Tag: embedding model
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Hacker News: 400x faster embeddings models using static embeddings
Source URL: https://huggingface.co/blog/static-embeddings Source: Hacker News Title: 400x faster embeddings models using static embeddings Feedly Summary: Comments AI Summary and Description: Yes **Summary:** This blog post discusses a new method to train static embedding models significantly faster than existing state-of-the-art models. These models are suited for various applications, including on-device and in-browser execution, and edge…
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Cloud Blog: Unlock multimodal search at scale: Combine text & image power with Vertex AI
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/combine-text-image-power-with-vertex-ai/ Source: Cloud Blog Title: Unlock multimodal search at scale: Combine text & image power with Vertex AI Feedly Summary: The way users search is evolving. When searching for a product, users might type in natural-sounding language or search with images. In return, they want tailored results that are specific to their query.…
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Hacker News: voyage-code-3
Source URL: https://blog.voyageai.com/2024/12/04/voyage-code-3/ Source: Hacker News Title: voyage-code-3 Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents voyage-code-3, a new embedding model optimized for code retrieval that significantly outperforms existing models in both performance and cost-efficiency. The introduction of Matryoshka learning and advanced quantization techniques allows for reduced storage requirements without compromising…
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Simon Willison’s Weblog: Open WebUI
Source URL: https://simonwillison.net/2024/Dec/27/open-webui/#atom-everything Source: Simon Willison’s Weblog Title: Open WebUI Feedly Summary: Open WebUI I tried out this open source (MIT licensed, JavaScript and Python) localhost UI for accessing LLMs today for the first time. It’s very nicely done. I ran it with uvx like this: uvx –python 3.11 open-webui serve On first launch it…
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Cloud Blog: Optimizing RAG retrieval: Test, tune, succeed
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/optimizing-rag-retrieval/ Source: Cloud Blog Title: Optimizing RAG retrieval: Test, tune, succeed Feedly Summary: Retrieval-augmented generation (RAG) supercharges large language models (LLMs) by connecting them to real-time, proprietary, and specialized data. This helps LLMs deliver more accurate, relevant, and contextually aware responses, minimizing hallucinations and building trust in AI applications. But RAG can be…
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Cloud Blog: Tailor your search engine with AI-powered hybrid search in Spanner
Source URL: https://cloud.google.com/blog/topics/developers-practitioners/hybrid-search-in-spanner-combine-full-text-and-vector-search/ Source: Cloud Blog Title: Tailor your search engine with AI-powered hybrid search in Spanner Feedly Summary: Search is at the heart of how we interact with the digital ecosystem, from online shopping to finding critical information. Enter generative AI, and user expectations are higher than ever. For applications to meet diverse user…
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Cloud Blog: How Vertex AI’s vector search helps unlock high-performance gen AI apps
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/build-fast-and-scalable-ai-applications-with-vertex-ai/ Source: Cloud Blog Title: How Vertex AI’s vector search helps unlock high-performance gen AI apps Feedly Summary: Think about your favorite apps – the ones that deliver instant results from massive amounts of data. They’re likely powered by vector search, the same technology that fuels generative AI. Vector search is crucial for…
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Hacker News: Roaming RAG – Make the Model Find the Answers
Source URL: http://arcturus-labs.com/blog/2024/11/21/roaming-rag–make-_the-model_-find-the-answers/ Source: Hacker News Title: Roaming RAG – Make the Model Find the Answers Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text presents a novel approach called “Roaming RAG,” which simplifies the retrieval-augmented generation (RAG) model by allowing a large language model (LLM) to directly navigate well-structured documents without the…
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Cloud Blog: Build agentic RAG on Google Cloud databases with LlamaIndex
Source URL: https://cloud.google.com/blog/products/databases/llamaindex-integrates-with-alloydb-and-cloud-sql-for-postgresql/ Source: Cloud Blog Title: Build agentic RAG on Google Cloud databases with LlamaIndex Feedly Summary: AI agents are revolutionizing the landscape of gen AI application development. Retrieval augmented generation (RAG) has significantly enhanced the capabilities of large language models (LLMs), enabling them to access and leverage external data sources such as databases.…
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Hacker News: Cascading retrieval: Unifying dense and sparse vector embeddings with reranking
Source URL: https://www.pinecone.io/blog/cascading-retrieval/ Source: Hacker News Title: Cascading retrieval: Unifying dense and sparse vector embeddings with reranking Feedly Summary: Comments AI Summary and Description: Yes Summary: Pinecone has introduced new cascading retrieval capabilities for AI search applications, enhancing the integration of dense and sparse retrieval systems. These advancements, which reportedly improve performance by up to…