Lorenzo Baraldi (University of Modena and Reggio Emilia) explores how internal representation spaces in multimodal foundation models can enhance control, safety, and grounding.
Every measurement, whether in physics, statistics, or machine learning, comes with a cost. From Heisenberg’s uncertainty principle to the limits of data prediction, Professor Xiao-Li Meng reminds us that knowledge itself is bounded by trade-offs. Precision and uncertainty are not opposites, they are partners in the same dance. In science, as in life, there is no free lunch.