  Over the past decade, AI has made a remarkable progress. It is agreed that
this is due to the recently revived Deep Learning technology. Deep Learning
enables to process large amounts of data using simplified neuron networks that
simulate the way in which the brain works. However, there is a different point
of view, which posits that the brain is processing information, not data. This
unresolved duality hampered AI progress for years. In this paper, I propose a
notion of Integrated information that hopefully will resolve the problem. I
consider integrated information as a coupling between two separate entities -
physical information (that implies data processing) and semantic information
(that provides physical information interpretation). In this regard,
intelligence becomes a product of information processing. Extending further
this line of thinking, it can be said that information processing does not
require more a human brain for its implementation. Indeed, bacteria and amoebas
exhibit intelligent behavior without any sign of a brain. That dramatically
removes the need for AI systems to emulate the human brain complexity! The
paper tries to explore this shift in AI systems design philosophy.
