7 - Computers versus brains: Challenges of sustainable artificial and biological intelligence

Abstract

Creating machines that can think and act just like humans has fascinated humanity for millennia. Breakthroughs of scientific and technological developments in recent decades allow us to build computers and robots that parallel or even surpass human abilities in many respects. The superhuman achievements are based on a new generation of Artificial Intelligence (AI) with neural networks using Deep Learning (DL). The performance of these AI systems increases exponentially, which requires exponentially increasing resources as well, including data, computational power, and energy. This development is not sustainable and there is a need for new AI approaches, which give careful consideration to limited resources. In this chapter, we discuss how new AI could benefit from lessons learnt from human brains, human intelligence, and human constraints. We describe 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 it helps building sustainable artificial intelligence.