Join us for this year’s Vienna Gödel Lecture with Nobel laureate and ‘Godfather of AI’ Geoffrey Hinton!

A pioneer in Neural Networks, Artificial Intelligence, and Machine Learning, Geoffrey Hinton’s research has profoundly shaped today’s AI systems. In 2024, he was awarded the Nobel Prize in Physics for foundational discoveries and inventions that enable machine learning with artificial neural networks.

Is AI Like us and will it like us?

At this year’s Gödel Lecture, Geoffrey Hinton will give a brief and biased history of AI and then present a way of visualizing roughly what happens when an AI understands a sentence. It is very unlike translating into some special internal language and much more like folding a protein. He’ll argue that current AIs understand natural language in pretty much the same way as we do, claim that most people have a completely wrong theory of what subjective experience is, and that there is no reason why AIs cannot have subjective experiences.

Given that chatbots understand language in much the same way we do, can have subjective experience in much the same way we do, already know much more than any one person - and will soon be much smarter than us - he will discuss some of the risks of releasing AI agents that were designed to maximize profits. He will also describe a way of reframing the problem of how we can coexist with superintelligent AI.

About Geoffrey Hinton

Geoffrey Hinton received his BA in Experimental Psychology from Cambridge in 1970 and his PhD in Artificial Intelligence from Edinburgh in 1978. He did postdoctoral work at the University of Sussex and the University of California, San Diego, and spent five years as a faculty member in the Computer Science department at Carnegie Mellon University. He then became a fellow of the Canadian Institute for Advanced Research and moved to the Department of Computer Science at the University of Toronto. He spent three years from 1998 until 2001 setting up the Gatsby Computational Neuroscience Unit at University College London and then returned to the University of Toronto, where he is now an emeritus distinguished professor. From 2004 to 2013, he was the director of the program on “Neural Computation and Adaptive Perception,” funded by the Canadian Institute for Advanced Research. From 2013 to 2023, he worked half-time at Google, where he became a Vice President and Engineering Fellow.

Geoffrey Hinton is a fellow of the UK Royal Society, the Royal Society of Canada, the Association for the Advancement of Artificial Intelligence, and a former president of the Cognitive Science Society. He is an honorary foreign member of the American Academy of Arts and Sciences, the US National Academy of Engineering, and the US National Academy of Sciences. He has received honorary doctorates from the University of Edinburgh, the University of Sussex, the University of Sherbrooke, and the University of Toronto. His awards include the David E. Rumelhart prize, the IJCAI award for research excellence, the Killam prize for Engineering, the NSERC Herzberg Gold Medal, the IEEE Frank Rosenblatt medal, the IEEE James Clerk Maxwell Gold medal, the NEC C&C award, the BBVA award, the Honda Prize, the Princess of Asturias Award, the ACM Turing Award, and the Queen Elizabeth Prize for Engineering.

Geoffrey Hinton designs machine learning algorithms. His aim is to discover a learning procedure that is efficient at finding complex structure in large, high-dimensional datasets and to show that this is how the brain learns to see. He was one of the researchers who introduced the back-propagation algorithm and the first to use backpropagation for learning word embeddings. His other contributions to neural network research include Boltzmann machines, distributed representations, time-delay neural nets, mixtures of experts, variational learning, products of experts, and deep belief nets (deep learning). His research group in Toronto made major breakthroughs in deep learning that have revolutionized speech recognition and object classification.

About the Vienna Gödel Lectures

Named after the famous Austrian-American logician, mathematician, and philosopher Kurt Gödel (1906-1978) and introduced in 2013, the annual Vienna Gödel Lectures bring world-class scientists to Vienna. The lecture series illustrates computer science’s fundamental and disruptive contribution to our information society, and investigates how our discipline explains and shapes the world we live in—and thereby, our lives as such.

AI Research & Education at TU Wien Informatics

TU Wien Informatics is at the forefront of advancements in AI, addressing challenges and developing ethical, human-centered, and environmentally sustainable AI systems. We foster research and collaboration across disciplines to advance AI for the benefit of society: The Cluster of Excellence, Bilateral AI (BILAI), brings together two main approaches in AI — symbolic and sub-symbolic AI — with the goal of creating a Broad AI capable of addressing diverse tasks across multiple domains. The Center for Artificial Intelligence and Machine Learning (CAIML) and the Christian-Doppler Laboratories are at the forefront of AI and Machine Learning research, leading efforts to strengthen both in their foundations and applications. Through the Digital Humanism Initiative, we strive for an inclusive, participatory development of technologies that benefit us all. These perspectives also inform AI education at TU Wien. The master’s program in Logic and Artificial Intelligence and the bachelor’s specialization in Artificial Intelligence + Machine Learning provide students with the foundations of AI, and through AI4all, we enable students across disciplines to explore how AI and Data Management methods can be applied across science and engineering effectively and responsibly.