Bellman principle — choose what is good now and sets up good options next — Deep Q-Learning provides a simple loop: try, remember what worked, and refine with weekly reviews. Includes relatable examples and checklists for practical, improvable policies.

Deep Q-Life Sobriety: Applying RL Habit Loops to Alcohol-Free Living

Extends the Deep Q-Life framework into a practical sobriety playbook. Maps alcohol cravings as Markov decision processes, designs replacement policies and experience replay rituals, and adds “soft” success factors such as mindfulness, future-self continuity, and self-compassion. Includes protocols and checklists for navigating high-risk situations and sustaining long-term alcohol-free living.

Download the daily review sheet (PDF)

Deep Q-Life Ownership: Applying RL to Stuff, Spending, and Space

Models purchases, subscriptions, and decluttering through Bellman-style thinking so you can ask, “What action today leaves me with better options tomorrow?” Includes ownership policies, contentment ratios, and replay rituals for lighter, more intentional environments.

Deep Q-Life Happiness: Formalising Joy, Fulfilment, and the Way

Casts joy, pleasure, contentment, and fulfilment as reward channels in a shared RL language, blending science, philosophy, and practice into a toolkit that helps you design a personalized happiness policy rather than chase vague goals.

Cognitive Bias: Thinking About Thinking

A practical, conversational tour of heuristics and bias clusters with self-tests and anti-bias protocols you can deploy in work, relationships, and everyday decisions to catch predictable errors before they cascade.

U-Shaped Personality Traits in High Achievers

Argues that many founders, creatives, and executives display bimodal trait patterns — spending more time at both extremes and less in the middle — and translates this “paradoxical personality” profile into practical guidance for channeling those extremes without burning out.

Take the U-Shape self-assessment (PDF)

Dark Traits in High Achievers and Everyday Life

A narrative-technical overview of the Dark Tetrad — narcissism, Machiavellianism, psychopathy, and sadism — focused on how sharp-edged traits show up in ambitious professionals. Distils measurement and longitudinal research into practical guidance for individuals and leaders, including red-flag patterns that call for clinical support and design principles for roles and environments that minimise harm while harnessing legitimate strengths.

Longevity and Health: From Myths to Proven Protocols

Synthesizes the strongest human evidence for extending healthspan: a Mediterranean-style, protein- and fiber-rich diet, structured aerobic (including Zone 2) and resistance training, 7-9 hours of sleep, and intentional hydration. Completes the protocol with stress-regulation practices and social connection to counter the mortality impact of chronic isolation.

Mitochondria: To Be or Not To Be

A practical, analogy-rich guide to mitochondrial biology and human performance that links ATP production, exercise, nutrition, sleep, stress, and temperature exposure into a coherent, safety-aware framework for improving everyday energy and resilience.

Aspirin: A Layperson's Guide

A practical, non-technical tour of aspirin that explains how this everyday drug eases pain and fever, changes platelet behavior, and can lower clotting risk — while also highlighting side effects, bleeding risks, and why long-term use should always be a personalized, doctor-guided decision.

The Rise of the AI Engineer: From Digital Alchemy to Institutional Advantage

Explains why AI engineers act as modern digital alchemists — fusing data, models, systems, and governance to deliver reliable GenAI advantage — and why institutions must cultivate those capabilities through programs such as The AI Engineer.

Why Coding Skills Still Matter in the Age of AI: Implications for Quantitative Finance

Programming is still the engine of quantitative finance, and GenAI only amplifies — not replaces — the need for precise, testable code, disciplined workflows, and human-in-the-loop guardrails across research, models, and production systems.

The Maestro and the Apprentice: Expertise in the Age of AI

An exploration of human-AI collaboration for quants. Learn how domain mastery and AI copilots combine to accelerate innovation.

The Transformative Impact of AI and Generative AI on Higher Education: A Comparative, Multiregional, and Skills-Based Analysis

A multiregional, comparative study of how AI and GenAI reshape higher education — documenting bottom-up student adoption, uneven institutional policy responses, and the widening AI/quant skills gap — while offering curricular strategies, assessment designs, and partnerships that keep finance programs aligned with modern demands.

Two Tales, One Insight: Today as the Safest Bet for Tomorrow

A twin narrative — one story-driven, one mathematical — showing why, with minimal information, today's value is the statistically safest single-number forecast for both tomorrow's stock price and tomorrow's temperature, linking everyday intuition with conditional expectations and random-walk thinking.