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Tag: llm

  • Enterprise AI Trends: AI Agents Explained Without Hype, From The Ground Up

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    Kurt Seifried
    in

    Source URL: https://nextword.substack.com/p/ai-agents-explained-without-hype Source: Enterprise AI Trends Title: AI Agents Explained Without Hype, From The Ground Up Feedly Summary: AI agents are Big Data and Data Science in 2013 all over again. Everyone talks about it, but they all think different things. This causes marketing and sales challenges. AI Summary and Description: Yes Summary: The…

  • Hacker News: Jeremy Howard taught AI and helped invent ChatGPT. He fears he’s failed

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    by

    Kurt Seifried
    in

    Source URL: https://www.abc.net.au/news/science/2023-11-15/jeremy-howard-taught-ai-to-the-world-and-helped-invent-chatgpt/103092474 Source: Hacker News Title: Jeremy Howard taught AI and helped invent ChatGPT. He fears he’s failed Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides an overview of Jeremy Howard’s contributions to the development of natural language processing (NLP) and large language models (LLMs), ultimately leading to tools like…

  • Hacker News: We hacked Google’s A.I Gemini and leaked its source code (at least some part)

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    by

    Kurt Seifried
    in

    Source URL: https://www.landh.tech/blog/20250327-we-hacked-gemini-source-code/ Source: Hacker News Title: We hacked Google’s A.I Gemini and leaked its source code (at least some part) Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the hacker team’s experience at the Google LLM bugSWAT event, focusing on their discovery of vulnerabilities in Google’s Gemini AI model. The…

  • Hacker News: Gemini hackers can deliver more potent attacks with a helping hand from Gemini

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    by

    Kurt Seifried
    in

    Source URL: https://arstechnica.com/security/2025/03/gemini-hackers-can-deliver-more-potent-attacks-with-a-helping-hand-from-gemini/ Source: Hacker News Title: Gemini hackers can deliver more potent attacks with a helping hand from Gemini Feedly Summary: Comments AI Summary and Description: Yes Summary: The provided text discusses the emerging threat of indirect prompt injection attacks on large language models (LLMs) like OpenAI’s GPT-3, GPT-4, and Google’s Gemini. It outlines…

  • Hacker News: The Great Chatbot Debate – March 25th

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    by

    Kurt Seifried
    in

    Source URL: https://computerhistory.org/events/great-chatbot-debate/ Source: Hacker News Title: The Great Chatbot Debate – March 25th Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses an upcoming live debate regarding the nature of large language models (LLMs) and raises important questions about their understanding and capabilities. This discourse is relevant for professionals in AI…

  • Wired: Anthropic’s Claude Is Good at Poetry—and Bullshitting

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    Kurt Seifried
    in

    Source URL: https://www.wired.com/story/plaintext-anthropic-claude-brain-research/ Source: Wired Title: Anthropic’s Claude Is Good at Poetry—and Bullshitting Feedly Summary: Researchers looked inside the chatbot’s “brain.” The results were surprisingly chilling. AI Summary and Description: Yes Summary: The text discusses the challenges researchers face in describing Anthropic’s large language model, Claude, while avoiding anthropomorphism. The release of new papers highlights…

  • Slashdot: Anthropic Maps AI Model ‘Thought’ Processes

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    by

    Kurt Seifried
    in

    Source URL: https://slashdot.org/story/25/03/28/0614200/anthropic-maps-ai-model-thought-processes?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Anthropic Maps AI Model ‘Thought’ Processes Feedly Summary: AI Summary and Description: Yes Summary: The text discusses a recent advancement in understanding large language models (LLMs) through the development of a “cross-layer transcoder” (CLT). By employing techniques similar to functional MRI, researchers can visualize the internal processing of LLMs,…

  • Hacker News: Every Flop Counts: Scaling a 300B LLM Without Premium GPUs

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    by

    Kurt Seifried
    in

    Source URL: https://arxiv.org/abs/2503.05139 Source: Hacker News Title: Every Flop Counts: Scaling a 300B LLM Without Premium GPUs Feedly Summary: Comments AI Summary and Description: Yes Summary: This technical report presents advancements in training large-scale Mixture-of-Experts (MoE) language models, namely Ling-Lite and Ling-Plus, highlighting their efficiency and comparable performance to industry benchmarks while significantly reducing training…