Experimental News Clipping Site

Tag: pytorch

  • Simon Willison’s Weblog: Defeating Nondeterminism in LLM Inference

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Sep/11/defeating-nondeterminism/#atom-everything Source: Simon Willison’s Weblog Title: Defeating Nondeterminism in LLM Inference Feedly Summary: Defeating Nondeterminism in LLM Inference A very common question I see about LLMs concerns why they can’t be made to deliver the same response to the same prompt by setting a fixed random number seed. Like many others I had…

  • Cloud Blog: The Dataproc advantage: Advanced Spark features that will transform your analytics and AI

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/data-analytics/why-use-dataproc-for-your-apache-spark-environment/ Source: Cloud Blog Title: The Dataproc advantage: Advanced Spark features that will transform your analytics and AI Feedly Summary: With its exceptional price-performance, Google Cloud’s Dataproc has evolved from a simple, managed open-source software (OSS) service to a powerhouse in Apache Spark and open lakehouses, driving the analytics and AI workloads of…

  • Cloud Blog: Announcing a new monitoring library to optimize TPU performance

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/compute/new-monitoring-library-to-optimize-google-cloud-tpu-resources/ Source: Cloud Blog Title: Announcing a new monitoring library to optimize TPU performance Feedly Summary: For more than a decade, TPUs have powered Google’s most demanding AI training and serving workloads. And there is strong demand from customers for Cloud TPUs as well. When running advanced AI workloads, you need to be…

  • Docker: Behind the scenes: How we designed Docker Model Runner and what’s next

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    by

    Kurt Seifried
    in

    Source URL: https://www.docker.com/blog/behind-the-scenes-how-we-designed-docker-model-runner-and-whats-next/ Source: Docker Title: Behind the scenes: How we designed Docker Model Runner and what’s next Feedly Summary: The last few years have made it clear that AI models will continue to be a fundamental component of many applications. The catch is that they’re also a fundamentally different type of component, with complex…