algorithmic methods

Professor Christoph Kumpan and Professor Georg Ringe would like to invite you to the NAIL Research Seminar #17 with Ass. Prof. David Restrepo Amariles (HEC Paris). The event will be held in English and will take place in person. You can also participate online by registering your participation via mail.

The Digital Services Act (DSA) of the European Union targets content moderation challenges, such as the dissemination of illegal content and disinformation, which are recognized as systemic risks. This presentation delves into the effectiveness of algorithms and crowdsourced moderation in meeting the obligations of Very Large Online Platforms (VLOPs) under the DSA concerning content moderation. Specifically, it examines the propagation of disinformation via X and evaluates the effectiveness of both human and algorithmic aspects of its content moderation processes, particularly Community Notes, on the spread of such content. We have created a dataset of Community Notes and corresponding tweet data since September 2023 to analyze content moderation and tweet diffusion. Employing topic modeling and a difference-in-difference methodology, the research quantifies the impact of Community Notes on tweet diffusion, demonstrating a significant reduction. Despite the observed effectiveness, the study highlights the need for enhanced content moderation strategies to address the rapid spread of misinformation. The findings of this study are pertinent for understanding the collaboration required among legal, technological, and regulatory stakeholders to uphold the DSA.

Institutions

• Network for Artificial Intelligence and Law (NAIL)

Future robots need to be robust and adaptable, and new design approaches are needed for new production methods. I will talk about my research in using evolutionary algorithms and biologically inspired methods with the aim of having more intelligent, robust, and adaptive behavior in robots. I will give a short introduction to some of the algorithms and show how we, at the University of Oslo, apply them in our research platforms for exploring automatic robot design and adaptation. Here, we take an embodied AI approach and aim to co-design the body and the behavior of the robots, such that they are well fit for their intended environments and tasks. These approaches are still at a fundamental research stage, and I will discuss potential future application areas, as well as challenges and opportunities related to the sustainability of these AI systems.

Learning objectives:

By the end of the session, participants will be able to:

• List some bio-inspired AI approaches for robot design and adaptation.
• Discuss challenges and opportunities related to algorithmic robot design.

Recommended mastery level:

• Some undergraduate level engineering or computer science skills would be beneficial, although not absolutely necessary.

Artificial Intelligence is transforming how we approach chemical research and synthesis. By teaching language models to understand and generate the language of chemistry, we have developed complementary AI systems that bridge the gap between computational design and experimental reality.

Our large language model system, ChemCrow, represents one of the first demonstrations of an AI system directly controlling robotic synthesis platforms, successfully executing the synthesis of compounds including organocatalysts and chromophores.

Complementing this, our small language model system, Saturn, currently the most sample-efficient molecular design algorithm, enables precise molecular generation with built-in synthesizability constraints. Saturn’s innovations include direct optimization against retrosynthetic predictions and integration of building block availability, ensuring that generated molecules are practically accessible.

Our work demonstrates how different scales of language models can work together to transform chemical research, from initial molecular design through to physical synthesis, potentially revolutionizing drug discovery, catalysis, and materials development.