From the Tiniest Creature,

to the Biggest Mammal:

Evolution, Learning, Bioinformatics

According to Theodosius Dobzhansky, “Nothing in Biology Makes Sense Except in the Light of Evolution” (Dobzhansky 1964). Evolution links all species from the tiniest creatures to the biggest mammals. Can Evolution learn? And how does language evolve and get learned, in particular across species? Can we link Noam Chomsky’s theory of innate capacity for language (Chomsky 1957) with Dobzhansky’s view of evolution?
Over the last few years, deep learning and artificial intelligence have made enormous progress and became leading methods across scientific disciplines. In particular, AI approaches are making enormous inroads in mining biological data and predicting structures of macromolecules.  Apart from the practical applications, profound similarities have been found to exist between the theory of learning, adaptive evolution in biology and thermodynamics. The progress of AI has been paralleled by a quiet revolution in understanding biology, from biological diversity, particularly, of prokaryotes and viruses, to disease spread and progression, thanks to the unprecedented progress of bioinformatics and genomics.
In this mini-workshop, with world figures from Evolution and Mathematical sciences, we highlight a few aspects of these diverse themes in the hope that some sense of unity emerges from imperative combination.