Website Nautilus has an entertaining and well-researched long story about the history of humanity’s attempts to make sense of the huge mass of data that we have collectively produced, starting with the work of Belgian librarian Paul Otlet, who in the early 1900’s set out to classify and index all human knowledge into one huge networked database. Apparently, “big data” was a hot topic a century ago as well…
Otlet's Universal Bibliographic Repertory [1]
By Zinneke - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=4427401
After having a near-fatal accident falling off his horse, Prussian footman Hans Berger (1873—1941) was surprised to learn that his sister had—being kilometers away—him a telegram to let him know that she sensed he was in grave danger.
How can one hope to understand the precise structure of a virus if it is able to become unrecognizable within weeks? The mathematics behind this questions didn't let go of my mind for extensive periods of time during my PhD studies in Belgium.
One of the main building blocks of modern AI-tools are artificial neural networks, abstract models inspired by the structure and functions of biological neural networks which enable machines to "learn". In this article, I will discuss some thoughts on this topic.
