This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since the early days of artificial intelligence, computer scientists have been dreaming of creating machines that can see and understand the world as we do. The efforts have led to the emergence of computer vision, a vast subfield of AI and computer science that deals with processing the content of visual data. In recent years, computer vision has taken great leaps thanks to advances of deep learning and artificial neural networks. Deep learning is a branch of AI that is especially good at processing unstructured data such as images and videos.

We need a lot of data thas a huge drawback. We are learning the representation directly and this is why it works so well. Even in RL, we need a lot of data and this can really be a drawback in every turn. And all supervised learning is backpropagation gradient descent derivative. Even 2005 some good progress were made.

Yann LeCun is Director of Facebook AI Research and Silver Professor at NYU, affiliated with the Courant Institute and the Center for Data Science. He received a PhD in Computer Science from Université P&M Curie (Paris). After a postdoc at the University of Toronto, he joined AT&T Bell Labs, and became head of Image Processing Research at AT&T Labs in 1996. He joined NYU in 2003 and Facebook in 2013. His current interests include AI, machine learning, computer vision, mobile robotics, and computational neuroscience. He is a member of the National Academy of Engineering.

Thomas Hertog reading a comment by Stephen Hawking on the Ethics of Artificial Intelligence Workshop 30 November - 1 December 2016 – One of the key issues today concerns the place of the human person in a growing digital environment of increasing complexity that not only expands the range of his or her capacities, but also may compete with them or even replace them. Over the past fifty years, robots and computers have progressively supplemented humans, initially only in relatively simple computational and manipulation tasks, but more recently in higher cognitive tasks that used to be the prerogative of the human brain, including language, mathematics, probabilistic reasoning and decision making. A crucial question is how to enhance the productive interactions between humans and artificial intelligence (AI). As such interactions reach new orders of complexity, many researchers and philosophers feel that the outcome may defy our understanding and produce radical changes in our personal and social life in the near future.