The AI Revolutions
A journey through the pivotal moments that shaped AI
Artificial intelligence is often described as a sudden revolution. In reality, it was built moment by moment.
The AI Revolutions takes you inside the pivotal breakthroughs that defined artificial intelligence, from its formal birth at the 1956 Dartmouth Conference to the modern era of deep learning, generative models, and autonomous systems. Each chapter focuses on a single turning point: IBM's Deep Blue defeating a world chess champion, AlexNet igniting the deep learning revolution, AlphaGo mastering a game once thought uniquely human, and the rise of large language models that changed how we write, work, and think.
More than a technical history, this book explores why these moments mattered; how they shifted scientific belief, redirected funding, reshaped industries, and altered public perception of what machines could do. It reveals how breakthroughs in algorithms, hardware, data, and ambition converged to create the Age of AI.
Written for technologists, policymakers, students, and curious readers alike, The AI Revolutions is a guide to understanding how we got here and why the next moment may be even more consequential than the last.
The following are excerpts from the forthcoming book, The AI Revolutions.
0 |
The Language of Intelligence Before exploring the story of AI in America, it's helpful to pause and understand the language of AI itself. The field of AI is filled with jargon, acronyms, and shifting meanings. Yet beneath the buzzwords lie clear and powerful ideas that shape the technology transforming our lives. |
1 |
The Question That Started It All Alan Turing publishes his seminal paper proposing the 'imitation game,' a test to determine if a machine can exhibit intelligent behavior indistinguishable from a human. This philosophical foundation shapes all future AI research. |
2 |
Dartmouth, Dreams, and Early Optimism John McCarthy, Marvin Minsky, and colleagues gather at Dartmouth College and coin the term 'Artificial Intelligence.' This summer workshop marks the official birth of AI as an academic discipline. |
3 |
Checkers and the First Learning Machine Arthur Samuel's checkers program. Self-learning before machine learning. Why this moment quietly changed everything. |
4 |
ELIZA Talks Back Joseph Weizenbaum's ELIZA showed that humans emotionally respond to machines. ELIZA was the first conversational AI. |
5 |
Deep Blue vs. Garry Kasparov The 1997 match that shocked the world. Why this was more than a chess game. Public perception shifts overnight. |
6 |
Jeopardy! and the Meaning of Understanding IIBM Watson takes on language. Ambiguity, puns, and context. Why language is harder than logic. |
7 |
AlphaGo and the End of Human Intuition Supremacy Why Go was considered unreachable. Move 37 and the birth of alien intelligence. Creativity without consciousness. |
8 |
The AI Winters Funding collapses and broken promises. Expert systems and their limits. Why AI survived when it failed. |
9 |
Data, Compute, and the Quiet Rebuild What had been a quiet rebuild suddenly erupted into the deep learning revolution, symbolized by AlexNet's 2012 breakthrough. |
10 |
Elon Musk and the Existential Question Fear, acceleration, and OpenAI's origin. AI as promise and threat. Tension between safety and speed. |
11 |
Jensen Huang and the Power of Compute GPUs as the unexpected AI engine. NVIDIA's quiet dominance. Why hardware decided the future. |
12 |
Sam Altman and the
Chatbot Moment From research lab to global product. Scaling intelligence. The moment AI went mainstream. |
13 |
Researchers, Engineers, and the Invisible Army The unsung contributors. Open source vs. corporate labs. Collaboration as a force multiplier. |
14 |
The Chatbot Moment When everyone met AI personally. Natural language as the interface of power. Trust, surprise, and dependency. |
15 |
AI in Science, Medicine, and Discovery Protein folding and drug discovery. AI as a tool for breakthroughs. Acceleration of human knowledge. |
16 |
Creativity, Art, and the Human Line Images, music, and writing. What authorship means now. Why creativity was never just human. |
17 |
Alignment, Safety, and Who Decides Control problems and governance. Corporate power vs. public interest. Can intelligence be steered? |
18 |
Regulation, Nations, and the AI Arms Race U.S., China, and global competition. Chips, models, and geopolitical leverage. AI as national infrastructure. |
19 |
Artificial General Intelligence: Myth or Momentum Definitions and disagreements. Signals we're watching. Why timing matters more than labels. |
About the Author
Roy McNeill brings a soldier's discipline, an engineer's precision, and a philosopher's curiosity to The AI Revolutions. A decorated U.S. Army Combat Engineer Officer who worked on top-secret computer projects, he later designed systems for Microsoft, IBM, General Electric, Siemens, Genentech, Bayer, and more. With degrees from the University of Kentucky, Pepperdine (MBA), and Stony Brook (ABD in Logic and Philosophy), Roy has spent years immersed in AI's evolution - from symbolic roots to generative breakthroughs.
Today, he operates from offices in the San Francisco Bay Area and San Salvador, El Salvador, guiding small businesses to harness AI for real-world advantage. The AI Revolutions is his tribute to the innovation ecosystem that made it all possible - and his mission to keep it thriving.