Experimental News Clipping Site

Tag: variability

  • Cloud Blog: New GKE inference capabilities reduce costs, tail latency and increase throughput

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/understanding-new-gke-inference-capabilities/ Source: Cloud Blog Title: New GKE inference capabilities reduce costs, tail latency and increase throughput Feedly Summary: When it comes to AI, inference is where today’s generative AI models can solve real-world business problems. Google Kubernetes Engine (GKE) is seeing increasing adoption of gen AI inference. For example, customers like HubX run…

  • The Register: Surprise! People don’t want AI deciding who gets a kidney transplant and who dies or endures years of misery

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.theregister.com/2025/03/08/ai_kidney_transplant_moral_decisions/ Source: The Register Title: Surprise! People don’t want AI deciding who gets a kidney transplant and who dies or endures years of misery Feedly Summary: Researchers find AI isn’t ready to help with moral decision making Is AI an appropriate source of moral guidance about which patients should be given kidney transplants?……

  • Simon Willison’s Weblog: Structured data extraction from unstructured content using LLM schemas

    —

    by

    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Feb/28/llm-schemas/#atom-everything Source: Simon Willison’s Weblog Title: Structured data extraction from unstructured content using LLM schemas Feedly Summary: LLM 0.23 is out today, and the signature feature is support for schemas – a new way of providing structured output from a model that matches a specification provided by the user. I’ve also upgraded both…

  • Schneier on Security: “Emergent Misalignment” in LLMs

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.schneier.com/blog/archives/2025/02/emergent-misalignment-in-llms.html Source: Schneier on Security Title: “Emergent Misalignment” in LLMs Feedly Summary: Interesting research: “Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs“: Abstract: We present a surprising result regarding LLMs and alignment. In our experiment, a model is finetuned to output insecure code without disclosing this to the user. The resulting model…

  • Hacker News: Evaluating modular RAG with reasoning models

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.kapa.ai/blog/evaluating-modular-rag-with-reasoning-models Source: Hacker News Title: Evaluating modular RAG with reasoning models Feedly Summary: Comments AI Summary and Description: Yes Summary: The text outlines the challenges and potential of Modular Retrieval-Augmented Generation (RAG) systems using reasoning models like o3-mini. It emphasizes the distinction between reasoning capabilities and practical experience in tool usage, highlighting insights…

  • The Register: DeepMind working on distributed training of large AI models

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.theregister.com/2025/02/11/deepmind_distributed_model_training_research/ Source: The Register Title: DeepMind working on distributed training of large AI models Feedly Summary: Alternate process could be a game changer if they can make it practicable Is distributed training the future of AI? As the shock of the DeepSeek release fades, its legacy may be an awareness that alternative approaches…

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

    —

    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…

  • Cloud Blog: ScatterBrain: Unmasking the Shadow of PoisonPlug’s Obfuscator

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/topics/threat-intelligence/scatterbrain-unmasking-poisonplug-obfuscator/ Source: Cloud Blog Title: ScatterBrain: Unmasking the Shadow of PoisonPlug’s Obfuscator Feedly Summary: Written by: Nino Isakovic Introduction Since 2022, Google Threat Intelligence Group (GTIG) has been tracking multiple cyber espionage operations conducted by China-nexus actors utilizing POISONPLUG.SHADOW. These operations employ a custom obfuscating compiler that we refer to as “ScatterBrain," facilitating…

  • Hacker News: Curl Project and Go Security Teams Reject CVSS as Broken

    —

    by

    Kurt Seifried
    in

    Source URL: https://socket.dev/blog/curl-project-and-go-security-teams-reject-cvss-as-broken Source: Hacker News Title: Curl Project and Go Security Teams Reject CVSS as Broken Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The debate surrounding the efficacy of the Common Vulnerability Scoring System (CVSS) is intensifying, particularly as key projects like cURL and Go distance themselves from it, advocating for context-driven…