Experimental News Clipping Site

Tag: language model applications

  • CSA: How the OWASP Top 10 for LLM Applications Supports AI

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    Kurt Seifried
    in

    Source URL: https://cloudsecurityalliance.org/articles/how-the-owasp-top-10-for-llm-applications-supports-the-ai-revolution Source: CSA Title: How the OWASP Top 10 for LLM Applications Supports AI Feedly Summary: AI Summary and Description: Yes Summary: The text discusses the introduction of the OWASP Top 10 for Large Language Model Applications, which outlines critical vulnerabilities specific to LLM applications. Emphasizing the importance of understanding security risks associated…

  • Hacker News: Calculate the number of language model tokens for a string

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    by

    Kurt Seifried
    in

    Source URL: https://blog.mastykarz.nl/calculate-number-language-model-tokens-string/ Source: Hacker News Title: Calculate the number of language model tokens for a string Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides guidance on calculating the number of language model tokens for a given string, which is essential for developers working with AI and NLP applications. The method…

  • Hacker News: Qwen2.5-1M: Deploy Your Own Qwen with Context Length Up to 1M Tokens

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    by

    Kurt Seifried
    in

    Source URL: https://qwenlm.github.io/blog/qwen2.5-1m/ Source: Hacker News Title: Qwen2.5-1M: Deploy Your Own Qwen with Context Length Up to 1M Tokens Feedly Summary: Comments AI Summary and Description: Yes Summary: The text reports on the new release of the open-source Qwen2.5-1M models, capable of processing up to one million tokens, significantly improving inference speed and model performance…

  • Cloud Blog: Powerful infrastructure innovations for your AI-first future

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    system automation
    in

    Source URL: https://cloud.google.com/blog/products/compute/trillium-sixth-generation-tpu-is-in-preview/ Source: Cloud Blog Title: Powerful infrastructure innovations for your AI-first future Feedly Summary: The rise of generative AI has ushered in an era of unprecedented innovation, demanding increasingly complex and more powerful AI models. These advanced models necessitate high-performance infrastructure capable of efficiently scaling AI training, tuning, and inferencing workloads while optimizing…