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.
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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 it comes to what’s possible. Costumes, props, movies, power-point presentations or other experimental setups – it is all allowed. Only time sets the limits –
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 most of the tasks we want to solve with Deep Learning, we need large, if not huge, amounts of data and computing power. This is
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 in store. Which intelligent materials will pave our tomorrows? How can substances and materials change our world in an intelligent way? What will the world
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 will be introduced. The research on semantics for the benefit of UAVs, specifically quadcopters, will be highlighted. The second part will contain the personal experiences
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 this talk, we introduce the extended functional definition of learning that can be used across scientific disciplines. We provide examples of how the definition can
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 our research showing the sophisticated anticipation abilities of live fish, as well as how we integrated prediction and anticipation into Robofish’s social interaction behaviors. We
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 which are often acompanied by oscillations in different frequency bands or by specific functional connectivity patterns between populations of neuron. A common hypothesis states, that
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 will give a brief overview of recent models we developed for weakly- and semi supervised as well as for active learning. In addition, we will
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 such collective concept, we have been using analytical and synthetic approaches to get more insights using mainly one particular biological system of Sulphur mollies as
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 assess the relative strengths of human versus machine cognition. This talk will take place in person at SCIoI.
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 former approach is attractive thanks to its elegance and potentially wide applicability, however the basic facts of human pattern vision do not support it. Instead,
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