Deep Learning for AI

RESEARCH ON ARTIFICIAL neural networks was motivated by the observation that human intelligence emerges from highly parallel networks of relatively simple, non-linear neurons that learn by adjusting the strengths of their connections. This observation leads to a central computational question: How is it possible for networks of this general kind to learn the complicated internal representations that are required for difficult tasks such as recognizing.

Automated summary

Research on artificial neural networks is motivated by the observation that human intelligence emerges from parallel networks of simple non-linear neurons, leading to the question of how these networks can learn complicated internal representations.