1766: John Dalton is born

On 6 September 1766, John Dalton was born in Eaglesfield, England. A Quaker schoolteacher with little formal education, Dalton would become one of the founders of modern chemistry through his atomic theory.

In the early 1800s, Dalton proposed that all matter is composed of indivisible atoms, that atoms of a given element are identical, and that chemical compounds are formed by the combination of atoms in simple whole-number ratios. His 1808 book A New System of Chemical Philosophy laid out these ideas, backed by careful measurements of gas pressures and chemical reactions. Though later refined by the discovery of subatomic particles, Dalton’s framework turned chemistry from a qualitative craft into a quantitative science.

Why does this matter for artificial intelligence? The digital computers that run today’s AI systems are physical devices built from semiconductors, metals and insulating materials whose behaviour is governed by the properties of atoms and electrons. Understanding atomic structure made possible the development of quantum mechanics, solid-state physics and ultimately the transistor—the basic switch of all modern computing. Without a reliable theory of matter, there would be no integrated circuits, no GPUs, and no large-scale neural networks.

Dalton also kept meticulous weather diaries for 57 years, illustrating the value of systematic data collection—an attitude that resonates with the data-driven methods of machine learning. His studies of colour-blindness (he was himself colour-blind) further showed how careful observation of human perception can yield scientific insight, a thread that continues in today’s work on computer vision and cognitive modelling.

From a humble birth on this day in 1766 to the silicon chips powering ChatGPT and autonomous robots, Dalton’s atoms remain the invisible foundation. Every time an AI model performs a matrix multiplication on a GPU, it is ultimately manipulating the behaviour of countless atoms whose existence Dalton first made scientifically rigorous.