Background

EN: Found on theregister.com The central bank for central banks is concerned about the eye-watering sums being invested into AI, and it's raising the specter of a global recession should the bubble burst. In its annual report for 2026, the Bank for International Settlements compared the current

Do you remember the Lippitt-Knoster model for managing complex change? This framework, which identifies critical elements needed for successful change, might help you in your AI transition and/or automation project! The framework identifies six critical elements required for successful change:

Found on Decoder podcast from The Verge Initially found on simonwillison.net Any business process that looks like code talking to a database in a repetitive way is up for grabs. It’s everywhere: the absolute cutting edge of advertising and marketing is automation with AI. It’s not being a creative.

Update on the 19th of April 2026 regarding DuckLake specification 1.0, found on thegerister.com Initially found on thegerister.com. DuckDB proposed DuckLake as a standard for metadata and catalogs, claims it simplifies lakehouses by using a standard SQL database for all metadata, instead of complex file-based systems, while still storing data in open formats like Parquet. It will be seen, if this makes them more reliable, faster, and easier to manage. The corresponding blog post is worth reading, because it gives a systematic view on the high level data architectures of DuckLake, Databricks, IceBerg, BigQuery and Snowflake.

Update in 26th of April 2026 found simonwillison.net Initially found on theregister.com Test driven development (TDD) produces much better results with AI coding assistants: TDD prevents a failure mode where agents write tests that verify broken behavior. When the tests exist before the code,

Found on theregister.com A feature regarding Geoff Huntley, his invention of the Ralph Wiggum Loop and the state of coding and agile: Developers, he argues, should now spend more time thinking about writing loops that drive coding assistants to produce better output, rather than persisting with code reviews.

Gefunden auf heise.de: Klassisches oder agiles Prjektmanagement: Welche Faktoren führen zu Problemen? Unklare Anforderungen Unrealistische Deadlines Unkontrolliert eskalierende technische Schulden Politik und Machtkämpfe Ich finde, man sollte noch den nachfolgenden Punkt mit hinzufügen, weil er ebenfalls eine häufige Ursache von Problemen ist:

Is the AI bubble soon ready to burst? EN: Found on theregister.com - "Big money is nervous about AI hype, but not ready to call it a bubble" AI hype train may jump the tracks over $2T infrastructure bill, warns Bain Ars Live: Is the AI bubble about to pop? A live chat with Ed Zitron Moody's raises

Gefunden auf heise.de. Irgendwie kann ich mich nicht dem Eindruck erwehren, dass Prof. Dr. Michael Stal diesen Sommer einiges zum Thema PyTorch gelesen hat... Zumindest hat er mit seiner Serie von Blog-Artikeln Künstliche neuronale Netze im Überblick eine lesenswerte Einführung in die Erstellung von künstliche neuronale Netze mit PyTorch gepostet:

Seit 2 August 2025 sind im Rahmen des EU AI Act die Transparenz- und Sorgfaltspflichten für generell einsetzbare KI in kraft getreten. Das ist ein guter Anlass mein englisches Blog-Posting Is it legal for AI to scrape licensed material and reproduce it in the generated output? ins deutsche zu Übersetzen und zu ergänzen. In Bezug auf KI gibt es einige wichtige rechtliche Fragestellungen, welche aktuell nahezu jeden Content-Ersteller und/oder Content-Provider betreffen: