Every day it seems we are hearing of new advances made by AIs thanks to Machine Learning, from improving healthcare to beating us at poker, it is often easy to forget that, behind every successful robot, there’s a clever human.
The swift pace of change we are seeing today is due to a concerted effort across industry and academia to find practical uses for the ever-growing amount of data we are generating and collecting.
So, in this post I am going to highlight some of the current movers ‘n’ shakers, whose breakthroughs in machine learning are proving to be fundamental to developing the digital tools and technologies making AI possible, from social networks to self-driving cars, to the industrial internet.
Andrew Ng
Ng has just resigned from his post as chief data scientist at Chinese online giant Baidu. As well as that he is the founder of the online training resource Coursera and associate professor at Stanford University’s computer science department.
Before joining Baidu he formed Google’s Brain AI research division and his work has focused on deep learning. At Stanford he has led projects including the development of the Stanford Artificial Intelligence Robot (STAIR) as well as algorithms to build 3D digital models from a single flat photographic image.
Yoshua Bengio
Professor at the Universite De Montreal’s department of computer science, Bengio is noted for his research into artificial neural networks and deep learning. He has stated that the overriding ambition behind his research is to understand “principles of learning that yield intelligence.” Among other principles of AI and ML, much of his published work concerns auto-encoders which are used for encoding or formatting unstructured data, to make it understandable by computers via unsupervised machine learning.
Yann LeCunn
As director of AI research at Facebook since 2013, LeCunn has received recognition for pioneering work in the field of computer vision – teaching machines to “see” in the same way we do by recognizing objects and to go on to learn, by classifying them. He is also considered one of the founders of the convolutional neural network model which aims to create algorithms which ingest and interpret information in the same way as a biological organism like an eye or a brain. He is a founding director NYU Center for Data
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