  Artificial intelligence is gaining strength and materials science can both
contribute to and profit from it. In a simultaneous progress race, new
materials, systems and processes can be devised and optimized thanks to machine
learning techniques and such progress can be turned into in-novative computing
platforms. Future materials scientists will profit from understanding how
machine learning can boost the conception of advanced materials. This review
covers aspects of computation from the fundamentals to directions taken and
repercussions produced by compu-tation to account for the origins, procedures
and applications of artificial intelligence. Machine learning and its methods
are reviewed to provide basic knowledge on its implementation and its
potential. The materials and systems used to implement artificial intelligence
with electric charges are finding serious competition from other information
carrying and processing agents. The impact these techniques are having on the
inception of new advanced materials is so deep that a new paradigm is
developing where implicit knowledge is being mined to conceive materi-als and
systems for functions instead of finding applications to found materials. How
far this trend can be carried is hard to fathom as exemplified by the power to
discover unheard of mate-rials or physical laws buried in data.
