As a 2024-5 Open Future Fellow, I explored AI across the research and publishing lifecycle. The output of this research is available as a report here: https://openfuture.eu/publication/governing-the-scholarly-ai-commons Summary: In recent years, commercial publishers and information analytics companies have increased their reliance on AI-based technologies to conduct a range of tasks across the research lifecycle.

Im Jahr 2024 unterstützte der Publikationsfonds des Landes Brandenburg Open-Access-Publikationen von Wissenschaftler*innen aus verschiedenen Fachbereichen. Diese Titel repräsentieren eine breite Palette von Disziplinen und sind Zeugnis der vielfältigen Forschungslandschaft des Landes. Zurzeit bringen wir Ihnen einige dieser Veröffentlichungen in unserem Blog näher.

Introduction The rise of artificial intelligence in code generation and problem-solving has transformed the way we approach both technical and creative tasks. From automating repetitive coding chores to providing insights into complex problem domains, AI tools have become essential companions for developers, researchers, and learners alike.

Introduction In today’s rapidly evolving AI landscape, conversational agents have become increasingly sophisticated, transitioning from simple text-based interactions to more natural, voice-enabled experiences. This blog post explores how to create an intelligent chatbot that not only understands and responds to text input but also speaks its responses aloud – all without writing a single line of code.

Understanding its Capabilities and Design

Welcome back, readers! In my previous post, I guided you through setting up an LLM pipeline using n8n and Ollama, all hosted locally (catch up here: How to install n8n and create an LLM pipeline using Ollama & Docker! (For Windows)). Today, we’re elevating that foundation by creating an automated email system that integrates n8n’s AI Agent with Outlook.

Introduction What Is Chain-of-Thought Prompting? Imagine solving a math problem or logic puzzle by writing out each step of your thinking process.

Reasoning, Coding, and Conversation: Evaluating Claude’s Evolution as a Thinking Partner

This is the second part of a blog post series on spatial machine learning with R. You can find the list of other blog posts in this series in part one. Introduction This document shows the application of caret for spatial modelling at the example of predicting air temperature in Spain.

The Crossref Nominating Committee invites expressions of interest to join the Board of Directors of Crossref for the term starting in January 2026. The committee will gather responses from those interested and create the slate of candidates that our membership will vote on in an election in September.

I chart the rise and fall of the Soviet Union, as measured by its share of world energy consumption.

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