Conferences  >  Mathematics  >  Neural Networks and Artificial Intelligence, Machine Learning  >  Germany

Max Planck Institute for the Physics of Complex Systems (MPI-PKS)

Complex Systems, Chaos and Self-Organisation,    Quantum materials, Low Temperature Physics

Entwickler.de Akademie

Das MLcon GenAI Training bietet eine einzigartige Kombination aus Theorie und Praxis. An Tag 1 starten wir mit den Grundlagen von Python für Machine Learning und den wichtigsten Frameworks. Tag 2 führt Sie in die Welt der Generative AI ein: Sie lernen, wie Modelle integriert, Prompts optimiert und Use Cases erfolgreich umgesetzt werden. Am dritten Tag wenden Sie dieses Wissen praktisch an, indem Sie RAG-Systeme implementieren, Vektordatenbanken nutzen und MLOps für den produktiven Betrieb einsetzen. Dieses Intensivtraining ist ideal für alle, die GenAI von Grund auf verstehen und direkt umsetzen möchten.

AI, Machine Learning, Künstliche Intelligenz, KI

Implementation and Applications of Artificial Intelligence,    Training in Computer Science, Courses

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Seminar will focus on bridging the gap between deep learning and knowledge graphs, and will discuss their integration: neurosymbolic AI. The aim is to advance the understanding of how symbolic knowledge - in the form of KGs - can be used to improve the capabilities of DL systems, and how DL can advance KG construction and applications.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

In a little over a year since the release of ChatGPT, language models (LMs) have stirred concerns in government, over the possibility that citizens will come to believe the textual and spoken output of such models. Similarly, they have caused panic in education, forcing a rethink of what students are learning and how to assess it. Of concern to us here, is whether LMs mean the end of computational and/or cognitive models of human language learning and language use. Does the practical success of LMs mean that computational linguistics (and perhaps even linguistics itself) is no longer relevant? Or are we missing problems with LMs that computational linguistics (and linguistics more generally) could help us both recognize and surmount?

Implementation and Applications of Artificial Intelligence,    Natural Language Processing, Computational Linguistics

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Seminar aims to bring together experts and stakeholders in Generative AI and computing education to foster collaboration and to chart a way forward as Generative AI continues to improve and proliferate. It is the goal of this seminar to leverage the experience and knowledge of dozens of programming education experts from around the world to form an enduring community of practice. During the Dagstuhl Seminar, we intend to develop strategies for incorporating LLMs into programming education and to rigorously evaluate their use and impact. This seminar will explore the following topics in the context of Generative AI in programming education: accessibility; diversity, equality, and inclusion; resources; introductory programming for computer science majors and non-majors; advanced courses (that use programming); curriculum changes; novel pedagogies, approaches and tools; and industry use and changes that may lead to new learning outcomes.

e-Learning, Computers in Education,    Didactics of Scientific Disciplines

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Geometry and Topology,    Optimization Theory, Operational Research