When talking about the “AI Revolution” it’s difficult to narrow down a common denominator. This is not only because science fiction didn’t prepare us for our first real encounters with AI, but also due to the many and varied accessions, ranging from hopes to fears.
The AI Revolution is nothing more and nothing less then a rite of passage. But to know, where this journey takes us, requires to know where it started. After about one decade of deep learning it’s time to take stock of progress and review some of the most important milestones and remaining challenges.
The advent of deep learning can be traced back to Geoffrey Hinton’s daredevil science article “Reducing the dimensionality of data with neural networks” (Hinton et al. 2006). It’s contents may kindly be summarized in two essential…