Experimental News Clipping Site

Tag: Jupyter Notebook

  • Docker: From Shell Scripts to Science Agents: How AI Agents Are Transforming Research Workflows

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    Kurt Seifried
    in

    Source URL: https://www.docker.com/blog/ai-science-agents-research-workflows/ Source: Docker Title: From Shell Scripts to Science Agents: How AI Agents Are Transforming Research Workflows Feedly Summary: It’s 2 AM in a lab somewhere. A researcher has three terminals open, a half-written Jupyter notebook on one screen, an Excel sheet filled with sample IDs on another, and a half-eaten snack next…

  • Hamel’s Blog: Selecting The Right AI Evals Tool

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    Kurt Seifried
    in

    Source URL: https://hamel.dev/blog/posts/eval-tools/ Source: Hamel’s Blog Title: Selecting The Right AI Evals Tool Feedly Summary: Over the past year, I’ve focused heavily on AI Evals, both in my consulting work and teaching. A question I get constantly is, “What’s the best tool for evals?”. I’ve always resisted answering directly for two reasons. First, people focus…

  • Cloud Blog: Google Distributed Cloud at the edge powers U.S. Air Force Mobility Guardian 2025

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/topics/public-sector/google-distributed-cloud-at-the-edge-powers-us-air-force-mobility-guardian-2025/ Source: Cloud Blog Title: Google Distributed Cloud at the edge powers U.S. Air Force Mobility Guardian 2025 Feedly Summary: For today’s mission owner, operating effectively in denied, degraded, intermittent, and limited bandwidth (DDIL) environments is paramount. The Department of Defense’s strategy requires smaller, dispersed teams to function autonomously, creating a critical need…

  • Cloud Blog: AI Hypercomputer developer experience enhancements from Q1 25: build faster, scale bigger

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/compute/ai-hypercomputer-enhancements-for-the-developer/ Source: Cloud Blog Title: AI Hypercomputer developer experience enhancements from Q1 25: build faster, scale bigger Feedly Summary: Building cutting-edge AI models is exciting, whether you’re iterating in your notebook or orchestrating large clusters. However, scaling up training can present significant challenges, including navigating complex infrastructure, configuring software and dependencies across numerous…

  • Hacker News: The Dino, the Llama, and the Whale (Deno and Jupyter for Local AI Experiments)

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    Kurt Seifried
    in

    Source URL: https://deno.com/blog/the-dino-llama-and-whale Source: Hacker News Title: The Dino, the Llama, and the Whale (Deno and Jupyter for Local AI Experiments) Feedly Summary: Comments AI Summary and Description: Yes Summary: The text outlines the author’s journey in experimenting with a locally hosted large language model (LLM) using various tools such as Deno, Jupyter Notebook, and…

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

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    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: Announcing the general availability of Spanner Graph

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/databases/spanner-graph-is-now-ga/ Source: Cloud Blog Title: Announcing the general availability of Spanner Graph Feedly Summary: In today’s complex digital world, building truly intelligent applications requires more than just raw data — you need to understand the intricate relationships within that data. Graph analysis helps reveal these hidden connections, and when combined with techniques like…

  • Hacker News: Optimizing Jupyter Notebooks for LLMs

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    Kurt Seifried
    in

    Source URL: https://www.alexmolas.com/2025/01/15/ipynb-for-llm.html Source: Hacker News Title: Optimizing Jupyter Notebooks for LLMs Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses optimizing Jupyter Notebooks for use with Large Language Models (LLMs), highlighting an experience of unexpected cost surges due to the verbose nature of .ipynb files. It provides practical solutions for reducing…