LECTURES

Who will be rich and poor in future? - Michio Kaku

Michio Kaku explains the main reason that will be a key factor in determining which countries will be poor and which will be rich in near future. Countries which only rely on commodities like oil is getting cheaper and cheaper every year but those who depend on intellectual capital, the power of the mind is becoming more and more precious. “First, education. We must educate people for the future, the

Artificial Intelligence Turns Images and Videos into Gold : Fei-Fei Li

Google Artificial Intelligence (AI) Chief Scientist Professor Fei-Fei Li, Director at Stanford Artificial Intelligence Lab, stated that  “Artificial Intelligence Turns Images & Videos into Gold” at Research Symposium 2017 in April 15, 2017. Who is Dr. Fei-Fei Li? Dr. Fei-Fei Li is currently Chief Scientist of AI/ML at Google Cloud, also an Associate Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab and

Architecting Predictive Algorithms for Machine Learning

Machine learning is one of the newest tools in a Data Scientist’s arsenal. In this session, you will learn key architectural principles and frameworks for creating practical approaches to solving the prediction problem. Interactive demonstration of various popular machine learning algorithms based on these principles and frameworks will be included.

The Convergence of Machine Learning and Artificial Intelligence Towards Enabling Autonomous Driving

Brains, Minds, and Machines Seminar Series: Amnon Shashua – Hebrew University, Co-founder, CTO and Chairman of Mobileye The field of transportation is undergoing a seismic change with the coming introduction of autonomous driving. The technologies required to enable computer driven cars involves the latest cutting edge artificial intelligence algorithms along three major thrusts: Sensing, Planning and Mapping. Prof. Amnon Shashua is describing the challenges and the kind of machine learning

Deploying Machine Learning Applications in the Enterprise: Peter Norvig

Peter Norvig is talking about Deploying machine learning applications in the Enterprise. Director of Research at Google Inc., Peter Norvig is a reference in terms of Machine Learning. He’s always looking at the world to re-build it, playing with programs and applications that nowadays have a dominant role in our world. “The world is made of lines” and we can draw anything with it, manually or numerically.  More companies are

Artificial Intelligence Lectures (01-13) - Barbara Hecker, PhD

Artificial Intelligence course introduces the foundation of simulating or crating intelligence from a computational point of view. It covers the techniques of reduction, reasoning, problem solving, knowledge representation, and machine learning. In addition, it covers applications of decision trees, neural Networks, support vector machines and other learning paradigms. Barbara Hecker, J.D., Ph.D. Barbara is an entrepreneur with a passion for teaching. She’s been a Department Chair, Chief Academic Officer and

Artificial Intelligence Complete Lectures (01-23)

Prof. Patrick Henry Winston introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of this course, students should be able to develop intelligent systems by assembling solutions to concrete computational problems; understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering; and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.

Preparing Our Economy for the Impact of Automation & AI: Robert Reich

Professor Reich comes to Google to discuss the impact of automation & artificial intelligence on our economy. He also provides a recommendation on how we can ensure future technologies benefit the entire economy, not just those at the top. Robert Reich is the Chancellor’s Professor of Public Policy at the University of California, Berkeley and Senior Fellow at the Blum Center for Developing Economies. He served as Secretary of Labor

Dr. Harry Shum on the future of AI at the 2017 Future Forum

Before computers can solve our greatest challenges, they must understand us. How can we make the leap from computers that perceive and identify objects or just words to a future where they comprehend and interpret the larger context of our world? How will the task-oriented bots of today evolve to agents that connect with us emotionally and improve our lives and our society? Artificial Intelligence will be the pivotal technology –

The Long-Term Future of Artificial Intelligence

Professor Stuart J. Russell (University of California, Berkeley) delivered a public lecture on Friday 15th May 2015 at the Centre for the Study of Existential Risk on the long-term future of Artificial Intelligence. The news media in recent months have been full of dire warnings about the risk that AI poses to the human race, coming from well-known figures such as Stephen Hawking, Elon Musk, and Bill Gates. Should we be