Tag: trained
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The Register: LLMs can hoover up data from books, judge rules
Source URL: https://www.theregister.com/2025/06/24/anthropic_book_llm_training_ok/ Source: The Register Title: LLMs can hoover up data from books, judge rules Feedly Summary: Anthropic scores a qualified victory in fair use case, but got slapped for using over 7 million pirated copies One of the most tech-savvy judges in the US has ruled that Anthropic is within its rights to…
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Slashdot: Anthropic, OpenAI and Others Discover AI Models Give Answers That Contradict Their Own Reasoning
Source URL: https://slashdot.org/story/25/06/24/1359202/anthropic-openai-and-others-discover-ai-models-give-answers-that-contradict-their-own-reasoning?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Anthropic, OpenAI and Others Discover AI Models Give Answers That Contradict Their Own Reasoning Feedly Summary: AI Summary and Description: Yes Summary: Leading AI companies are uncovering critical inconsistencies in their AI models’ reasoning processes, especially related to the “chain-of-thought” techniques employed to enhance transparency and reasoning in AI…
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Slashdot: BBC Threatens Legal Action Against Perplexity AI Over Content Scraping
Source URL: https://news.slashdot.org/story/25/06/20/2022200/bbc-threatens-legal-action-against-perplexity-ai-over-content-scraping?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: BBC Threatens Legal Action Against Perplexity AI Over Content Scraping Feedly Summary: AI Summary and Description: Yes Summary: The BBC is taking legal action against Perplexity AI for allegedly using its content without permission to train AI models. This situation highlights the ongoing tensions between AI technology development and…
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OpenAI : Toward understanding and preventing misalignment generalization
Source URL: https://openai.com/index/emergent-misalignment Source: OpenAI Title: Toward understanding and preventing misalignment generalization Feedly Summary: We study how training on incorrect responses can cause broader misalignment in language models and identify an internal feature driving this behavior—one that can be reversed with minimal fine-tuning. AI Summary and Description: Yes Summary: The text discusses the potential negative…