1866: Thomas Hunt Morgan is born

On 25 September 1866, in Lexington, Kentucky, Thomas Hunt Morgan was born into a family of Southern aristocracy whose fortunes had been battered by the Civil War. Few could have guessed that the infant would become one of the founders of modern genetics and, indirectly, a contributor to the intellectual stream that feeds artificial intelligence.

In the laboratories of Columbia University, Morgan turned the humble fruit fly Drosophila melanogaster into the central model organism of genetics. Through meticulous breeding experiments he and his students—Alfred Sturtevant, Calvin Bridges, and Hermann Muller—proved that genes are physical entities arranged linearly on chromosomes. They mapped the first genetic linkage groups and showed how crossing-over shuffles hereditary information. For this work Morgan received the 1933 Nobel Prize in Physiology or Medicine.

The decisive conceptual leap was to treat heredity as the transmission of discrete particles of information. Once genes were understood as coded instructions that could be recombined and mutated, biology acquired an information-theoretic vocabulary. This vocabulary travelled quickly. In the 1940s and 1950s, cyberneticians such as Norbert Wiener and John von Neumann drew explicit analogies between chromosomal mechanisms and the stored-program computer. The same analogy later licensed the invention of genetic algorithms by John Holland and the broader field of evolutionary computation.

Today the thread is everywhere visible in AI:

• Neuroevolution and population-based training optimize neural networks by mimicking selection, crossover and mutation.
• AI systems such as AlphaFold predict three-dimensional protein structures directly from genetic sequence data, a feat unimaginable without the chromosomal theory of inheritance.
• Synthetic biology and AI-driven gene editing rely on the same informational view of life that Morgan established.

A birthday once noted only in family Bibles now quietly commemorates the moment when the idea of information entered biology—and began its long migration into the machines that learn.