Patterns

The universe is chaotic. Within the chaos there are patterns. These patterns are due to emergent properties of relatively simple rules underlying the unimaginably complex interactions of matter. Patterns can be found almost anywhere in nature, from the organization of stars and galaxies to the symmetry of ice crystals in a snowflake. This phenomenon is not unique to nature; incredibly complex patterns can be observed by applying very simple rules such as in the Mandelbrot set or in cellular automata. These emergent properties are also responsible for the origin of life on Earth and the evolution which guides it.

M74 Spiral Galaxy

Life is a striking example of the organization of matter. When suitable chemical and physical conditions arose in early Earth, organic compounds eventually organized themselves into a form allowing self-replication. Natural selection takes advantage of patterns in an organism's environment to gradually optimize its suitability for a particular environment. This process has lead to the huge variety and complexity of life forms seen today. The process of evolution has also created patterns within its creations, such as the fractals seen in Romanesco broccoli. Intelligent biological systems have evolved to actively recognize and exploit the patterns in their environment in order to gain an evolutionary advantage. Learning from the success of biological cognition may help in the pursuit of creating truly intelligent machines.

Aloe Polyphylla

A crucial step in designing an intelligent machine is understanding the fundamental ways in which patterns are organized in nature. The ability to accurately predict and complete patterns allows a system to act intelligently in its environment. In order to make predictions about patterns a machine needs to be capable of learning from past experiences and recognizing both spatial and temporal patterns. Almost all current neural network techniques are only capable of detecting spatial patterns and cannot detect patterns through time. The fact that the human brain is capable of intelligence provides proof that intelligence is possible given limited computational resources, giving hope that computational intelligence may be achieved in the near future.