Abstract
Creating machines that can think and act just like humans has fascinated humanity for millennia. Breakthroughs of scientific and technological developments in the past century, which demonstrate rapidly accelerating pace in recent decades, allow us now to build computers and robots that parallel or even surpass human abilities in some respects. This is the era of new Artificial Intelligence (AI) with Deep Learning (DL) exploiting very big databases and requiring massive computational resources. It is a fundamental question whether the new AI could benefit from lessons learnt from human brains and human intelligence, or machine intelligence may develop better without considering human experiences and constraints. In this chapter we analyze various aspects of biological and artificial intelligence. We introduce a balanced approach based on the concepts of complementarity and multistability as manifested in human brain operation and cognitive processing. This approach provides insights into key principles of intelligence in biological brains and helps building more powerful artificially intelligent devices.
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