The billion-dollar business with user data | c't uplinkTrump administration might not fight state AI regulations after allGoogle's new learning model aims to stop catastrophic forgetting in AI systems.Researchers are tinkering with websites for AI agents.

The AI news for November 23rd, 2025

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Here are the details of the day's selected top stories:

The billion-dollar business with user data | c't uplink
Source: https://www.heise.de/news/Das-Milliardengeschaeft-mit-den-Nutzerdaten-c-t-uplink-11087698.html?wt_mc=rss.red.ho.themen.k%C3%BCnstliche+intelligenz.beitrag.beitrag
Why did we choose this article?
Clear, practical look at the economics and mechanics of the data-collection business that powers many AI products. Useful for listeners who need to understand privacy risks, data provenance, and why data labeling/behavioral profiles matter for model performance and regulation.

Trump administration might not fight state AI regulations after all
Source: https://techcrunch.com/2025/11/22/trump-administration-might-not-fight-state-ai-regulations-after-all/
Why did we choose this article?
Timely policy signal: federal-state dynamics will shape how AI is governed in practice. Important for product teams, compliance officers, and policy-minded listeners to track whether states will be free to experiment with regulation and how that affects deployment strategies.

Google's new learning model aims to stop catastrophic forgetting in AI systems.
Source: https://the-decoder.de/neues-lernmodell-von-google-soll-katastrophales-vergessen-in-ki-systemen-stoppen/
Why did we choose this article?
Technical but high-impact research: addresses continual learning and catastrophic forgetting — a key limitation for systems that must adapt over time. Good for engineering leads and researchers who plan for long-lived models or on-device personalization.

Researchers are tinkering with websites for AI agents.
Source: https://the-decoder.de/forscher-basteln-an-webseiten-fuer-ki-agenten/
Why did we choose this article?
Practical engineering advance that could make web-enabled agents more reliable and safe by adding explicit semantics for agent actions. Direct implications for product teams building agent integrations and for web developers who may need to adopt new standards.

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