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How Google Uses Embedding

18 engineering articles about Embedding from Google's engineering team

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Intermediate
The article provides an in-depth exploration of the EmbeddingGemma architecture, detailing its origins, embedding generation process, and the comprehensive training methodology.
Henrique Schechter Vera, Juyeong Ji, Sahil Dua
7 min read
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Beginner
The article discusses the recent enhancements to the Gemini Batch API, which now includes support for the Gemini Embedding model and compatibility with the OpenAI SDK.
Lucia Loher, Patrick Löber
2 min read
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Intermediate
This article discusses the integration of Google's EmbeddingGemma model with Google Cloud's Dataflow to create a scalable embedding pipeline for AI applications.
Danny McCormick, Ian Ballantyne, Olivier Lacombe
5 min read
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Intermediate
EmbeddingGemma is an innovative open embedding model designed for on-device AI applications, featuring 308 million parameters for efficient performance.
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Intermediate
The article discusses the Gemini Embedding text model and its applications in various industries, highlighting its effectiveness in enhancing AI applications through context engineering and retriev...
Vishal Dharmadhikari, Janie Zhang
4 min read
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Intermediate
The article announces the general availability of the Gemini Embedding text model, gemini-embedding-001, in the Gemini API and Vertex AI.
Min Choi, Janie Zhang
3 min read
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Intermediate
The article discusses the latest updates to the Gemini API, highlighting new models and functionalities that enhance developers' ability to create applications using generative AI.
Shrestha Basu Mallick, Logan Kilpatrick, Alisa Fortin, Ivan Solovyev
7 min read
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Advanced
The article introduces Keras Recommenders, a new library designed to simplify the creation of state-of-the-art recommendation systems using Keras with JAX, TensorFlow, or PyTorch.
Yufeng Guo, Monica Song
3 min read
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Intermediate
The article discusses the new features and improvements in Gemma 3, highlighting its vision-language capabilities, architectural changes for memory efficiency, and enhanced multilingual support.
Ju-yeong Ji, Ravin Kumar
9 min read
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Beginner
The article discusses the introduction of the Gemini Embedding text model (gemini-embedding-exp-03-07) available through the Gemini API.
Logan Kilpatrick, Zach Gleicher, Parashar Shah
3 min read
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Advanced
The article discusses the Vertex AI RAG Engine, a tool designed to help developers build grounded generative AI applications by addressing challenges like hallucinations and outdated knowledge.
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Intermediate
The article discusses the use of multimodal embeddings to enhance visual search capabilities, particularly for artists and enterprise-scale document search.
Anthony Tripaldi
10 min read
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Intermediate
The article discusses the PaliGemma architecture, a lightweight open vision-language model (VLM) inspired by PaLI-3.
Ju-yeong Ji, Ravin Kumar
6 min read
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Advanced
The article explores the RecurrentGemma architecture, a hybrid model that combines gated linear recurrences with local sliding window attention, enhancing performance for long context prompts.
Ju-yeong Ji, Ravin Kumar
6 min read
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Intermediate
The article discusses the release of Gemma 2, a new suite of open models that sets a new standard for performance and accessibility in conversational AI.
Ju-yeong Ji, Ravin Kumar
5 min read
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Intermediate
The article provides an overview of the Gemma model family architectures, detailing its lightweight, state-of-the-art open models derived from Gemini research.
Ju-yeong Ji, Ravin Kumar
9 min read
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Advanced
The article introduces the AI Edge Torch Generative API, designed to enable developers to create high-performance LLMs in PyTorch for deployment on edge devices using the TensorFlow Lite runtime.
Cormac Brick, Haoliang Zhang
10 min read
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Intermediate
The article discusses the latest updates from Coral, including a partnership with balena, new open-source tools, and enhancements to their ML software stack.

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