WASP Lighthouse Seminar: Is Information Digital? A Defense of Reality

When: 10 July 2026, 14:00 to 15:00
Where: Teknodromen, M-Hus, Lund
Coffee and fika will be served after the seminar.

Please sign up at survey.mailing.lu.se/Survey/65629 before 3 July.

Data-driven techniques, such as large-language models, have proven astonishingly powerful in recent years, but progress has been much slower with cyber-physical systems such as robots. Many people assume this is because there is not enough training data. In this talk, I explore a possible explanation that is much more fundamental. Specifically, I ask the question of whether there is a fundamental difference between acquisition of knowledge through observation and acquisition of knowledge through embodied interaction. Can you learn to ride a bicycle by watching others ride a bicycle? In previous work, I have used concepts from computer science (zero-knowledge proofs, bisimulation, etc.) to show that there are things you can learn from embodied interaction that cannot be learned by objective observation. In this talk, I use Shannon information theory to argue that objective observation falls far short of revealing everything about physical reality. There is information in the real world that cannot be represented digitally, and objective observation can never acquire more than a small subset of this information. In short, learning to ride a bicycle may require getting on a bicycle, even for a robot.

Edward A. Lee is Professor of the Graduate School and Distinguished Professor Emeritus in Electrical Engineering and Computer Sciences (EECS) at the University of California at Berkeley, where he has been on the faculty since 1986. He is also co-founder of Xronos Inc. and BDTI, Inc. He is the author of seven books, some with several editions and translations, including two for a general audience, and hundreds of papers and technical reports. Lee has delivered hundreds of keynotes and other invited talks at venues worldwide and has graduated 40 PhD students. Image Professor Lee’s research studies cyber-physical systems, which integrate physical dynamics with software and networks. His focus is on the use of deterministic models as a central part of the engineering toolkit for such systems. He is the director of iCyPhy, the Berkeley Industrial Cyber-Physical Systems Research Center. From 2005-2008, he served as Chair of the EE Division and then Chair of the EECS Department at UC Berkeley. He has led the development of several influential open-source software packages, notably Ptolemy and Lingua Franca. Lee received his BS degree in 1979 from Yale University, with a double major in Computer Science and Engineering and Applied Science, an SM degree in EECS from MIT in 1981, and a Ph.D. in EECS from UC Berkeley in 1986. From 1979 to 1982 he was a member of technical staff at Bell Labs in Holmdel, New Jersey, in the Advanced Data Communications Laboratory. Lee is a Fellow of the IEEE, was an NSF Presidential Young Investigator, and won the 1997 Frederick Emmons Terman Award for Engineering Education. He received the 2016 Outstanding Technical Achievement and Leadership Award from the IEEE Technical Committee on Real-Time Systems (TCRTS), the 2018 Berkeley Citation, the 2019 IEEE Technical Committee on Cyber-Physical Systems (TCCPS) Technical Achievement Award, the 2022 European Design and Automation Association (EDAA) Achievement Award, the 2022 ACM SIGBED Technical Achievement Award, an honorary doctorate from the Technical University of Vienna in 2022, the 2023 CASES Test of Time Award for a paper published in 2008 on PRET machines, and the 2024 HiPEAC Technology Transfer Award.

More about Edward A. Lee: eecs.berkeley.edu/~eal