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Tag: trained

  • Cloud Blog: Supercharge your AI: GKE inference reference architecture, your blueprint for production-ready inference

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/topics/developers-practitioners/supercharge-your-ai-gke-inference-reference-architecture-your-blueprint-for-production-ready-inference/ Source: Cloud Blog Title: Supercharge your AI: GKE inference reference architecture, your blueprint for production-ready inference Feedly Summary: The age of AI is here, and organizations everywhere are racing to deploy powerful models to drive innovation, enhance products, and create entirely new user experiences. But moving from a trained model in a…

  • Simon Willison’s Weblog: Qwen3-4B Instruct and Thinking

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/6/qwen3-4b-instruct-and-thinking/ Source: Simon Willison’s Weblog Title: Qwen3-4B Instruct and Thinking Feedly Summary: Qwen3-4B Instruct and Thinking Yet another interesting model from Qwen—these are tiny compared to their other recent releases (just 4B parameters, 7.5GB on Hugging Face and even smaller when quantized) but with a 262,144 context length, which Qwen suggest is essential…

  • Cisco Security Blog: Foundation-sec-8B-Instruct: An Out-of-the-Box Security Copilot

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    Kurt Seifried
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    Source URL: https://feedpress.me/link/23535/17112350/foundation-sec-8b-instruct-out-of-the-box-security-copilot Source: Cisco Security Blog Title: Foundation-sec-8B-Instruct: An Out-of-the-Box Security Copilot Feedly Summary: Foundation-sec-8B-Instruct layers instruction fine-tuning on top of our domain-focused base model, giving you a chat-native copilotthat understands security. AI Summary and Description: Yes Summary: The text describes a new method of fine-tuning AI models, specifically designed for security applications. This…

  • Shabie’s blog: Let the kaleidoscope turn

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    Kurt Seifried
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    Source URL: https://shabie.github.io/2025/07/31/let-the-kaleidoscope-turn.html Source: Shabie’s blog Title: Let the kaleidoscope turn Feedly Summary: “Any good classifier knows that in the process of classification, information about variety is lost while information about similarities is gained.” – Joseph Tainter AI Summary and Description: Yes Summary: The text discusses the limitations of traditional retrieval-augmented generation (RAG) systems in…

  • Simon Willison’s Weblog: Trying out Qwen3 Coder Flash using LM Studio and Open WebUI and LLM

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Jul/31/qwen3-coder-flash/ Source: Simon Willison’s Weblog Title: Trying out Qwen3 Coder Flash using LM Studio and Open WebUI and LLM Feedly Summary: Qwen just released their sixth model(!) for this July called Qwen3-Coder-30B-A3B-Instruct – listed as Qwen3-Coder-Flash in their chat.qwen.ai interface. It’s 30.5B total parameters with 3.3B active at any one time. This means…

  • Cloud Blog: Now GA: C4 VMs with Local SSD, bare metal, and larger shapes, on Intel Xeon 6

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/compute/c4-vms-based-on-intel-6th-gen-xeon-granite-rapids-now-ga/ Source: Cloud Blog Title: Now GA: C4 VMs with Local SSD, bare metal, and larger shapes, on Intel Xeon 6 Feedly Summary: We’re thrilled to announce a significant expansion of our C4 virtual machine series, with the general availability of 28 powerful new shapes. This expansion introduces C4 shapes with Google’s next-gen…

  • Schneier on Security: Subliminal Learning in AIs

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    Kurt Seifried
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    Source URL: https://www.schneier.com/blog/archives/2025/07/subliminal-learning-in-ais.html Source: Schneier on Security Title: Subliminal Learning in AIs Feedly Summary: Today’s freaky LLM behavior: We study subliminal learning, a surprising phenomenon where language models learn traits from model-generated data that is semantically unrelated to those traits. For example, a “student” model learns to prefer owls when trained on sequences of numbers…