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Tag: embeddings

  • Cloud Blog: How to enable real time semantic search and RAG applications with Dataflow ML

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/topics/developers-practitioners/create-and-retrieve-embeddings-with-a-few-lines-of-dataflow-ml-code/ Source: Cloud Blog Title: How to enable real time semantic search and RAG applications with Dataflow ML Feedly Summary: Embeddings are a cornerstone of modern semantic search and Retrieval Augmented Generation (RAG) applications. In short, they enable applications to understand and interact with information on a deeper, conceptual level. In this post,…

  • Cloud Blog: Tools Make an Agent: From Zero to Assistant with ADK

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/topics/developers-practitioners/tools-make-an-agent-from-zero-to-assistant-with-adk/ Source: Cloud Blog Title: Tools Make an Agent: From Zero to Assistant with ADK Feedly Summary: Imagine that you’re a project manager at QuantumRoast, a global coffee machine company. You help your teammates navigate a sea of engineering roadmaps, sudden strategy pivots (we’re doing matcha now!), and incoming tickets from customers— everything…

  • Cloud Blog: Introducing BigQuery ObjectRef: Supercharge your multimodal data and AI processing

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/data-analytics/new-objectref-data-type-brings-unstructured-data-into-bigquery/ Source: Cloud Blog Title: Introducing BigQuery ObjectRef: Supercharge your multimodal data and AI processing Feedly Summary: Traditional data warehouses simply can’t keep up with today’s analytics workloads. That’s because today, most data that’s generated is both unstructured and multimodal (documents, audio files, images, and videos). With the complexity of cleaning and transforming…

  • Tomasz Tunguz: The Multimodal Lake House : Partnering with Lance

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    Kurt Seifried
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    Source URL: https://www.tomtunguz.com/partnering-with-lance/ Source: Tomasz Tunguz Title: The Multimodal Lake House : Partnering with Lance Feedly Summary: Remember when you took a family photo & Ghibli-styled it? Or that vibe coding session, when you pasted a screenshot of the browser so the AI can help you debug some Javascript? Today, we expects AI to be…

  • Simon Willison’s Weblog: Qwen3 Embedding

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Jun/8/qwen3-embedding/#atom-everything Source: Simon Willison’s Weblog Title: Qwen3 Embedding Feedly Summary: Qwen3 Embedding New family of embedding models from Qwen, in three sizes: 0.6B, 4B, 8B – and two categories: Text Embedding and Text Reranking. The full collection can be browsed on Hugging Face. The smallest available model is the 0.6B Q8 one, which…

  • Cloud Blog: Accelerate your gen AI: Deploy Llama4 & DeepSeek on AI Hypercomputer with new recipes

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/deploying-llama4-and-deepseek-on-ai-hypercomputer/ Source: Cloud Blog Title: Accelerate your gen AI: Deploy Llama4 & DeepSeek on AI Hypercomputer with new recipes Feedly Summary: The pace of innovation in open-source AI is breathtaking, with models like Meta’s Llama4 and DeepSeek AI’s DeepSeek. However, deploying and optimizing large, powerful models can be  complex and resource-intensive. Developers and…

  • Cloud Blog: Google is a Leader in the 2025 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms report

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/gartner-2025-magic-quadrant-for-data-science-and-ml-platforms/ Source: Cloud Blog Title: Google is a Leader in the 2025 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms report Feedly Summary: Today, we are excited to announce that Gartner® has named Google as a Leader in the 2025 Magic Quadrant™ for Data Science and Machine Learning Platforms report (DSML).…

  • Simon Willison’s Weblog: Codestral Embed

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/May/28/codestral-embed/#atom-everything Source: Simon Willison’s Weblog Title: Codestral Embed Feedly Summary: Codestral Embed Brand new embedding model from Mistral, specifically trained for code. Mistral claim that: Codestral Embed significantly outperforms leading code embedders in the market today: Voyage Code 3, Cohere Embed v4.0 and OpenAI’s large embedding model. The model is designed to work…