Non-Generative AI Agents: When Classical AI Is Superior to Generative Models
The article explains when non-generative AI agents should be used and why traditional models remain superior to LLMs in many business-critical applications.
How can critical changes in the condition of intensive care patients be detected early and, at the same time, evaluated in a medically sound manner? A recent scientific paper published in *Communications Medicine*, a peer-reviewed journal in the Nature portfolio, addresses this question. Markward Britsch, a data scientist at HMS, was also involved in the work as part of an interdisciplinary research team.
Erfahre, wie Atomic Delivery Teams Unternehmen helfen, Generative AI Projekte erfolgreich von der Idee in die skalierbare Produktion zu bringen. Der Artikel zeigt die wichtigsten Rollen, Fähigkeiten und Prinzipien für nachhaltige AI Wertschöpfung.
Digital Sovereignty for AI and Analytics Platforms
Robust IT architectures ensure control over data and systems without limiting flexibility. Using real-world examples, we demonstrate how organizations can reduce dependencies and achieve long-term resilience through thoughtful technology decisions.
Vector stores are at the heart of modern GenAI applications. However, scaling them efficiently is more complex than it seems. From metadata management to hybrid search to ingestion pipelines: Here, you’ll learn about common pitfalls and how to avoid them based on real-world project experience.
Early tracing and testing of LLM calls identify issues before they become costly, thereby accelerating the development, quality, and time-to-market of GenAI solutions.
In this article, you’ll learn how the Model Context Protocol (MCP) structures the interaction between the host, client, and server, what security considerations are relevant, and what typical application workflows look like. This article is intended for architects, developers, and IT decision-makers who want to integrate LLMs securely and scalably into business processes.
