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    <title>Learn about Pinpoint - Pinpoint Help</title>
    <dc:date>2026-06-05T21:46:55+00:00</dc:date>
    <link>https://support.google.com/pinpoint/answer/17007004</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Pinpoint is an AI-powered research platform designed to help journalists and academics analyze large collections of documents. With Pinpoint, you can:

Analyze massive collections: Easily search, filter, transcribe and organize thousands of documents, including PDFs, images, and audio files.
Leverage generative AI: Use Gemini's capabilities to answer research questions together with supporting evidence found in your documents.
Foster collaborative research: share your work with colleagues and tackle large scale projects as a team. You can also publicly share - supporting community-driven research.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:b11108685683/</dc:identifier>
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    <title>Google DeepMind Workers Vote to Unionize Over Military AI Deals</title>
    <dc:date>2026-05-06T11:31:52+00:00</dc:date>
    <link>https://www.wired.com/story/google-deepmind-workers-vote-to-unionize-over-military-ai-deals/?utm_mailing=WIR_Daily_050626_UNPAID&amp;bxid=5c48db8cfc942d0477965f00&amp;cndid=16546997&amp;hasha=e8605e5d8d0f312f10844b8980373038&amp;hashc=c8722d00b579ef5fe678e67148af2c251bdd162b3b18a9802bd8134858e9fceb&amp;esrc=Wired_etl_load</link>
    <dc:creator>amy</dc:creator><description><![CDATA[UK staff of Google’s AI research lab hope to block the use of the company’s artificial intelligence models in military settings.]]></description>
<dc:subject>google unionizing</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:b3af6a2c5188/</dc:identifier>
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    <title>This guide covers running **Gemma 4 26B MOE** (Mixture of Experts) locally on an Apple Silicon Mac using llama.cpp with memory-mapped files. The MOE architecture activates only 8 of 128 experts per token, making it incredibly efficient. · GitHub</title>
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    <link>https://gist.github.com/imaurer/00059ab1c60abab16804ad8e22715bf1</link>
    <dc:creator>amy</dc:creator><description><![CDATA[This guide covers running **Gemma 4 26B MOE** (Mixture of Experts) locally on an Apple Silicon Mac using llama.cpp with memory-mapped files. The MOE architecture activates only 8 of 128 experts per token, making it incredibly efficient]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:33df53d81bc2/</dc:identifier>
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    <title>llm-d officially a CNCF Sandbox project | Google Cloud Blog</title>
    <dc:date>2026-03-26T00:15:59+00:00</dc:date>
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    <dc:creator>amy</dc:creator><description><![CDATA[Sean Horgan
Product Manager
Abdel Sghiouar
Senior Cloud Developer Advocate]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:76e7df5789ff/</dc:identifier>
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    <title>Google Has a Secret Reference Desk. Here's How to Use It.</title>
    <dc:date>2026-03-22T16:45:06+00:00</dc:date>
    <link>https://cardcatalogforlife.substack.com/p/google-has-a-secret-reference-desk?triedRedirect=true</link>
    <dc:creator>amy</dc:creator><description><![CDATA[40 Google features to find exactly what you need, the alternative search engines that do things Google won't, and the reference desk framework underneath all of it.]]></description>
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<dc:identifier>https://pinboard.in/u:amy/b:503017f96f19/</dc:identifier>
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    <title>Alphabet president Ruth Porat heaps praise on Trump and offers Google’s assistance</title>
    <dc:date>2026-03-05T17:38:18+00:00</dc:date>
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    <dc:creator>amy</dc:creator><description><![CDATA[The tech industry is only working for itself. It seems like Musk, Zuckerberg, Tim Cook, and Google execs are trying to outdo one another in sucking up to Trump.]]></description>
<dc:subject>google politics</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:7aadecbd6e27/</dc:identifier>
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    <dc:date>2026-01-28T15:31:45+00:00</dc:date>
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    <dc:creator>amy</dc:creator><description><![CDATA[Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability]]></description>
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<dc:identifier>https://pinboard.in/u:amy/b:cfa410de7b51/</dc:identifier>
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    <title>AI Agent Engineering in Go with the Google ADK | by Karl Weinmeister | Google Cloud - Community | Jan, 2026 | Medium</title>
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    <link>https://medium.com/google-cloud/ai-agent-engineering-in-go-with-the-google-adk-4f2a992c6db4</link>
    <dc:creator>amy</dc:creator><dc:subject>golang google machine_learning</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:509908b50334/</dc:identifier>
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    <title>&quot;Allow for session&quot; only allows once for shell commands that include a path · Issue #16750 · google-gemini/gemini-cli</title>
    <dc:date>2026-01-20T22:03:02+00:00</dc:date>
    <link>https://github.com/google-gemini/gemini-cli/issues/16750?_bhlid=c7bb13bb8a59dea9b1872228cf2ecb6aa41b4ec7</link>
    <dc:creator>amy</dc:creator><dc:subject>amusements machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:d15237887cdb/</dc:identifier>
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    <title>Joint statement from Google and Apple</title>
    <dc:date>2026-01-12T22:52:08+00:00</dc:date>
    <link>https://blog.google/company-news/inside-google/company-announcements/joint-statement-google-apple/</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Apple and Google have entered into a multi-year collaboration under which the next generation of Apple Foundation Models will be based on Google's Gemini models and cloud technology. These models will help power future Apple Intelligence features, including a more personalized Siri coming this year.
After careful evaluation, Apple determined that Google's Al technology provides the most capable foundation for Apple Foundation Models and is excited about the innovative new experiences it will unlock for Apple users. Apple Intelligence will continue to run on Apple devices and Private Cloud Compute, while maintaining Apple's industry-leading privacy standards.]]></description>
<dc:subject>machine_learning google apple</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:31ab080b794d/</dc:identifier>
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    <title>Jules - An Autonomous Coding Agent</title>
    <dc:date>2026-01-10T15:46:29+00:00</dc:date>
    <link>https://jules.google/</link>
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    <dc:date>2026-01-10T15:44:31+00:00</dc:date>
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<item rdf:about="https://minimaxir.com/2025/12/nano-banana-pro/">
    <title>Nano Banana Pro is the best AI image generator, with caveats | Max Woolf's Blog</title>
    <dc:date>2026-01-08T23:49:40+00:00</dc:date>
    <link>https://minimaxir.com/2025/12/nano-banana-pro/</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:1a0aeb2df08d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://minimaxir.com/2025/11/nano-banana-prompts/">
    <title>Nano Banana can be prompt engineered for extremely nuanced AI image generation</title>
    <dc:date>2026-01-08T23:49:18+00:00</dc:date>
    <link>https://minimaxir.com/2025/11/nano-banana-prompts/</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Nano Banana allows 32,768 input tokens and I’m going to try to use them all dammit.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:42883164ecf0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://cloud.google.com/blog/topics/developers-practitioners/production-ready-ai-with-google-cloud-learning-path">
    <title>Production-Ready AI with Google Cloud Learning Path | Google Cloud Blog</title>
    <dc:date>2025-12-26T16:12:41+00:00</dc:date>
    <link>https://cloud.google.com/blog/topics/developers-practitioners/production-ready-ai-with-google-cloud-learning-path</link>
    <dc:creator>amy</dc:creator><description><![CDATA[We're excited to launch the Production-Ready AI with Google Cloud Learning Path, a free series designed to take your AI projects from prototype to production.
This page is the central hub for the curriculum. We'll be updating it weekly with new modules from now through mid-December.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:f393be76e63b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.cnbc.com/2025/12/20/josh-woodward-google-gemini-ai-safety.html">
    <title>Google was at risk of losing dominance until promoting Josh Woodward</title>
    <dc:date>2025-12-26T16:05:36+00:00</dc:date>
    <link>https://www.cnbc.com/2025/12/20/josh-woodward-google-gemini-ai-safety.html</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:fec69ea23f99/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://abseil.io/fast/hints.html">
    <title>abseil / Performance Hints</title>
    <dc:date>2025-12-19T23:26:58+00:00</dc:date>
    <link>https://abseil.io/fast/hints.html</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Over the years, we (Jeff & Sanjay) have done a fair bit of diving into performance tuning of various pieces of code, and improving the performance of our software has been important from the very earliest days of Google, since it lets us do more for more users. We wrote this document as a way of identifying some general principles and specific techniques that we use when doing this sort of work, and tried to pick illustrative source code changes (change lists, or CLs) that provide examples of the various approaches and techniques. Most of the concrete suggestions below reference C++ types and CLs, but the general principles apply to other languages. The document focuses on general performance tuning in the context of a single binary, and does not cover distributed systems or machine learning (ML) hardware performance tuning (huge areas unto themselves). We hope others will find this useful.]]></description>
<dc:subject>computing google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:9ad6cec951f3/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:computing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://antigravity.google/">
    <title>Google Antigravity</title>
    <dc:date>2025-12-13T15:59:12+00:00</dc:date>
    <link>https://antigravity.google/</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:7d0832beba70/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://developers.googleblog.com/en/introducing-code-wiki-accelerating-your-code-understanding/?trk=feed_main-feed-card_feed-article-content">
    <title>Introducing Code Wiki: Accelerating your code understanding - Google Developers Blog</title>
    <dc:date>2025-11-30T14:16:38+00:00</dc:date>
    <link>https://developers.googleblog.com/en/introducing-code-wiki-accelerating-your-code-understanding/?trk=feed_main-feed-card_feed-article-content</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google documentation</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:95196f25a0d6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:documentation"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://cloud.google.com/blog/products/containers-kubernetes/how-we-built-a-130000-node-gke-cluster">
    <title>How we built a 130,000-node GKE cluster | Google Cloud Blog</title>
    <dc:date>2025-11-30T04:26:55+00:00</dc:date>
    <link>https://cloud.google.com/blog/products/containers-kubernetes/how-we-built-a-130000-node-gke-cluster</link>
    <dc:creator>amy</dc:creator><dc:subject>google kubernetes k8s</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:2c63f97ae4f1/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:kubernetes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:k8s"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://medium.com/@carinaclaassen13/7-emerging-trends-in-agentic-evaluation-920fdc30eb14">
    <title>7 Emerging Trends in Agentic Evaluation | by Carina Claassen | Nov, 2025 | Medium</title>
    <dc:date>2025-11-26T22:06:12+00:00</dc:date>
    <link>https://medium.com/@carinaclaassen13/7-emerging-trends-in-agentic-evaluation-920fdc30eb14</link>
    <dc:creator>amy</dc:creator><description><![CDATA[The biggest challenge in agentic AI isn’t building the agent — it’s building the guardrails.
As an AI engineer at Google, I have spent the past year focused on the evaluation and improvement of agentic systems across various generative media applications. This work has surfaced seven key trends invaluable for anyone looking to transform evaluation into a powerful tool for improving the transparency, reliability, and steerability of agentic systems.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:55aada02f043/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://stocks.apple.com/A3_7cl_47TK28sruL2Rz3xg">
    <title>Why Google’s AI Wins Are Bad News for Nvidia Stock and the AI Trade — Barron’s</title>
    <dc:date>2025-11-24T22:25:33+00:00</dc:date>
    <link>https://stocks.apple.com/A3_7cl_47TK28sruL2Rz3xg</link>
    <dc:creator>amy</dc:creator><description><![CDATA[This isn’t a DeepSeek moment. It is much, much bigger.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:7d3ceeb147b4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://lakshmanok.medium.com/im-proven-wrong-on-playbooks-and-google-adk-a760bc0f5be3">
    <title>I’m proven wrong on Playbooks and Google ADK | by Lak Lakshmanan | Nov, 2025 | Medium</title>
    <dc:date>2025-11-24T18:51:52+00:00</dc:date>
    <link>https://lakshmanok.medium.com/im-proven-wrong-on-playbooks-and-google-adk-a760bc0f5be3</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:1fc41c006f0c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.tensorflow.org/datasets/catalog/c4">
    <title>c4  |  TensorFlow Datasets</title>
    <dc:date>2025-11-10T18:42:57+00:00</dc:date>
    <link>https://www.tensorflow.org/datasets/catalog/c4</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning big_data google common_crawl</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:c0f77e56e7f9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:big_data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:common_crawl"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.theguardian.com/us-news/2025/oct/29/google-amazon-israel-contract-secret-code">
    <title>Revealed: Israel demanded Google and Amazon use secret ‘wink’ to sidestep legal orders | US news | The Guardian</title>
    <dc:date>2025-11-09T16:59:37+00:00</dc:date>
    <link>https://www.theguardian.com/us-news/2025/oct/29/google-amazon-israel-contract-secret-code</link>
    <dc:creator>amy</dc:creator><description><![CDATA[...For Israel, losing control of its data to authorities overseas was a significant concern. So to deal with the threat, officials created a secret warning system: the companies must send signals hidden in payments to the Israeli government, tipping it off when it has disclosed Israeli data to foreign courts or investigators.

To clinch the lucrative contract, Google and Amazon agreed to the so-called winking mechanism, according to leaked documents seen by the Guardian, as part of a joint investigation with Israeli-Palestinian publication +972 Magazine and Hebrew-language outlet Local Call.
]]></description>
<dc:subject>google amazon ughh</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:amy/b:8170f5e92d99/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:amazon"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:ughh"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.youtube.com/watch?v=hLSTGgc7gDc&amp;trk=feed_main-feed-card_ingested-content-summary-external-video-content">
    <title>Building agentic RAG for e-commerce with ADK and Vector Search</title>
    <dc:date>2025-10-25T00:23:00+00:00</dc:date>
    <link>https://www.youtube.com/watch?v=hLSTGgc7gDc&amp;trk=feed_main-feed-card_ingested-content-summary-external-video-content</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Experience how AI agents can revolutionize shopping by understanding your personal style, tastes and preferences to anticipate your needs and offer tailored ...]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:b29adf7cb9f7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://blog.vllm.ai/2025/10/16/vllm-tpu.html">
    <title>vLLM TPU: A New Unified Backend Supporting PyTorch and JAX on TPU</title>
    <dc:date>2025-10-19T02:52:41+00:00</dc:date>
    <link>https://blog.vllm.ai/2025/10/16/vllm-tpu.html</link>
    <dc:creator>amy</dc:creator><description><![CDATA[vLLM is a fast and easy-to-use library for LLM inference and serving.]]></description>
<dc:subject>machine_learning google llms</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:3a4e2a49333d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:llms"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://ai.google.dev/gemini-api/docs/image-generation">
    <title>Image generation with Gemini (aka Nano Banana)  |  Gemini API  |  Google AI for Developers</title>
    <dc:date>2025-10-08T15:28:56+00:00</dc:date>
    <link>https://ai.google.dev/gemini-api/docs/image-generation</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Get started generating images with the Gemini API]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:07c046836348/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://developers.googleblog.com/en/gemini-2-5-flash-image-now-ready-for-production-with-new-aspect-ratios/">
    <title>Gemini 2.5 Flash Image now ready for production with new aspect ratios - Google Developers Blog</title>
    <dc:date>2025-10-08T15:27:29+00:00</dc:date>
    <link>https://developers.googleblog.com/en/gemini-2-5-flash-image-now-ready-for-production-with-new-aspect-ratios/</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Nano Banana]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:5d71d3689512/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://medium.com/google-cloud/build-a-gemini-full-stack-research-agent-with-agent-development-kit-11192e8e9165?trk=feed_main-feed-card_reshare_feed-article-content">
    <title>Build a Gemini Full-Stack Research Agent with Agent Development Kit</title>
    <dc:date>2025-10-08T14:15:30+00:00</dc:date>
    <link>https://medium.com/google-cloud/build-a-gemini-full-stack-research-agent-with-agent-development-kit-11192e8e9165?trk=feed_main-feed-card_reshare_feed-article-content</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Built to demonstrate how ADK helps structure complex agentic workflows, build modular agents, and incorporate HITL steps.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:34f5ddf0c4f0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://blog.lmcache.ai/2025-10-07-LMCache-on-GKE/?trk=feed_main-feed-card_feed-article-content">
    <title>LMCache on Google Kubernetes Engine: Boosting LLM Inference Performance with KV Cache on Tiered Storage | LMCache blog website</title>
    <dc:date>2025-10-08T14:06:10+00:00</dc:date>
    <link>https://blog.lmcache.ai/2025-10-07-LMCache-on-GKE/?trk=feed_main-feed-card_feed-article-content</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Overview of the Collaboration The KV Cache is a memory optimization that makes Large Language Models(LLMs) run the forward pass faster by storing Key (K) and Value (V) matrices to prevent the model from recalculating them for the entire text sequence with every new generated token. Maximizing the KV Cache...]]></description>
<dc:subject>machine_learning google kubernetes k8s</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:dd0c605946a5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:kubernetes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:k8s"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://deepmind.google/discover/blog/introducing-codemender-an-ai-agent-for-code-security/">
    <title>Google DeepMind introduces new AI agent for code security</title>
    <dc:date>2025-10-08T02:19:50+00:00</dc:date>
    <link>https://deepmind.google/discover/blog/introducing-codemender-an-ai-agent-for-code-security/</link>
    <dc:creator>amy</dc:creator><description><![CDATA[CodeMender is a new AI-powered agent that improves code security automatically. It instantly patches new software vulnerabilities, and rewrites and secures existing code, eliminating entire...]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:fb6165a4f7f3/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://codelabs.developers.google.com/codelabs/cloud-run/tools-make-an-agent">
    <title>Tools Make an Agent: From Zero to Assistant with ADK  |  Google Codelabs</title>
    <dc:date>2025-10-02T17:08:38+00:00</dc:date>
    <link>https://codelabs.developers.google.com/codelabs/cloud-run/tools-make-an-agent</link>
    <dc:creator>amy</dc:creator><dc:subject>google machine_learning</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:394ed144d61c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://medium.com/google-cloud/build-a-gemini-full-stack-research-agent-with-agent-development-kit-11192e8e9165">
    <title>Build a Gemini Full-Stack Research Agent with Agent Development Kit | by Debi Cabrera - Googler | Google Cloud - Community | Sep, 2025 | Medium</title>
    <dc:date>2025-10-02T15:31:07+00:00</dc:date>
    <link>https://medium.com/google-cloud/build-a-gemini-full-stack-research-agent-with-agent-development-kit-11192e8e9165</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:1d707330d6dd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/alokpattani/ai-agents/tree/main/pdf_data_extraction_agent">
    <title>ai-agents/pdf_data_extraction_agent at main · alokpattani/ai-agents · GitHub</title>
    <dc:date>2025-10-01T17:09:41+00:00</dc:date>
    <link>https://github.com/alokpattani/ai-agents/tree/main/pdf_data_extraction_agent</link>
    <dc:creator>amy</dc:creator><description><![CDATA[PDF Data Extraction Agent

Data extraction agent to extract data found in a PDF provided by the user into a more structured CSV or JSON file. The agent looks to determine the output schema itself before doing any extraction, with input from the user to guide it.

Builds on data extraction agent used in demo at 2025 USOPC Performance Innovation Summit]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:f3ea4072adf5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://cloud.google.com/blog/topics/developers-practitioners/announcing-the-new-practical-guide-to-data-science-on-google-cloud?trk=feed_main-feed-card_feed-article-content">
    <title>Announcing the new Practical Guide to Data Science on Google Cloud | Google Cloud Blog</title>
    <dc:date>2025-09-28T15:26:03+00:00</dc:date>
    <link>https://cloud.google.com/blog/topics/developers-practitioners/announcing-the-new-practical-guide-to-data-science-on-google-cloud?trk=feed_main-feed-card_feed-article-content</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Learn how to leverage Google Cloud's BigQuery, Serverless Spark, and Vertex AI for modern data science workflows. This guide covers unified tooling, end-to-end solutions, and real-world use cases with code examples.]]></description>
<dc:subject>google data_science</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:9e597cccec8e/</dc:identifier>
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<item rdf:about="https://cloud.google.com/blog/products/compute/introducing-flex-start-vms-for-the-compute-engine-instance-api?trk=feed-detail_main-feed-card_feed-article-content">
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    <dc:creator>amy</dc:creator><description><![CDATA[Flex-start VMs, powered by Dynamic Workload Scheduler, let you create single VM instances with fair and improved access to GPUs.]]></description>
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<dc:identifier>https://pinboard.in/u:amy/b:b240b155211d/</dc:identifier>
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<item rdf:about="https://medium.com/google-cloud/build-a-gemini-full-stack-research-agent-with-agent-development-kit-11192e8e9165?trk=feed_main-feed-card_feed-article-content">
    <title>Build a Gemini Full-Stack Research Agent with Agent Development Kit</title>
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    <dc:creator>amy</dc:creator><description><![CDATA[Built to demonstrate how ADK helps structure complex agentic workflows, build modular agents, and incorporate HITL steps.]]></description>
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<item rdf:about="https://cloud.google.com/architecture/multiagent-ai-system">
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    <dc:date>2025-09-20T15:25:24+00:00</dc:date>
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<dc:identifier>https://pinboard.in/u:amy/b:805100388293/</dc:identifier>
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<item rdf:about="https://support.google.com/websearch/answer/16420827?hl=en">
    <title>Use Deep Search in AI Mode for in-depth research - Google Search Help</title>
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    <link>https://support.google.com/websearch/answer/16420827?hl=en</link>
    <dc:creator>amy</dc:creator><description><![CDATA[For questions where you want an even more thorough response, try Deep Search in AI Mode — our most advanced research tool in Google Search. Built with the Gemini 2.5 Pro model, it browses hundreds of sites and reasons across them, crafting a comprehensive, fully-cited report in just minutes. Deep Search is available to Google AI subscribers in Labs.]]></description>
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<dc:identifier>https://pinboard.in/u:amy/b:0327fd6fb172/</dc:identifier>
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<item rdf:about="https://medium.com/google-cloud/now-available-direct-importing-from-bigquery-to-vector-search-f4ba01b48dfd">
    <title>Now available: Direct Importing from BigQuery to Vector Search | by Kaz Sato | Google Cloud - Community | Aug, 2025 | Medium</title>
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<item rdf:about="https://blog.google/intl/en-mena/product-updates/explore-get-answers/nano-banana-image-editing-in-gemini-just-got-a-major-upgrade/">
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<item rdf:about="https://labs.google/fx/tools/flow">
    <title>Flow</title>
    <dc:date>2025-08-05T04:04:07+00:00</dc:date>
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<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
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<item rdf:about="https://cloud.google.com/blog/topics/developers-practitioners/implementing-high-performance-llm-serving-on-gke-an-inference-gateway-walkthrough">
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Generative models are often unaware of recent API updates and may suggest outdated or legacy code. You can copy and paste the instructions from this file into your development environment to provide the model with the necessary context.]]></description>
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    <dc:creator>amy</dc:creator><description><![CDATA[Agentic Design Patterns  A Hands-On Guide to Building Intelligent Systems, Antonio Gulli Table of Contents - total 405 pages   = 1+2+1+1+4+9+103+61+34+114+55+5+4 11 Acknowledgement list (Add your name here if you provided feedback and wanted to be listed) Dedication, 1 page  Acknowledgment, 2 pa...]]></description>
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<dc:identifier>https://pinboard.in/u:amy/b:e18c79d38411/</dc:identifier>
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<item rdf:about="https://codelabs.developers.google.com/bigquery-dataframes-iowa-liquor-sales">
    <title>Exploratory data analysis of Iowa liquor sales using the BigQuery DataFrames package</title>
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    <link>https://codelabs.developers.google.com/bigquery-dataframes-iowa-liquor-sales</link>
    <dc:creator>amy</dc:creator><description><![CDATA[In this lab, you will use BigQuery DataFrames from a Python notebook in BigQuery Studio to clean and analyze the Iowa liquor sales public dataset. Make use of BigQuery ML and remote function capabilities to discover insights]]></description>
<dc:subject>bigquery big_data google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:e990dd6ac4ab/</dc:identifier>
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<item rdf:about="https://cloud.google.com/gov/federal-defense-and-intel">
    <title>Department of Defense | Google Cloud</title>
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<item rdf:about="https://blog.google/technology/developers/introducing-gemini-cli-open-source-ai-agent/">
    <title>Google announces Gemini CLI: your open-source AI agent</title>
    <dc:date>2025-07-04T23:20:45+00:00</dc:date>
    <link>https://blog.google/technology/developers/introducing-gemini-cli-open-source-ai-agent/</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google genAI</dc:subject>
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<item rdf:about="https://gemini.google/overview/gems/?hl=en">
    <title>Gemini Gems — build custom AI experts from Gemini</title>
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    <link>https://gemini.google/overview/gems/?hl=en</link>
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<dc:identifier>https://pinboard.in/u:amy/b:dadf839fd3fc/</dc:identifier>
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<item rdf:about="https://www.theverge.com/decoder-podcast-with-nilay-patel/673638/google-ceo-sundar-pichai-interview-ai-search-web-future">
    <title>Google CEO Sundar Pichai says AI will be ‘bigger than the internet’ | The Verge</title>
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<dc:identifier>https://pinboard.in/u:amy/b:a312cd84eea0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
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<item rdf:about="https://github.com/google-gemini/gemini-cli">
    <title>GitHub - google-gemini/gemini-cli: An open-source AI agent that brings the power of Gemini directly into your terminal.</title>
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    <dc:creator>amy</dc:creator><description><![CDATA[An open-source AI agent that brings the power of Gemini directly into your terminal.]]></description>
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<dc:identifier>https://pinboard.in/u:amy/b:c1308985b2d1/</dc:identifier>
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<item rdf:about="https://www.linkedin.com/pulse/structured-output-gemma3-ali-afshar-nadae?trk=article-ssr-frontend-pulse-lite_little-text-block">
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    <dc:creator>amy</dc:creator><description><![CDATA[Ali Afshar
Ollama, Pydantic]]></description>
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<dc:identifier>https://pinboard.in/u:amy/b:9c8a89db803f/</dc:identifier>
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<item rdf:about="https://www.linkedin.com/pulse/from-structured-data-smart-actions-alternative-approach-ali-afshar-cdwte?trk=feed_main-feed-card_feed-article-content">
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    <dc:creator>amy</dc:creator><description><![CDATA[Ali afshar]]></description>
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<item rdf:about="https://github.com/google/adk-samples/tree/main/python/agents/gemini-fullstack">
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<item rdf:about="https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference">
    <title>Generate content with the Gemini API in Vertex AI  |  Generative AI on Vertex AI  |  Google Cloud</title>
    <dc:date>2025-06-12T09:38:38+00:00</dc:date>
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<item rdf:about="https://cloud.google.com/bigquery/docs/data-canvas">
    <title>Analyze with BigQuery data canvas  |  Google Cloud</title>
    <dc:date>2025-06-10T10:39:27+00:00</dc:date>
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<dc:identifier>https://pinboard.in/u:amy/b:bf4d9b973976/</dc:identifier>
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<item rdf:about="https://cloud.google.com/blog/products/data-analytics/exploring-new-bigquery-data-canvas-ai-assistant-features">
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    <dc:date>2025-06-10T10:38:01+00:00</dc:date>
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    <dc:creator>amy</dc:creator><dc:subject>google bigquery big_data</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:5621f71a8366/</dc:identifier>
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<item rdf:about="https://www.theverge.com/news/681762/google-gemini-scheduled-actions-planned-tasks">
    <title>Google Gemini can now handle scheduled tasks like an assistant</title>
    <dc:date>2025-06-10T03:15:40+00:00</dc:date>
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<item rdf:about="https://cloud.google.com/blog/products/ai-machine-learning/enhancing-vllm-for-distributed-inference-with-llm-d">
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    <dc:date>2025-05-21T14:29:49+00:00</dc:date>
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<dc:identifier>https://pinboard.in/u:amy/b:80ed1062fbf9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
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<item rdf:about="https://blog.google/technology/developers/gemini-code-assist-updates-google-io-2025/">
    <title>Gemini Code Assist: Updates from Google I/O 2025</title>
    <dc:date>2025-05-21T13:46:11+00:00</dc:date>
    <link>https://blog.google/technology/developers/gemini-code-assist-updates-google-io-2025/</link>
    <dc:creator>amy</dc:creator><description><![CDATA[Gemini Code Assist for individuals and for GitHub are now generally available and powered by Gemini 2.5.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:ea87106cfbd7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.theverge.com/news/670495/google-ai-ultra-plan-pricing-launch-io-2025">
    <title>Google reveals $250 per month ‘AI Ultra’ plan</title>
    <dc:date>2025-05-21T02:42:03+00:00</dc:date>
    <link>https://www.theverge.com/news/670495/google-ai-ultra-plan-pricing-launch-io-2025</link>
    <dc:creator>amy</dc:creator><description><![CDATA[A “VIP pass” to Google AI.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:403682bcd052/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
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</item>
<item rdf:about="https://www.wired.com/story/google-deepminds-ai-agent-dreams-up-algorithms-beyond-human-expertise/?utm_mailing=WIR_Daily_051525&amp;bxid=5c48db8cfc942d0477965f00&amp;cndid=16546997&amp;hasha=e8605e5d8d0f312f10844b8980373038&amp;hashc=c8722d00b579ef5fe678e67148af2c251bdd162b3b18a9802bd8134858e9fceb&amp;esrc=Wired_etl_load">
    <title>Google DeepMind’s AI Agent Dreams Up Algorithms Beyond Human Expertise | WIRED</title>
    <dc:date>2025-05-16T17:16:21+00:00</dc:date>
    <link>https://www.wired.com/story/google-deepminds-ai-agent-dreams-up-algorithms-beyond-human-expertise/?utm_mailing=WIR_Daily_051525&amp;bxid=5c48db8cfc942d0477965f00&amp;cndid=16546997&amp;hasha=e8605e5d8d0f312f10844b8980373038&amp;hashc=c8722d00b579ef5fe678e67148af2c251bdd162b3b18a9802bd8134858e9fceb&amp;esrc=Wired_etl_load</link>
    <dc:creator>amy</dc:creator><description><![CDATA[A new system that combines Gemini’s coding abilities with an evolutionary approach improves datacenter scheduling and chip design, and fine-tunes large language models.]]></description>
<dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:5733f67ae3dc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://gemini.google.com/app">
    <title>‎Gemini</title>
    <dc:date>2025-04-20T14:06:41+00:00</dc:date>
    <link>https://gemini.google.com/app</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:6f60ec734dd5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://cloud.google.com/blog/products/containers-kubernetes/how-gke-powers-ai-innovation">
    <title>How GKE powers AI innovation | Google Cloud Blog</title>
    <dc:date>2025-04-19T14:11:20+00:00</dc:date>
    <link>https://cloud.google.com/blog/products/containers-kubernetes/how-gke-powers-ai-innovation</link>
    <dc:creator>amy</dc:creator><description><![CDATA[* Cluster Director for GKE, now generally available, lets you deploy and manage large clusters of accelerated VMs with compute, storage, and networking — all operating as a single unit.

* GKE Inference Quickstart, now in public preview, which simplifies the selection of infrastructure and deployment of AI models, while delivering benchmarked performance characteristics.

* GKE Inference Gateway, now in public preview, provides intelligent routing and load balancing for AI inference on GKE.

* A new container-optimized compute platform is rolling out on GKE Autopilot today, and in Q3, Autopilot’s compute platform will be made available to standard GKE clusters.

* Gemini Cloud Assist Investigations, now in private preview, helps with GKE troubleshooting, decreasing the time it takes to understand the root cause and resolve issues.

* With a built-in partnership with Anyscale, RayTurbo on GKE will launch later this year to deliver superior GPU/TPU performance, rapid cluster startup, and robust autoscaling.]]></description>
<dc:subject>google gcp GKE k8s kubernetes</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:3d0a8b0a3e1e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:gcp"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:GKE"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:k8s"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:kubernetes"/>
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</item>
<item rdf:about="https://codeassist.google/">
    <title>Gemini Code Assist | AI coding assistant</title>
    <dc:date>2025-04-15T13:34:07+00:00</dc:date>
    <link>https://codeassist.google/</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning google genAI</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:634f551589c1/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:genAI"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://ai.google.dev/gemini-api/docs/function-calling">
    <title>Function Calling with the Gemini API  |  Google AI for Developers</title>
    <dc:date>2025-04-05T14:11:25+00:00</dc:date>
    <link>https://ai.google.dev/gemini-api/docs/function-calling</link>
    <dc:creator>amy</dc:creator><dc:subject>machine_learning llms google</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:12be8dd383af/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:llms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://theintercept.com/2025/04/03/google-cbp-ai-border-surveillance-ibm-equitus/">
    <title>Google Is Helping the Trump Administration Deploy AI Along the Mexican Border</title>
    <dc:date>2025-04-03T18:50:38+00:00</dc:date>
    <link>https://theintercept.com/2025/04/03/google-cbp-ai-border-surveillance-ibm-equitus/</link>
    <dc:creator>amy</dc:creator><dc:subject>google politics</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:925b84b7075c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:politics"/>
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</item>
<item rdf:about="https://www.oreilly.com/library/view/machine-learning-production/9781098156008/">
    <title>Machine Learning Production Systems[Book]</title>
    <dc:date>2025-03-24T17:11:15+00:00</dc:date>
    <link>https://www.oreilly.com/library/view/machine-learning-production/9781098156008/</link>
    <dc:creator>amy</dc:creator><description><![CDATA[by Robert Crowe, Hannes Hapke, Emily Caveness, Di Zhu
Released October 2024
Publisher(s): O'Reilly Media, Inc.
ISBN: 9781098156015]]></description>
<dc:subject>machine_learning google gcp</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:712167609f46/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:gcp"/>
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</item>
<item rdf:about="https://gemini.google.com/canvas?hl=en">
    <title>‎Gemini - chat to supercharge your ideas</title>
    <dc:date>2025-03-22T16:34:52+00:00</dc:date>
    <link>https://gemini.google.com/canvas?hl=en</link>
    <dc:creator>amy</dc:creator><dc:subject>google machine_learning genAI</dc:subject>
<dc:identifier>https://pinboard.in/u:amy/b:7748c1e2f8a0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:google"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:machine_learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:amy/t:genAI"/>
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</item>
</rdf:RDF>