Conférences  >  Informatique  >  Mise en œuvre et applications de l'intelligence artificielle  >  Allemagne

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Code search describes the process of retrieving source code from a repository, where that source code matches a query. Whether a developer is looking for where an error was thrown, learning how to use a new-to-them API, learning a new programming language, or browsing their team’s directory to familiarize themselves with the codebase, search underpins all these activities. Beyond those human-driven software engineering processes, search is also a component in automated software engineering, such as automated program repair, code example recommendation, and clone detection. Furthermore, new generative AI tools have challenged traditional code search by presenting alternative approaches to finding and reusing code.

This Dagstuhl Seminar brings together experts in mining software repositories, human factors in software engineering, software documentation, code examples, program analysis, and industrial code search systems to bridge the gap between industry and academia and set the roadmap for the next decade of code search research.

Génie logiciel,    Conception et gestion des bases de données, Moteurs de recherche et extraction de connaissances à pa

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

This Dagstuhl Seminar aims to unify the international research on resilient and antifragile autonomous systems (RAAS), leading to faster scientific advancements and industrial adoption. To that end, the seminar wants to bring together leading researchers and practitioners with expertise in autonomous system resilience, antifragility, safety, and ethics from disciplines including Computer Science, Computational Biology, and Ethics, to share and discuss each other’s understanding of, methods for, and open challenges related to RAAS.

resilience, antifragility, autonomous systems, AI, safety, ethics and assurance of autonomous systems

Robotique, automation & mécatronique,    Soft computing, algorithmes évolutionnaires, domaine des métaheuristiques, logique floue

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

This Dagstuhl Seminar provides a unique opportunity for discussing the discrepancy between human and AI generalization mechanisms and crafting a vision on how to align the two streams in a compelling and promising way that combines the strengths of both. To ensure an effective seminar, we aim to bring together cross-disciplinary perspectives across computer and cognitive science fields. Our participants will include experts in Interpretable Machine Learning, Neuro-Symbolic Reasoning, Explainable AI, Commonsense Reasoning, Case-based Reasoning, Analogy, Cognitive Science, and Human-Computer Interaction. Specifically, the seminar will focus on the following questions: How can cognitive mechanisms in people be used to inspire generalization in AI? What Machine Learning methods hold the promise to enable such reasoning mechanisms? What is the role of data and knowledge engineering for AI and human generalization? How can we design and model human-AI teams that can benefit from their complementary generalization capabilities? How can we evaluate generalization in humans and AI in a satisfactory manner?

Interpretable Machine Learning, Human-AI Collaboration, Cognitive Science, Neuro-Symbolic Reasoning, Explainability

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Philosophie universitaire

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

While recommender systems is largely an applied field, their evaluation builds on and intersects theories from information retrieval, machine learning, and human-computer interaction. Historically, the theories and evaluation approaches in these fields are very different. Thoroughly evaluating recommender systems requires integrating all perspectives. Hence, this seminar will bring together experts from these fields and serve as a vehicle for discussing and developing the state-of-the-art and practice of evaluating recommender systems. The seminar will set the ground for developing recommender systems evaluation metrics, methods, and practices through collaborations and discussions between participants from diverse backgrounds, e.g., academic and industry researchers, industry practitioners, senior and junior. We emphasize the importance of getting and keeping the big picture of a recommender system’s performance in its context of use, for which it is ultimate to incorporate the technical and the human element. We will set the basis for the next generation of researchers, apt to evaluate and advance recommender systems thoroughly.

Logiciels,    Interface homme-machine, expérience utilisateur, la réalité virtuelle

This symposium will treat the impact of Artificial intelligence (AI) and Machine Learning (ML) on chemistry and biology, including drug design. The underlying theme of the discussions will be what we can now do with AI and ML that we couldn’t do before. For instance, is AI simply a new interpolation method in the old traditional computer-aided drug design (CADD)? Are the methods applied nowadays intransparent in contrast to the those applied in the early days? How can we combine the development and application of new materials with AI-generated knowledebases? How much can AI help in the prediction and retro-synthesis of new chemical compounds, and how useful are these compounds? Still, the quality of published data matters as meaningful AI applications depend on the availability of high-quality test datasets.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

The timeliness of this seminar is critical: in the last twelve months, LLMs have revolutionized many commercial fields and their use in education continues to grow. This use is mostly by students who use LLMs to generate answers to school work, while universities are grappling with the impact of LLMs on assessment policies and pedagogy.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Automated machine learning (AutoML) aims to reduce the need for experts to obtain effective ML pipelines. It offers off-the-shelf solutions that can be applied without prior knowledge in ML, allowing engineers to dedicate more time to domain-specific tasks. Regrettably, AutoML is underutilized in computational mechanics. There is almost no communication between the two communities, and engineers spend unnecessary effort selecting and configuring ML algorithms. In light of this, the current Dagstuhl Seminar is dedicated to fostering cross-pollination between the fields of AutoML and Computational Mechanics. It aims to convene a curated selection of international experts, each hailing from diverse backgrounds and various application domains, encompassing computer science, machine learning, engineering, mathematics, operations research, and industrial applications.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Robotic Process Automation (RPA) is an emerging technology that sits between the fields of Business Process Management (BPM) and Artificial Intelligence (AI). RPA allows organizations to automate high-volume and repetitive tasks – also referred to as routines – performed by human users. The enactment of these routines is emulated by means of a software (SW) robot that works on the applications' user interfaces (UIs) in the same way as the original human operators did. The overall goal is to explore the scientific and technological foundations to pioneer new trust-aware RPA solutions that work in partnership with the human workforce, to enhance human capabilities rather than replace human intelligence and break through the barriers to human trust using RPA.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

The central topic of our Dagstuhl Seminar is the development, implementation, and evaluation of new AI technologies to support decision-making in management. A distinguishing feature is therefore innovative algorithms from the field of AI (e.g. explainable AI, generative AI, large language models, probabilistic ML, causal ML, etc.) that enable new insights in practice and beyond. This holds great potential for informing and improving decision-making.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Conversational Agents (CA) as frontends to Information Retrieval (IR) and Recommender Systems (RS) become more popular in everyday life, with a wider range of users and usages. The latest developments in Large Language Models (LLMs) will have tremendous consequences, especially for the workplace and education. In this Dagstuhl Perspectives Workshop, we want to focus on the evaluation of these conversational systems, as appropriate methods are still missing. The quality of these systems is limited in terms of personalization, veracity and correctness, bias, transparency, trustworthiness, and understandability. Thus, evaluation methods must address these shortcomings. Furthermore, user- and usage-oriented aspects should become a more prominent and integral component in evaluations, as the user population as well as the tasks these systems are used for become more heterogeneous. For this reason, the topic-centric view of relevance has to be extended to a broad range of facets which are important for the different usage scenarios. Therefore, suitable evaluation criteria have to be specified, which form the basis for defining appropriate measures. Most importantly, the range of evaluation methods must be revisited and extended, as popular methods like the Cranfield approach or crowdsourcing must be complemented by new evaluation methods and strategies specifically tailored to this new type of system.

Traitement automatique des langues, Linguistique informatique,    Gestion des connaissances, Big Data Computing

Software & Support Media GmbH

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ML Business & Strategy, Advanced ML Development, ML Tools, APIs & Frameworks, ML Basics & Principles

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Automated programming refers to techniques that suggest newly written code, e.g., in the form of code completion tools. Techniques for automated programming include large language models that predict code based on natural language specifications of the intended behavior. The recent development of technologies like Codex and ChatGPT have made us examine the possibility of automated programming in the future. Automated program repair refers to a suite of techniques for automated rectification of errors or vulnerabilities in programs. Automated program repair technologies were originally developed for reducing the debugging effort for manually written code. However, interestingly these techniques can be adapted to improve automatically generated code. This Dagstuhl Seminar will explore the intersection of these two fields.

Génie logiciel,    Traitement automatique des langues, Linguistique informatique

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.

Génomique et bio-informatique,    Réseaux de neurones et intelligence artificielle, apprentissage automatique

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

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