Vor ca. einem Jahr hatte ich die Idee zu #Aufwärts: #Netwalking statt #Networking. Mir war aufgefallen, dass ich über die Jahre den Kontakt zu vielen Kontakten verloren hatte.
Bei meiner ersten Unternehmung, SnipClip, war ich 4 Tage die Woche unterwegs: für Kunden und Konferenzen. Bei meiner zweiten Unternehmung, Datentreiber, ging das nicht mehr und ich wollte es nicht mehr: für Kind 12J und Kind 6J.
Meine Frau arbe...
https://www.datentreiber.com/blog/nachste-woche-gehts-zum-7-mal-aufwarts/
Let me tell you another story from the Machine Learning Week Europe (MLW). Two years ago, a speaker at MLW presented an LLM solution for extracting information from emails. Their biggest challenge: avoiding prompt injections. 80% of the effort went into LLMOps: securing the operations of the LLM.
During the Q&A participants asked just a few simple questions (I'll simplify things a bit here):
Q: Why didn't you just use entity recognition...
https://www.datentreiber.com/blog/ml-is-more-than-llm/
Leading LLMs often return “trendslop”: buzzy strategy advice that ignores your context and the hard trade-offs real strategy demands. So don’t let AI *choose*—use it to expand options, challenge assumptions, and stress-test decisions with your team. #AI #LLM #Strategy #Data #Leadership
https://hbr.org/2026/03/researchers-asked-llms-for-strategic-advice-they-got-trendslop-in-return
https://www.datentreiber.com/blog/researchers-asked-llms-for-strategic-advice-they-gottrendslop-in-return/
Leaders might assume that LLMs are able to offer a kind of unbiased, outside perspective. But new research found that leading LLMs have clear biases when it comes to strategy and consistently recommend strategies that align with modern managerial buzzwords and trends rather than context-specific strategic logic. This propensity for AI to opt for buzzy ideas over reasoned solutions is called “trendslop,” and leaders should beware of it warping their strategic planning. When using AI in strategic planning, leaders should: use it to expand options, not make choices; counteract known and potential biases; remain alert to changing biases; watch out for the hybrid trap; and not rely on context alone.
