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Source channel @githubtrending · Post #14737 · May 22

#other This book provides a systematic introduction to large language models (LLMs), covering topics like traditional language models, LLM architectures, prompt engineering, efficient parameter tuning, model editing, and retrieval-enhanced generation. It aims to be easy to read and rigorous, with monthly updates and a list of relevant papers. The book helps readers understand LLMs' principles and applications, making it beneficial for those interested in AI and NLP. It offers a structured learning path, which is useful for both beginners and advanced learners. https://github.com/ZJU-LLMs/Foundations-of-LLMs

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AI & Law

@ai_and_law · Post #746 · 01/20/2026, 08:04 AM

🇨🇦AI Defamation Risk: Canadian Artist Prepares Lawsuit After Google Error Canadian musician Ashley MacIsaac says a Google AI-generated summary falsely labeled him a convicted sex offender, leading a concert venue to cancel his show. MacIsaac told the Canadian Press he believes the system confused him with another individual in Canada who has similar charges, but the error directly cost him income and harmed his reputation. MacIsaac is now preparing to sue Google, arguing that the misinformation amounts to defamation and created real-world risks, including potential issues at border controls. He stated that AI companies must be held accountable for what their systems publish and what harms they can reasonably prevent, noting that he is unlikely to be the last person affected by such errors. The incident underscores how AI-generated summaries can produce high-impact false statements about individuals, with immediate legal, economic, and personal consequences, even when no human editorial judgment is involved. #AI#AIDefamation#Liability#GenerativeAI#ReputationRisk