Thursday Morning Talk

Nina Poth (Science of Intelligence), “Exploring the prospects for a prediction-oriented view of intelligence”

Abstract: It has recently been proposed that a minimal condition of intelligence is the ability to form accurate predictions (Tjøstheim & Stephens 2021). In this talk, I evaluate the promise of this view for integrating intelligence research across subdisciplines within the cognitive and life sciences. I argue that this view combines two desirable features: (1)

Thursday Morning Talk

Friedhelm Hamann (Science of Intelligence), “Applications of event cameras: Animal Behavior Quantification in the Wild”

Abstract: Event cameras are novel bio-inspired sensors that naturally respond to motion in the scene. They have promising advantages, namely a high dynamic range, little motion blur and low latency. But how can we leverage these advantages for vision tasks such as animal behavior quantification? In this talk I will  present two applications developed at

PI Lecture

Marcel Brass (Science of Intelligence), “Social agency”

MAR 2.057

Abstract: Sense of agency (SOA) refers to the experience of controlling one’s own actions and corresponding effects. Social agency refers to SOA in situations where other social agents are involved. This can refer to situations in which we act together or in the presence of other agents or to situations where we control the behaviour

External Event

Girls’ Day 2023 at SCIoI 

MAR 2.057

It's that time of year again! Every April, school girls all over Germany visit scientific institutions to get inspiration for their future careers. SCIoI has participated in this event twice before, and we will be hosting another group of girls this coming 27 April. The event will start with some inspiring talks by our members

Thursday Morning Talk

Radoslaw Cichy, “Deep neural networks as scientific models of vision”

Abstract: Artificial deep neural networks (DNNs) are used in many different ways to address scientific questions about how biological vision works. In spite of the wide usage of DNNs in this context, their scientific value is periodically questioned. I will argue that DNNs are good in three ways for vision science: for prediction, for explanation,

External Event

“Future of Air – Speculative Workshop Series” – Es liegt was in der Luft (in German)

Workshop title: Es liegt was in der Luft Theme: Stage and the Environment Where: Hochschule für Schauspielkunst Ernst Busch Im Anthropozän, dem sogenannten ‘Zeitalter des Menschen’, ist die Umwelt zur Bühne geworden. Auf dieser Bühne zeigen sich ökologische Ausnahmezustände und drohende klimatische Kipppunkte. Unsere Rolle ist es, auszuhandeln, wie es weitergehen kann: Der Verlauf der

Thursday Morning Talk

Lauren Sumner-Rooney

More details to follow. This talk will take place in person at SCIoI.  

External Event

“Future of Air – Speculative Workshop Series” – Von Kontrolle zu Kooperation (in German)

Workshop title: Von Kontrolle zu Kooperation Theme: Air as Technology Where: silent green Kulturquartier   Betonindustrie, Verbrennungsmotor, Google-Suchanfrage – Technologie wird heute an ihrer CO₂-Emission gemessen. Unsere technische Kultur hat Karriere gemacht durch einen allzu sorglosen und zerstörerischen Umgang mit Ressourcen. Dabei wird vor allem der Versuch unternommen, Materialien und Umgebungen zu kontrollieren. Und das

Shintaro Shiba, “From Events to Motion to its Applications”

MAR 2.057

Abstract: Estimating motion from image sensors is a fundamental problem in computer vision and robotics. Event cameras are novel bio-inspired sensors that provide a signal suitable for estimating motion because their pixels naturally respond to intensity changes, which are tightly related to motions in the scene. However, event data is fundamentally different from conventional frame

Thursday Morning Talk

Milagros Miceli, “Transparency for whom? Designing data documentation with data workers”

MAR 2.057

Abstract: The opacity of datasets poses a significant challenge to creating inclusive and intelligible machine learning (ML) systems. Various AI ethics initiatives have addressed this issue by proposing standardized dataset documentation frameworks based on the value of transparency.  In this talk, I propose a shift of perspective: from documenting for transparency to documenting for reflexivity.