Deep Learning is the next big thing in Artificial Intelligence – does this kill off the white collar worker?
Firstly, let’s discuss the difference between machine learning and deep learning. Both are important adjuncts to Artificial Intelligence or AI. Machine learning was the first spin off. The idea was to teach a computer to identify objects by teaching it – via human beings – through metaphors. So if you wanted the machine to learn what a cat looks like then a human showed it a picture of a cat. It doesn’t scale very well.
Then there is Deep Learning (Google acquired British deep learning business DeepMind in 2014 for a trivial $500 million). There are a lot of companies out there attempting to develop this, including British company WeSee.
Deep learning is essentially unassisted learning.
In 2011, Stanford computer science professor Andrew Ng founded Google’s Google Brain project, which created a neural network trained with deep learning algorithms. It became famous after it proved to be capable of recognizing high level concepts, such as cats, after watching YouTube videos, and without ever having been told what a cat is.
Last year, Facebook named computer scientist Yann LeCun as its new director of AI Research. He has been tasked with using deep learning expertise to help to create solutions that will better identify faces and objects in the 350 million photos and videos uploaded to Facebook each day.
Of course, this provides major advertising revenue opportunities for Google, which is Facebook’s largest revenue stream.