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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 #256 · 03/07/2024, 08:04 AM

Mozilla Foundation Study Raises Concerns on Watermarking AI Content Hello everyone! In a study released by the Mozilla Foundation, the challenges of identifying synthetic content online have been brought to light. Titled "In Transparency We Trust? Evaluating Watermarking and Labeling AI-Generated Content," the study delves into the effectiveness of various methods, including watermarking and labeling, in differentiating between synthetic and authentic content. The study, which conducted a comprehensive assessment of seven methods, both machine-readable and human-facing, revealed alarming findings: none of the methods were rated as "good," indicating significant hurdles in accurately identifying synthetic content. Despite efforts to implement watermarking and labeling, the study underscores the persistent difficulties faced in combatting the proliferation of AI-generated content. #MozillaFoundation#AIContent#Watermarking