Organisms and Algorithms

"Organisms and Algorithms" is a collection created based on the evolution of biological organisms, starting from the fundamental forms of life. It explores the synchronicity of an evolutionary journey from single-celled organisms to algorithmic systems.

This collection consists of generated and distorted visuals of single-celled organisms. As the creator, my aim is to emphasize the synchronicity between the systems of nature and technology. The complexity theories of Edgar Morin, the morphogenesis studies of Alan Turing, and Stuart Kauffman's concept of self-organization are the primary inspirations for this collection.

Single-Celled Organisms

Single-celled organisms, the most fundamental and ancient forms of life, are the starting point of biological evolution. Prokaryotes represent the initial steps of this evolution, appearing approximately 3.5 billion years ago. Prokaryotes are simple microorganisms without a cellular nucleus.

Single-celled eukaryotes, on the other hand, possess a cell nucleus and organelles, making their cell structures more complex. For instance, Euglena (Euglena gracilis) has characteristics of both plants and animals; it can photosynthesize and, when necessary, feed on organic matter. Amoebas (Amoeba proteus) are known for their ability to change shape, moving with pseudopodia and ingesting food through phagocytosis.

While these might seem like simple high school biology facts, the knowledge they hold leads to far greater implications than their familiarity suggests.

These single-celled organisms laid the foundational stones of biological diversity, paving the way for the evolution of more complex life forms. Their genetic and biochemical mechanisms form the basis of today's multicellular organisms and ecosystems (Chaosmos).

"Even in the most physical sciences, there is an anthropo-social dimension." - Edgar Morin

The visual existence of organisms is also possible through an evolutionary process. As we perceive the existence of this unseen reality through technology, Alan Turing enables us to understand organisms through algorithms. Alan Turing's work "The Chemical Basis of Morphogenesis" explains how biological patterns are formed through chemical and mathematical processes. Turing modeled biological morphogenesis processes with reaction-diffusion systems, demonstrating how natural patterns and forms emerge spontaneously. While the reaction-diffusion model shows how order and complexity arise in biological systems, machine learning algorithms reveal similar order and complexity in data analysis and prediction processes. These similarities help us understand the deep connections and synchronicities between nature and technology.

Biological systems and technological algorithms share similarities in complexity and adaptation processes. The evolutionary processes of living beings in nature parallel the development of machine learning and artificial intelligence algorithms.

According to Heidegger, technology can lead to an unnatural transformation of nature and humanity. However, it appears that technology is also evolving naturally.

Machine learning is the ability of computers to learn and make predictions from data. Deep learning, using multi-layered neural networks, learns complex data and relationships. Neural networks are mathematical models of biological synapses: inputs, weights, biases, and activation functions are processed to produce results.

"Humanity is a result of biological evolution and cultural transformation; technology is a natural extension of this process." - Edgar Morin

Ecosystems are complex networks where living organisms interact with their inanimate environments. Similarly, artificial intelligence and complex systems self-organize through the interaction of many independent components. In both cases, organisms are creating their algorithms.

"Finding order in the midst of chaos is the essence of self-organization." - Stuart Kauffman

The concept behind "Organisms and Algorithms" was realized to witness the deep connections in my mind between nature and technology, and their journey from simplicity to complexity.

The generated visuals exist for viewers to explore the synchronicity between "nature-technology" and how they parallel each other through "simple-complex" systems.