Jan De Bruyne (Leiden University), “Liability for Damage Involving AI – Some Regulatory Challenges and Priorities”
More details to follow. Photo by DeepMind on Unsplash This talk will take place in person at SCIoI.
12 events found.
Berlin Science Week 2022 – The Science Slam of the Berlin Clusters of Excellence, “Clear the stage for science”
At our cluster science slam, scientists try everything to entertain their audience, regardless of whether the subject is e.g. mathematics, neuroscience or active material. The sky is the limit when
Heiner Spiess (Science of Intelligence), “Tools to study the generality of Deep Neural Network Representations”
Abstract: As many of us know by now, Deep Learning has enabled tackling very challenging problems and applications that were previously almost impossible to solve with machine learning. However, for
What are futures made of? Collactive Materials, a joint SCIoI/MoA project
Abstract: The BUA-funded experimental knowledge transfer project CollActive Materials, a collaboration between the Clusters of Excellence Science of Intelligence and Matters of Activity, encourages speculation on what the future has
Thursday morning talk: Nicolas Mandel, “Kangaroos & Quadcopters”
Abstract: The contents of this presentation will be twofold. In the first part the Centre for Robotics of the Queensland University of Technology (QUT) and its research directions and facilities
Jan De Houwer (Ghent University), “Learning in Individual Organisms, Genes, Machines, and Groups: A New Way of Defining and Relating Learning in Different Systems”
MAR 2.057Abstract: Learning is a central concept in many scientific disciplines. Communication about research on learning is, however, hampered by the fact that different researchers define learning in different ways. In
David Bierbach (Science of Intelligence), “Anticipation in social interactions among live and artificial agents”
Abstract: The aim of SCIoI’s P10 is to investigate how anticipation and prediction shapes social interactions among live and artificial agents using for example the Robofish system. We will outline
Klaus Obermayer (Science of Intelligence), “Computational Models of Electric Field Effects and Optimal Control of Neurons and Neural Populations”
Abstract: The brain is a complex dynamical system with processes operating on different spatial scales. At the macroscopic end one observes global dynamical phenomena, which are called „brain states“ and
Erik Rodner “Please label me: challenges and efficient strategies for data annotation and selection”
Abstract: Lack of data and annotations has been the showstopper for machine learning projects when I started my PhD and 15 years later it still is. In my talk, I
Robert Lange and Luis Gomez (Science of Intelligence), “Quantifying and modelling collective behavior across ecological contexts”
Abstract: A central challenge in understanding the concept of swarm intelligence is the relation between the behavior of a swarm of agents and its ecological niche. In order to interpret
John Dylan Haynes (Science of Intelligence), “Intelligence in humans versus machines”
Many claims have been made that machine intelligence could make humans superfluous in the near future. Today this claim is largely seen as overstated, but it is still important to
Peter Neri (Laboratoire des Systèmes Perceptifs, CNRS, Paris), “The unreasonable recalcitrance of human vision to theoretical domestication”
Abstract: We can view cortex from two fundamentally different perspectives: a powerful device for performing optimal inference, or an assembly of biological components not built for achieving statistical optimality. The
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