Learning AI From Bacteria

What if Earth’s simplest organisms were also the smartest? What if we could learn new computational methods from them? Biomimicry is the adoption of a biological innovation to solve a biological problem. Neural networks are an example of this as applied to artificial intelligence. Where bacteria are a keystone species, they can do virtually anything. Both intersected greatly in tech innovation and a trained biologist, this area really excites me! I’m launching a literature review whereby I look at research with bacteria that could inform the way we pursue artificial intelligence.

Our Tiny Cousins

Photo of E. coli bacteria.
Micrograph of E. coli bacteria. E. coli is a commonly used model organism in biology research. Photo credit: NIH.

Bacteria are the simplest organisms on the planet. They form the lowest branch on the shrub of life. Ancestral bacterial cells probably were not the first life on the planet, but they surely are an early lineage. They are single celled and lack organelles (complex internal structures) but they are ubiquitous: found at the bottom of the oceans, in the hottest thermal pools, in the coldest corners of Antarctica, inside nuclear reactors, and more.

Uniquely Suited

Bacteria have special powers that make them well suited for this type of study. There is tremendous diversity of species, meaning a variety of genes to work with. They replicate fast. Many species can trade genes and acquire genes from their environment (packed into circular molecules called plasmids), and these capabilities can be used to add genes artificially. For there many properties, bacteria are already used industrially (e.g.: consuming wastes) and medically (e.g.: detecting carcinogens with the Ames test).

My Plan

This series of posts will explore current research in biomimicry and bacteriology as they relate to computers and AI. Posts will go up intermittently, about once every two weeks.

© Peter Roehrich, 2017