History of artificial intelligence: Birth of AI to LLM and Machine Learning

The history of artificial intelligence (AI) began in antiquity, with myths, stories, and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The study of logic and formal reasoning from antiquity to the present led directly to the invention of the programmable digital computer in the 1940s, a machine based on abstract mathematical reasoning. This device and the ideas behind it inspired scientists to begin discussing the possibility of building an electronic brain.

The field of AI research was founded at a workshop held on the campus of Dartmouth College in 1956.^[1] Attendees of the workshop became the leaders of AI research for decades. Many of them predicted that machines as intelligent as humans would exist within a generation. The U.S. government provided millions of dollars with the hope of making this vision come true.^[2]

Eventually, it became obvious that researchers had grossly underestimated the difficulty of this feat.^[3] In 1974, criticism from James Lighthill and pressure from the U.S.A. Congress led the U.S. and British Governments to stop funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government and the success of expert systems reinvigorated investment in AI, and by the late 1980s, the industry had grown into a billion-dollar enterprise. However, investors’ enthusiasm waned in the 1990s, and the field was criticized in the press and avoided by industry (a period known as an “AI winter“). Nevertheless, research and funding continued to grow under other names.

In the early 2000s, machine learning was applied to a wide range of problems in academia and industry. The success was due to the availability of powerful computer hardware, the collection of immense data sets, and the application of solid mathematical methods. Soon after, deep learning proved to be a breakthrough technology, eclipsing all other methods. The transformer architecture debuted in 2017 and was used to produce impressive generative AI applications, amongst other use cases.

Investment in AI boomed in the 2020s. The recent AI boom, initiated by the development of transformer architecture, led to the rapid scaling and public releases of large language models (LLMs) like ChatGPT. These models exhibit human-like traits of knowledge, attention, and creativity, and have been integrated into various sectors, fueling exponential investment in AI. However, concerns about the potential risks and ethical implications of advanced AI have also emerged, causing debate about the future of AI and its impact on society.

Precursors

Mythical, fictional, and speculative precursors

Myth and legend

In Greek mythology, Talos was a creature made of bronze who acted as guardian for the island of Crete. He would throw boulders at the ships of invaders and would complete 3 circuits around the island’s perimeter daily.^[4] According to pseudo-Apollodorus‘ Bibliotheke, Hephaestus forged Talos with the aid of a cyclops and presented the automaton as a gift to Minos.^[5] In the Argonautica, Jason and the Argonauts defeated Talos by removing a plug near his foot, causing the vital ichor to flow out from his body and rendering him lifeless.^[6]

Pygmalion was a legendary king and sculptor of Greek mythology, famously represented in Ovid‘s Metamorphoses. In the 10th book of Ovid’s narrative poem, Pygmalion becomes disgusted with women when he witnesses the way in which the Propoetides prostitute themselves. Despite this, he makes offerings at the temple of Venus asking the goddess to bring to him a woman just like a statue he carved.^[7]

Medieval legends of artificial beings

In Of the Nature of Things, the Swiss alchemist Paracelsus describes a procedure that he claims can fabricate an “artificial man”. By placing the “sperm of a man” in horse dung, and feeding it the “Arcanum of Mans blood” after 40 days, the concoction will become a living infant.^[8]

The earliest written account regarding golem-making is found in the writings of Eleazar ben Judah of Worms in the early 13th century.^[9] During the Middle Ages, it was believed that the animation of a Golem could be achieved by insertion of a piece of paper with any of God’s names on it, into the mouth of the clay figure.^[10] Unlike legendary automata like Brazen Heads,^[11] a Golem was unable to speak.^[12]

Takwin, the artificial creation of life, was a frequent topic of Ismaili alchemical manuscripts, especially those attributed to Jabir ibn Hayyan. Islamic alchemists attempted to create a broad range of life through their work, ranging from plants to animals.^[13]

In Faust: The Second Part of the Tragedy by Johann Wolfgang von Goethe, an alchemically fabricated homunculus, destined to live forever in the flask in which he was made, endeavors to be born into a full human body. Upon the initiation of this transformation, however, the flask shatters and the homunculus dies.^[14]

Modern fiction

Main article: Artificial intelligence in fiction

By the 19th century, ideas about artificial men and thinking machines became a popular theme in fiction. Notable works like Mary Shelley‘s Frankenstein and Karel Čapek‘s R.U.R. (Rossum’s Universal Robots)^[15] explored the concept of artificial life. Speculative essays, such as Samuel Butler‘s “Darwin among the Machines“,^[16] and Edgar Allan Poe’s “Maelzel’s Chess Player“^[17] reflected society’s growing interest in machines with artificial intelligence. AI remains a common topic in science fiction today.^[18]

Automata

Main article: Automaton

Realistic humanoid automata were built by craftsman from many civilizations, including Yan Shi,^[19] Hero of Alexandria,^[20] Al-Jazari,^[21] Haroun al-Rashid,^[22] Jacques de Vaucanson,^[23][24] Leonardo Torres y Quevedo,^[25] Pierre Jaquet-Droz and Wolfgang von Kempelen.^[26][27]

The oldest known automata were the sacred statues of ancient Egypt and Greece.^[28][29] The faithful believed that craftsman had imbued these figures with very real minds, capable of wisdom and emotion—Hermes Trismegistus wrote that “by discovering the true nature of the gods, man has been able to reproduce it”.^[30] English scholar Alexander Neckham asserted that the Ancient Roman poet Virgil had built a palace with automaton statues.^[31]

During the early modern period, these legendary automata were said to possess the magical ability to answer questions put to them. The late medieval alchemist and proto-Protestant Roger Bacon was purported to have fabricated a brazen head, having developed a legend of having been a wizard.^[32][33] These legends were similar to the Norse myth of the Head of Mímir. According to legend, Mímir was known for his intellect and wisdom, and was beheaded in the Æsir-Vanir War. Odin is said to have “embalmed” the head with herbs and spoke incantations over it such that Mímir’s head remained able to speak wisdom to Odin. Odin then kept the head near him for counsel.^[34]

Formal reasoning

Artificial intelligence is based on the assumption that the process of human thought can be mechanized. The study of mechanical—or “formal”—reasoning has a long history. Chinese, Indian and Greek philosophers all developed structured methods of formal deduction by the first millennium BCE. Their ideas were developed over the centuries by philosophers such as Aristotle (who gave a formal analysis of the syllogism),^[35] Euclid (whose Elements was a model of formal reasoning), al-Khwārizmī (who developed algebra and gave his name to the word algorithm) and European scholastic philosophers such as William of Ockham and Duns Scotus.^[36]

Spanish philosopher Ramon Llull (1232–1315) developed several logical machines devoted to the production of knowledge by logical means;^[37][38] Llull described his machines as mechanical entities that could combine basic and undeniable truths by simple logical operations, produced by the machine by mechanical meanings, in such ways as to produce all the possible knowledge.^[39] Llull’s work had a great influence on Gottfried Leibniz, who redeveloped his ideas.^[40]

In the 17th century, Leibniz, Thomas Hobbes and René Descartes explored the possibility that all rational thought could be made as systematic as algebra or geometry.^[41] Hobbes famously wrote in Leviathan: “For reason … is nothing but reckoning, that is adding and subtracting”.^[42] Leibniz envisioned a universal language of reasoning, the characteristica universalis, which would reduce argumentation to calculation so that “there would be no more need of disputation between two philosophers than between two accountants. For it would suffice to take their pencils in hand, down to their slates, and to say each other (with a friend as witness, if they liked): Let us calculate.”^[43] These philosophers had begun to articulate the physical symbol system hypothesis that would become the guiding faith of AI research.

The study of mathematical logic provided the essential breakthrough that made artificial intelligence seem plausible. The foundations had been set by such works as Boole‘s The Laws of Thought and Frege‘s Begriffsschrift.^[44] Building on Frege‘s system, Russell and Whitehead presented a formal treatment of the foundations of mathematics in their masterpiece, the Principia Mathematica in 1913. Inspired by Russell‘s success, David Hilbert challenged mathematicians of the 1920s and 30s to answer this fundamental question: “can all of mathematical reasoning be formalized?”^[36] His question was answered by Gödel‘s incompleteness proof,^[45] Turing‘s machine^[45] and Church‘s Lambda calculus.^[a]

Their answer was surprising in two ways. First, they proved that there were, in fact, limits to what mathematical logic could accomplish. But second (and more important for AI) their work suggested that, within these limits, any form of mathematical reasoning could be mechanized. The Church-Turing thesis implied that a mechanical device, shuffling symbols as simple as 0 and 1, could imitate any conceivable process of mathematical deduction.^[45] The key insight was the Turing machine—a simple theoretical construct that captured the essence of abstract symbol manipulation.^[48] This invention would inspire a handful of scientists to begin discussing the possibility of thinking machines.