Long before the first computer, the first line of binary code or even the first vacuum tube entered our lives, there was a dream: to create a being that thinks and acts like a human without being made of flesh and blood. To truly understand where today’s artificial intelligence is heading, it is worth going back to antiquity and discovering how this fundamental idea was born in myths and legends.
When we think about the origins of AI, we picture research labs, yet its real roots lie in ancient epics. In Greek mythology, Hephaestus, the god of fire and the forge, was in effect the first “engineer” to build autonomous machines. The most famous of his works was Talos, a giant bronze guardian who patrolled the shores of Crete. Talos was not a biological being but an ancient automaton powered by “ichor,” the divine fluid that flowed through his veins and gave him his strength. Hephaestus also built golden handmaidens endowed with a voice and the ability to think, and, together with the other gods, he created Pandora out of clay, “programming” her ultimate purpose in the mortal world.
Strikingly similar ideas, ones that point straight to today’s programming, appear in the Jewish legend of the Golem. In sixteenth-century Prague, Rabbi Judah Loew formed a mighty guardian out of clay and brought him to life with something like an ancient “boot code”: the Hebrew word “Emet” (truth) written on his forehead. Most fascinating of all, deactivating this living matter took nothing more than erasing the first letter on his forehead. That changed the command to “Met” (death) and turned the Golem back into a useless lump of clay. It is a piercing metaphor, a reminder that centuries ago people already understood perfectly well that the right instruction can give matter the form of intelligence.
The fascination with creating artificial life is therefore by no means a digital invention. It is humanity’s age-old desire to transcend its own limits and, for a moment, take on the role of creator. The ancient myths preserved in our culture asked exactly the same questions that keep AI researchers up at night today: what thinking really is, and how to stay in control of what we create.