It was created under the name Institut de recherche en informatique et en automatique (IRIA) in 1967 at Rocquencourt near Paris, part of Plan Calcul. Its first site was the historical premises of SHAPE (central command of NATO military forces). In 1979 IRIA became INRIA. Since 2011, it has been styled inria.
Inria is a Public Scientific and Technical Research Establishment (EPST) under the double supervision of the French Ministry of National Education, Advanced Instruction and Research and the Ministry of Economy, Finance and Industry.
New research explains why so many biological networks, including the human brain (a network of neurons), exhibit a hierarchical structure, and will improve attempts to create artificial intelligence.
The study, published in PLOS Computational Biology, demonstrates this by showing that the evolution of hierarchy – a simple system of ranking – in biological networks may arise because of the costs associated with network connections.
Like large businesses, many biological networks are hierarchically organised, such as gene, protein, neural, and metabolic networks. This means they have separate units that can each be repeatedly divided into smaller and smaller subunits. For example, the human brain has separate areas for motor control and tactile processing, and each of these areas consist of sub-regions that govern different parts of the body.
But why do so many biological networks evolve to be hierarchical? The results of this paper suggest that hierarchy evolves not because it produces more efficient networks, but instead because hierarchically wired networks have fewer connections. This is because connections in biological networks are expensive – they have to be built, housed, maintained, etc. – and there is therefore an evolutionary pressure to reduce the number of connections.
In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings may also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.