“THALES<\/b>” is a Deep Neural Network (DNN)<\/b> that was developed entirely by the Hellenic Industrial Property Organisation (OBI), specifically within the Search Directorate, by a team of scientific experts with knowledge or studies in the field of Artificial Intelligence (AI).<\/b><\/p>\n
In very general terms, a Neural Network<\/b> attempts to mimic the functioning of the human brain, which is composed of billions of neurons<\/b> interconnected in a dense network along connections called Synapses.<\/b><\/p>\n
After long-term testing tailored to the technical\/scientific texts of Patent Applications, the team arrived at an architecture that, without going into technical details, includes a total of 483 neurons (or units)<\/b> distributed across 5 hidden layers<\/b>, with a total of 31 million trainable parameters.<\/p>\n
The goal of developing “THALES” was to automate the initial review<\/b> and classification process<\/b> of incoming patent applications based on the technical\/scientific field they relate to, and to subsequently route\/assign<\/b> them to the appropriate examining departments of OBI. This process used to take the working team several days to complete.<\/p>\n
Today, “THALES” has fully replaced the previous working team, and the entire process of reviewing and assigning new patent applications now takes only 2-3 minutes.<\/p>\n