Conferences  >  Informatics  >  Implementation and Applications of Artificial Intelligence  >  Germany

Software & Support Media GmbH

Join us for MLCon Berlin, happening from November 25–29, 2024, in the innovative city of Berlin. This conference is the go-to event for data scientists, machine learning engineers, and AI enthusiasts eager to explore the latest advancements in machine learning and artificial intelligence. Whether you're an experienced professional or just starting in the field, MLCon Berlin offers a unique opportunity to gain cutting-edge knowledge and practical skills to excel in your career.

Phone: [017693102012];     Email: marketing@sandsmedia.com

Generative AI and LLMs, MLOps, Advanced ML Development, ML Tools, APIs & Frameworks, ML Business & Strategy, ML Basics & Principles, ML Fundamentals Bootcamp

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

At the Dagstuhl Seminar on RNA Regulation and Multidimensional Transcriptomics, we will delve into the intersection of computational biology, deep learning, and RNA research. The event will explore how cutting-edge AI technologies are reshaping our understanding of RNA-based gene regulation and its role in health and disease.

Genomics and Bioinformatics,    Neural Networks and Artificial Intelligence, Machine Learning

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Perspectives Workshop aims, first of all, to bring together the communities working on the related areas of learning through interaction, (conversational) agents in games, dialogue and interaction, and collecting judgments from crowds through games, to make each community aware of the most recent developments in the other areas. We also intend to discuss current challenges, and whether advances in one area (e.g., grounded interaction) can benefit other areas (e.g., interactive learning).

WEKA FACHMEDIEN GMBH

Der zweite »Medical Solution Day« widmet sich 2024 der »KI für die Medizingeräte-Entwicklung« und den drängendsten Entwickler-Fragen zur KI-Integration: Was können KI-Algorithmen in medizinischen Anwendungen leisten, und wie lassen sie sich dort implementieren, aktualisieren und skalieren? Wie sollten MedTech-Entwickler – auch unter regulatorischen Aspekten – dabei vorgehen? Führende Technologie- und Medizin-Experten teilen Ihre KI-Expertise, um komplexe Medizin-KI-Anwendungen zu verstehen und zu entwickeln. Sie geben Hilfestellungen an die Hand und berichten über praktische und klinische Anwendungen in der Medizintechnik.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Generative AI systems are rapidly being integrated into global systems of cultural communication, consumption, and production. As these technologies shape our cultures, we urgently need conceptual foundations for investigating the cultural inclusivity of generative AI pipelines (from data collection, to model development and deployment, to evaluation), as well as methods to study the varying societal and cultural impacts of generative AI. This Dagstuhl Seminar wants to bring together scholars and practitioners from computer science, social sciences, the tech industry, and creative industries to discuss the cultural implications of generative AI and find paths toward building generative AI that can be responsive to the diverse needs of individuals, groups, and societies around the world. Together, seminar participants will build shared language and frameworks for reshaping the technical and social architectures of generative AI.

Natural Language Processing, Computational Linguistics,    Social Networks and Social Aspects of Information Technology

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Seminar Task and Situation-Aware Evaluation of Speech and Speech Synthesis is an opportunity to help redefine the metrics and methods traditionally used to evaluate speech synthesis and human speech as they are used across disciplines, tasks, and applications. The seminar is designed as a collaborative platform where experts from engineering, the humanities, social sciences, and more come together to challenge the status quo and drive innovation. Through the combination of perspectives and the bridging of gaps between scientific disciplines we hope to uncover and develop evaluation techniques that are not only scientifically rigorous but also contextually relevant to the diverse uses of speech technology today. We seek the collective expertise of participants from diverse areas of science and technology – ranging from phonetics to machine learning, from rhetorical analysis to practical applications in assistive technologies. This interdisciplinary approach is essential for crafting evaluation standards that are as dynamic and nuanced as the technologies and applications they aim to assess. To this end, we encourage you to share, debate, and refine ideas, methods, and tools that can contribute to a transformative discussion on the evaluation of speech synthesis.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Artificial Intelligence, Computers and Society, Databases, Trust, Transparency, Accountability, Knowledge Graphs, Web Data

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Artificial intelligence has made tremendous strides across many spheres of life, however deploying this technology in safety critical domains remains challenging. This seminar focuses on clinical practice where data-driven models can streamline the work of healthcare professionals and democratise access to personalised medicine, thus have lasting positive impact on society, but also where deploying such tools without adequate foresight and safeguards can be perilous. This duality – anticipated benefits that may come along with unintended consequences – requires new technologies to be thoroughly vetted, e.g., with clinical trials and medical certification processes, before they can be deployed to avoid any harmful fallout. However, fulfilling such regulatory requirements is a lengthy and complex process plagued with many challenges, hence while prototype systems are becoming increasingly ubiquitous, they often remain indefinitely designated as research tools that can be used exclusively for research purposes. Their lacklustre adoption is compounded by pervasive reproducibility issues; history of unsafe systems being deployed prematurely; scarce data that are inherently private, difficult to collect or share, and often riddled with numerous biases; and prevalence of automation promises that never come to fruition. Such hurdles result in healthcare remaining one of the least digitised spheres of life.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Logic and learning are central to Computer Science, and in particular to AI-related research. Already Alan Turing envisioned in his 1950 “Computing Machinery and Intelligence” paper a combination of statistical (ab initio) machine learning and an “unemotional” symbolic language such as logic. The combination of logic and learning has received new impetus from the spectacular success of deep learning systems. The goal of this Dagstuhl Seminar is to bring together researchers from various communities related to utilizing logical constraints in deep learning and to create bridges between them via the exchange of ideas.

Neural Networks and Artificial Intelligence, Machine Learning,    Information Theory, Foundations of Computer Science

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

The first goal of this Dagstuhl Seminar is to survey existing uses of any kind of XR technologies in the OR. More importantly, we will seek to foster and create ideas for novel research on using XR in the OR. This should lead to novel use cases of the technology, novel research questions, and an agenda for research on XR in the OR for the next 5 years. As one of the tangible outcomes, we plan to develop a position paper outlining this agenda during the seminar, and submit it to a major journal. These goals will be achieved by bringing together researchers from all sub-fields of XR (VR, AR, sound and haptic rendering, new materials, and other kinds of mixed reality), along with practitioners (surgeons) from different medical areas, in order to bring the practical perspective of surgery to the seminar.

Healthcare Technologies,    Human-Computer Interaction, User Experience, Virtual Reality

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

There are many connections between market design with and without money, and this Dagstuhl Seminar aims to provide a platform for scholars in auctions, matching, and learning in games to work together and develop new ideas on how to deal with the complexities in designing and analyzing real-world markets.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

In our daily lives, we as humans perceive our surroundings in an inherently multimodal way. Nevertheless, the vast majority of data analysis idioms are exclusively visual, not using the apparent potential of combined designs. While the visualization field studies visual data analysis solutions, the sonification field investigates comparable solutions that convey data over non-speech audio. There are several similarities between the methods and design theories of both approaches, such as the use of perceptual variables to encode data attributes, the use of marks and substrates for conveying items, and the role of interaction in manipulating the data representations. Over the recent decades, both fields have established research communities, theoretical frameworks, and toolkit support.

Neural Networks and Artificial Intelligence, Machine Learning,    Multimedia, Computer Graphics and Visualization, Games

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Reactive systems are software systems that engage in a continual dialogue with their environment. They constitute the software parts of cyber-physical systems where timely reactions are often critical to safety. Applications include autonomous vehicles, electric power systems, industrial automation, healthcare electronics, and robotics. Because the software engages in a continual dialog with its environment, it often has conflicting requirements. It needs to be predictable, but robust to unpredictable events; it needs to react in a timely manner, but this often requires reacting with inconsistent information; it needs to be adaptable, but demonstrably safe; and it needs to be secure, but accessible and available. Many conferences and workshops focus on one of the goals, such as achieving real-time behavior, without explicitly acknowledging the costs and without providing sound strategies for dealing with failures that prevent reaching the goals. The focus of this seminar will be on the tradeoffs that are intrinsic in the design of such systems. When you make a system predictable, available, secure, or even demonstrably safe, what have you lost? This Dagstuhl Seminar will pull in experts from manifold disciplines to identify and discuss the fundamental limits in reactive systems design that make tradeoffs inevitable.

Soft Computing, Evolutionary Computation, Metaheuristic Optimization, Fuzzy Logic,    Internet of Things (IoT) and Sensor Networks

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

The objective of this workshop is to bring together researchers, practitioners, and experts in the field of explainable AI to collaboratively develop reusable experiment designs. Evaluating explainability methods is something that has not been standardized by the community, meaning each author must develop and justify their own approaches. This reduces the abilities of researchers to publish their findings, which can also hinder progress in this space.

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?

Neural Networks and Artificial Intelligence, Machine Learning,    Natural Language Processing, Computational Linguistics

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH