Artificial Intelligence(Al) Expert in the World

      The latest developments in the field of AI especially machine learning has ensured that AI stays in the news for all the right reasons. With no sector untouched by the ever-evolving AI, it is quite easy to forget that behind every successful robot there is a clever human.

And to answer your question, here’s my list of best of AI experts in the world. These are the movers ‘n’ shakers of the AI world whose breakthroughs in machine learning has proved to be fundamental in developing the digital tools and technologies.

So without a further ado, here’s my list of the best AI experts

Andrew Ng: If you are an AI enthusiast then you must know that he is one of the most respected AI minds in the industry. Co-founder of the online educational program organization Coursera, Andrew Ng is one of the most prominent minds in machine learning and deep learning. He’s a co-founder of the Google Brain team and previously led the AI group at Chinese internet company Baidu, which is considered to be the equivalent of Google in China. Presently, he is an adjunct professor at Stanford University.

Demis Hassabis: Co-founder of Deep Mind, a UK AI startup acquired by Google in 2014 Demis Hassabis’ work focused on the development of artificial neural networks by combining machine learning with neuroscience. Deep Mind’s most publicized success so far has been its AlphaGo AI, which last year became the first computer program to beat a professional human Go player. Before this breakthrough, even the best AIs were only capable of playing at the level of human amateurs and could be defeated by most people with practice.

Fei-Fei Li: Currently taking a sabbatical to work as chief of AI and ML at Google Cloud, Li is associate professor at Stanford University where she heads the Stanford Artificial Intelligence Lab as director, as well as the Stanford Vision Lab. She has authored over 100 scientific articles on subjects ranging from computational neuroscience to visual recognition and Big Data and her work on the ImageNet project – a database of images designed for training deep learning image recognition algorithms – is widely recognized.