
As the senior managing director of a technology firm that employs algorithms in their most complex forms, I spend a lot of time trying to explain, via nature-centric analogies, how these formulae work. The most cutting-edge algorithms are known as “genetic algorithms,” because they self-adapt their “recipes” through interactions with a wider environment of stimuli, thereby approximating evolutionary responses found in nature. The hardest part about explaining that to people comes from overcoming their bias toward unnatural silicon solutions, as opposed to the carbon-based pathways of discovery and adaptation through failure that define our human existence. Oddly enough, people tend […]