"The Anatomy of the Nervous System, from the Standpoint of Development and Function," (Illustration: Santiago Ramon y Cajal, c. 1920)

The first computers were not invented by humans but by nature. The mantra of complexity science — that complexity arises from interactions among simple components — is wrong. The parts — whether cells, neurons, bees, or humans — are often wonderfully complex themselves but operate under many constraints and are prone to failure and myopia and, consequently, errors in information processing that can lead to a profound misunderstanding of the nature of reality. In this public lecture, Jessica Flack will discuss how nature computes. She will build on the above points to argue collective computation — computation by the parts together — evolved as a solution to imperfect information processing, sometimes resulting in recovery of the “ground truth out there in the world” and sometimes resulting in a collectively constructed reality that takes on a life and meaning of its own. Flack will also discuss how an understanding of computation in nature challenges us to broaden our understanding of computation’s theoretical foundations.

All things are words belonging to that language / In which Someone or Something, night and day, / Writes down the infinite babble that is, per se, / The history of the world. And in that hodgepodge / Both Rome and Carthage, he and you and I, / My life that I don’t grasp, this painful load / Of being riddle, randomness, or code, / And all of Babel’s gibberish stream by.

-Jorge Luis Borges, two stanzas from his poem, The Compass

Flack is a professor at the Santa Fe Institute and director of its Collective Computation Group. Flack’s interests include the role of collective computation in the origins of biological space and time, coarse-graining in nature, causality, and robustness. 

Watch the video:

Watch some of the highlights:

11:00           Computers in nature

11:15           The concept of the circuit

12:30           Gene regulatory circuits in animals

16:00           How the brain computes – collective computation      

20:57           Why compute?

23:30           Collective concepts in biology

24:15           Information processing to produce order in biology

30:00           Error in biological systems and effective theory

32:50           The value and tenets of collective intelligence

37:15           Approaches to computation in nature

44:50           Attempts to prove the brain is an algorithmic computer

48:00           Fundamental mechanics in developing a theory of computation in biology

50:10           Questions to answer in computational biology

52:50           Architecture of collective computation

55:00           Monkey behavior as an example of collective computation

1:01:50        Coarse-graining – emphasizing the essence of a concept, not the details

1:06:05        Macaque behavior as an example of collective computation architecture

1:11:02        The principle of individual versus collective encoding

1:12:19        Accumulation versus aggregation

1:15:20        The concept of uncertainty reduction

1:17:08        The ideas that complexity emerges from the interaction of simple components is wrong

1:19:00        The computing device versus computation in physical and biological systems