We are surrounded by information. While it can be easy to focus on individual data points, smart decisions require perspective. We created these unique works of art using data from important events in the trading industry and various components of our enterprise risk platform.
Each work of art began as data sets which were transformed into pixels by running different geometric calculations. Then, a series of functions helped ‘paint’ the piece in its entirety.
The results showcase the beauty and complexity of the market.
Order and Abstraction:
A brief history of algorithmic art
An algorithm is defined by Merriam-Webster as “a step-by-step procedure for solving a problem or accomplishing some end.” Although algorithms are most commonly associated with modern digital functions like search engines and streaming services, they have been used in some form for centuries, especially in association with the practices of mathematics and architecture. As early as 1600 BC, the Babylonians were developing algorithms used for factorization and finding square roots, and Euclid – the Greek mathematician – produced a famous algorithm around 300 BC for computing the greatest common divisor of two numbers. The actual term ‘algorithm’ is said to originate from a 9th Century Persian mathematician known as “the father of Algebra.” The term “algorism” was coined to refer to Latin translations of his arithmetic rules. Around the 18th century “allegorism” became the modern “algorithm.”
The birth of “the modern algorithm” occurred during the mid to late industrial revolution, with Alan Turing’s “Turing Machine” being one of the most notable examples, used to decrypt coded German messages during WWII. With the rise of computers, algorithms have become an integral part of modern life. From Google searches to social media feeds to genetic research, algorithms help us find our way around the digital world.
The Human Touch
Algorithms tend to be deterministic – meaning their repeated execution produces identical results. For this reason, algorithms are simply tools. A great mathematical equation, piece of architecture or work of art created with these tools relies on the introduction of an outside factor to modify the outcome. This can be in the form of a random number generator, an external body of data, or instructions supplied by a human being. The relationship between human and computer can be explored through the concept of algorithmic art (also known as generative art). Some of the earliest examples of computer-generated algorithmic art were created in the 1960s by artists such as Georg Nees, Frieder Nake and Michael Noll. The programs created by these artists would supply the instructions and variables to the algorithm, and ranged from highly- controlled to highly-random experimentation. In 1970, Sonia Landy Sheridan established Generative Systems as a program at the School of the Art Institute of Chicago, further controlled to highly-random experimentation. In 1970, Sonia Landy Sheridan established Generative Systems as a program at the School of the Art Institute of Chicago, further exploring the relationship between the algorithm and the human hand.
The Intersection of Art and Data
Data may be invisible, but its presence in modern life looms large. Much of the time, the scale is too big and the pace is too fast to absorb all of it without developing new techniques for understanding. One of these techniques is the practice of representing data in a visual form. By helping reveal the shape, trajectory, and relationships between all of these data points, the people working in this space help us understand how technology can be utilized to expand the boundaries of what is possible, and move society forward.