Work

Innovations and emerging trends in applied machine intelligence

Year: 2026

Type: article

Abstract: The article presents selected insights from the tenth Dagstuhl Workshop on Applied Machine Intelligence, highlighting recent advances in generative, knowledge‑based, and hybrid AI. It discusses how generative AI is reshaping creative and editorial workflows. The workshop also examined the limitations of LLMs in explanation tasks and quality assurance, emphasising the need for trustworthy, domain‑sensitive and hybrid approaches that combine neural and symbolic methods. Further contributions explore agentic AI as an emerging paradigm for business information systems and revisit abductive reasoning to better integrate formal inference with human‑centred modelling. Together, these perspectives illustrate how hybrid AI can address current shortcomings and support reliable, transparent and domain‑aligned applications across sectors.

Source: Informatik-Spektrum

DOI: 10.1007/s00287-026-01618-5

Authors: Bernhard G. Humm, Johannes Busse, Steffen Castle, Rolf Fricke, Markus von der Heyde, Thomas Hoppe, Dave Raggett, Anatol Reibold, Rigo Wenning, Fiona Zender

Institutions: Darmstadt University of Applied Sciences, University of Applied Sciences Landshut, German Research Centre for Artificial Intelligence, Fraunhofer Institute for Open Communication Systems, European Research Consortium for Informatics and Mathematics, Leipzig University

Language: English

Topic: Artificial Intelligence Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,390

OpenAlex ID: W7225609468

FWCI:

Cites: 28

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