Should the constraints of the human brain inform how we design artificial intelligence? In this essay, Danyal Akarca explores how our growing understanding of neuroscience is inspiring new paradigms at the forefront of AI research following his recent publication in Nature Machine Intelligence.

It is now over a century since the father of modern neuroscience, Ramón y Cajal, proposed that animal nervous systems are organised according to three very general principles: material, space and time. These principles tell us that animal brains conserve their material to prevent unnecessary energy expenditure, space to optimise the physical arrangement of cells within a finite volume, and time to enable rapid and effective communication that facilitate action.

Understanding general principles like these within neuroscience gives us context for how, in living organisms existing in the animal kingdom, various flavours of biological intelligence can evolve and develop. Of course, these are not the only principles at play – neuroscience has advanced tremendously the last hundred years – but such principles are useful because they sharpen our understanding of the various physical factors that commonly constrain the emergence of intelligent behaviour in biology. But can principles of brain organisation and function, such as these proposed by Cajal, inspire new advances at the forefront of artificial intelligence (AI)?