Experimental News Clipping Site

Tag: data preprocessing

  • Cloud Blog: Accelerate your AI workloads with the Google Cloud Managed Lustre

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/storage-data-transfer/google-cloud-managed-lustre-for-ai-hpc/ Source: Cloud Blog Title: Accelerate your AI workloads with the Google Cloud Managed Lustre Feedly Summary: Today, we’re making it even easier to achieve breakthrough performance for your AI/ML workloads: Google Cloud Managed Lustre is now GA, and available in four distinct performance tiers that deliver throughput ranging from 125 MB/s, 250…

  • Hacker News: Apache Airflow: Key Use Cases, Architectural Insights, and Pro Tips

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    Kurt Seifried
    in

    Source URL: https://codingcops.com/apache-airflow/ Source: Hacker News Title: Apache Airflow: Key Use Cases, Architectural Insights, and Pro Tips Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses Apache Airflow, an open-source tool designed for managing complex workflows and big data pipelines. It highlights Airflow’s capabilities in orchestrating ETL processes, automating machine learning workflows,…

  • Hacker News: Yek: Serialize your code repo (or part of it) to feed into any LLM

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    Kurt Seifried
    in

    Source URL: https://github.com/bodo-run/yek Source: Hacker News Title: Yek: Serialize your code repo (or part of it) to feed into any LLM Feedly Summary: Comments AI Summary and Description: Yes **Short Summary with Insight:** The text presents a Rust-based tool called “yek” that automates the process of reading, chunking, and serializing text files within a repository…

  • Cloud Blog: Distributed data preprocessing with GKE and Ray: Scaling for the enterprise

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/preprocessing-large-datasets-with-ray-and-gke/ Source: Cloud Blog Title: Distributed data preprocessing with GKE and Ray: Scaling for the enterprise Feedly Summary: The exponential growth of machine learning models brings with it ever-increasing datasets. This data deluge creates a significant bottleneck in the Machine Learning Operations (MLOps) lifecycle, as traditional data preprocessing methods struggle to scale. The…

  • Cloud Blog: Supervised Fine Tuning for Gemini: A best practices guide

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/master-gemini-sft/ Source: Cloud Blog Title: Supervised Fine Tuning for Gemini: A best practices guide Feedly Summary: Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning…

  • Hacker News: LLäMmlein 1B and 120M – German-only decoder models

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    system automation
    in

    Source URL: https://www.informatik.uni-wuerzburg.de/datascience/projects/nlp/llammlein/ Source: Hacker News Title: LLäMmlein 1B and 120M – German-only decoder models Feedly Summary: Comments AI Summary and Description: Yes Summary: The text describes the development of two German-only decoder models, LLäMmlein 120M and 1B, highlighting their competitive performance against state-of-the-art models. This is particularly relevant for professionals in AI security and…