#aisummaries — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #aisummaries, aggregated by home.social.
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#Reddit shares fell 9% after the Wall Street Journal reported the company is considering ending its #contentdeal with #Google for #AItraining. The deal, worth $60 million annually, is expiring soon, and Reddit is reevaluating its benefits as Google’s #AIsummaries impact #searchtraffic. This comes amid a broader trend of media companies reassessing their relationships with AI giants. https://www.cnbc.com/2026/07/22/reddit-stock-google-ai-content-deal.html?eicker.news #tech #media #news
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Whoa! This could become a BIG deal .....
German court ruled Google Is liable for false statements generated by AI overviews presented in AI powered search results.
The ruling indicates that when an AI generates new statements that do not appear directly in its original sources, the company that designs, trains, operates, and manages the system must assume legal liability for any damages caused by those statements.
Further the Court held, correcting misinformation is not the responsibility of third parties. Google is the only entity with the ability to modify the technology underpinning its AI-generated summaries and, therefore, “must be held accountable.”
https://www.wired.com/story/a-court-has-ruled-that-google-is-liable-for-false-statements-generated-by-ai-overviews/ #AI #Google #AISearch #Internet #Liability #Falsehoods #FalseStatements #LLMs #AITraining #LegalPrecendent #ChatBots #Lawsuit #AISummaries #Law
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Sharing again. This is the most recent article on SEO Theory.
"AI Summaries Have Created 2 Unsolvable SEO Problems"
#ai #aisummaries #searchengineoptimization #seo #webmarketing #google #bing #aioverviews
https://www.seo-theory.com/ai-summaries-have-created-2-unsolvable-seo-problems/
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Attention LLM security enthusiasts! Google's Bug Hunters posted a detailed run through on protecting Large Language Models that goes beyond basic prompt injection:
It covers:
• Advanced prompt injection techniques
• Data poisoning strategies
• Model extraction methods
• Adversarial examples in the wildThis showcases how attackers are getting craftier, attempting to bypass ethical constraints while maintaining the illusion of authority.
But that's just the beginning. The post delves into the complexities of each attack vector and discusses potential mitigation strategies.
For those of us pushing the boundaries of AI security, this is a must-read. It might just change how you approach LLM vulnerabilities.
Check it out and let's discuss: What new insights did you gain from this analysis?"