AboutAI

Sebastian and Gary Marcus take a critical look at modern Machine Learning, asking whether techniques used today will pave the way to our AI future or whether the Deep Learning hype train is just running on hot air. For those new to AI, this episode is a great follow-up to "Ep.1 - AI 101 w/ David Barber" and for those already familiar, enjoy a uniquely in-depth conversation with AI's No.1 Anti-Hype man.

AI is a powerful technology with nearly inconvincible potential. The future of AI is in our hands but we must wield that responsibility properly. What can we do to ensure that AI benefits humanity in the long-term? Sebastian takes a critical look at the big picture with Stuart Russell: one of the world's leading minds in the field of Artificial Intelligence. Dr. Russell authored the most widely used university textbook for AI, and is a Professor of Computer Science and Smith-Zadeh Professor in Engineering at the University of California, Berkeley.

Will AI leave us all jobless? How will society change if that happens? Should we be worried? Sebastian talks to Economist and Futurist Robin Hanson to get some perspective on humanity's relationship with automation, and to ask how we might go about improving social institutions to accommodate future changes. Dr Hanson is an Associate Professor of Economics at George Mason University and a Research Associate at the Future of Humanity Institute of Oxford University. He's written a plethora of books about the present and future of society and economics, and despite receiving push-back, continues to expand the boundaries of his chosen fields through a passion for futurism.

This episode is your introduction to the world of AI! Sebastian asks David Barber all the beginner questions that'll help you understand how AI actually works. Dr. Barber is the Director of the UCL Centre for Artificial Intelligence, as well as being a Professor of Machine Learning at UCL, a Turing Fellow and the cofounder of a spinout from UCL called re:infer. His work involves developing methods to tackle fundamental challenges in Artificial Intelligence; particularly in reasoning under uncertainty and efficient training of AI systems.