When I hear someone suggest that AI was “invented” with ChatGPT, I’ll admit, a part of me cringes. It’s not a philosophical stance I can articulate or a logical argument I’m prepared to debate on the spot. It’s more of a gut reaction, a sense of indignation that something so rich, so complex, and so deeply rooted in human history could be reduced to a single, recent development. And that, dear reader, is precisely why I feel compelled to embark on this journey with you.

The human imagination has long been captivated by the prospect of creating intelligent entities. From the mythical golems and automatons of antiquity to the sophisticated androids of modern science fiction, the desire to imbue inanimate objects with life and thought reflects a deep-seated curiosity about the nature of existence and the boundaries of creation.¹ The “invention” of artificial intelligence (AI) is not a singular event attributed to one individual or a specific date; rather, it represents a continuous, multidisciplinary journey spanning centuries of philosophical inquiry, mathematical innovation, and technological advancement. This report traces the intricate story of AI’s genesis, exploring its conceptual origins, the foundational computational breakthroughs, its formal establishment as a field, periods of both rapid progress and challenging setbacks, and its contemporary resurgence.

A Journey Through the History of AI

Over the next six posts, we’ll unravel the true story of artificial intelligence, stretching far beyond the current headlines. We’ll explore the fascinating evolution of AI, from its earliest conceptual stirrings to the powerful technologies we see today.

• Part I: The Deep Roots – Philosophical and Logical Foundations:
  The conceptual origins of AI trace back to ancient philosophical inquiries into intelligence and the development of formal logic by figures like Aristotle, Leibniz, and Boole, which provided the abstract framework for machine reasoning.
• Part II: The Seeds of Computation – From Theory to Machine:
  The theoretical groundwork for machine intelligence was laid by Alan Turing’s computational models, followed by the practical development of early computing hardware and software, and influenced by the interdisciplinary field of cybernetics.
• Part III: The Formal Birth – Dartmouth and the Coining of “AI”:
  The field of artificial intelligence was formally established at the 1956 Dartmouth Summer Research Project, where the term “artificial intelligence” was coined, unifying ambitious goals for machine simulation of human intellect.
• Part IV: Early Triumphs and Symbolic AI’s Golden Age:
  Following its inception, AI saw early successes with symbolic programs like Logic Theorist and expert systems, though initial enthusiasm for neural networks like the Perceptron was curtailed by identified limitations.
• Part V: The AI Winters – Challenges, Critiques, and Retrenchment:
  Periods known as “AI winters” occurred due to over-optimistic predictions, practical computational barriers like combinatorial explosion, and philosophical critiques that challenged the fundamental assumptions of machine intelligence, leading to significant funding cuts.
• Part VI: The Resurgence – Data, Deep Learning, and the Modern Era:
  AI experienced a powerful resurgence driven by the revival of neural networks (especially with backpropagation), the availability of vast datasets, and exponential increases in computational power (like GPUs), leading to breakthroughs in deep learning and large language models.

Join me as we uncover the true depth and breadth of AI’s incredible story, proving it’s far more than just a recent phenomenon.

References used through the whole journey

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2. The History of AI: From Turing to Generative AI Models – Robert F. Smith, accessed on July 1, 2025, https://robertsmith.com/blog/the-history-of-ai/
3. What Is Artificial Intelligence (AI)? | IBM, accessed on July 1, 2025, https://www.ibm.com/think/topics/artificial-intelligence
4. A brief history of AI | Tech Tonic – Medium, accessed on July 1, 2025, https://medium.com/deno-the-complete-reference/a-brief-history-of-ai-0d495513f5c3
5. From Cybernetics To Machine Learning: The Evolution Of Self-Regulating Systems, accessed on July 1, 2025, https://quantumzeitgeist.com/from-cybernetics-to-machine-learning-the-evolution-of-self-regulating-systems/
6. CYBERNETICS: A Definition – University of Oxford Department of Computer Science, accessed on July 1, 2025, https://www.cs.ox.ac.uk/activities/ieg/e-library/sources/cyber-macmillan.pdf
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8. en.wikipedia.org, accessed on July 1, 2025, https://en.wikipedia.org/wiki/Dartmouth_workshop
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12. The Perceptron Paradox: How Minsky and Papert Exposed the Limits of Early AI – Medium, accessed on July 1, 2025, https://medium.com/@inamdaraditya98/the-perceptron-paradox-how-minsky-and-papert-exposed-the-limits-of-early-ai-78f93f450dc6
13. Perceptrons (book) – Wikipedia, accessed on July 1, 2025, https://en.wikipedia.org/wiki/Perceptrons_(book)