Experimental News Clipping Site

Tag: vector database

  • Cloud Blog: How SIGNAL IDUNA supercharges customer service with gen AI

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/how-signal-iduna-supercharges-customer-service-with-gen-ai/ Source: Cloud Blog Title: How SIGNAL IDUNA supercharges customer service with gen AI Feedly Summary: Today’s insurance customers expect more: simple digital services, instant access to service representatives when they want to discuss personal matters, and quick feedback on submitted invoices. Meeting these demands has become increasingly difficult for insurers due to…

  • Cloud Blog: Unico builds cutting-edge IDTech with Spanner Vector Search

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/databases/unico-builds-cutting-edge-idtech-with-spanner-vector-search/ Source: Cloud Blog Title: Unico builds cutting-edge IDTech with Spanner Vector Search Feedly Summary: Unico is a leading biometric verification and authentication company addressing the global challenges of identity management and fraud prevention.  With nearly two decades of experience in the Brazilian market, Unico has become a reliable supplier to over 800…

  • Hacker News: DeepSearcher: A Local open-source Deep Research

    —

    by

    Kurt Seifried
    in

    Source URL: https://milvus.io/blog/introduce-deepsearcher-a-local-open-source-deep-research.md Source: Hacker News Title: DeepSearcher: A Local open-source Deep Research Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The provided text outlines the development and functionality of DeepSearcher, an open-source research agent that automates query decomposition, data retrieval, and synthesis of information into detailed reports. It showcases innovations in AI-driven research…

  • Cloud Blog: Enhancing AlloyDB vector search with inline filtering and enterprise observability

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/databases/enhancing-alloydb-vector-search-with-inline-filtering-and-enterprise-observability/ Source: Cloud Blog Title: Enhancing AlloyDB vector search with inline filtering and enterprise observability Feedly Summary: Many specialized vector databases today require you to create complex pipelines and applications in order to get the data you need. AlloyDB for PostgreSQL offers Google Research’s, state-of-the-art vector search index, ScaNN, enabling you to optimize…

  • Hacker News: The Best Way to Use Text Embeddings Portably Is with Parquet and Polars

    —

    by

    Kurt Seifried
    in

    Source URL: https://minimaxir.com/2025/02/embeddings-parquet/ Source: Hacker News Title: The Best Way to Use Text Embeddings Portably Is with Parquet and Polars Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text provides a detailed overview of generating and utilizing text embeddings from large language models, specifically applied to Magic: The Gathering cards. It emphasizes the…

  • Cloud Blog: Unlock Inference-as-a-Service with Cloud Run and Vertex AI

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/improve-your-gen-ai-app-velocity-with-inference-as-a-service/ Source: Cloud Blog Title: Unlock Inference-as-a-Service with Cloud Run and Vertex AI Feedly Summary: It’s no secret that large language models (LLMs) and generative AI have become a key part of the application landscape. But most foundational LLMs are consumed as a service, meaning they’re hosted and served by a third party…

  • Chip Huyen: Common pitfalls when building generative AI applications

    —

    by

    Kurt Seifried
    in

    Source URL: https://huyenchip.com//2025/01/16/ai-engineering-pitfalls.html Source: Chip Huyen Title: Common pitfalls when building generative AI applications Feedly Summary: As we’re still in the early days of building applications with foundation models, it’s normal to make mistakes. This is a quick note with examples of some of the most common pitfalls that I’ve seen, both from public case…

  • Cloud Blog: Unlock multimodal search at scale: Combine text & image power with Vertex AI

    —

    by

    Kurt Seifried
    in

    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.…

  • Cloud Blog: Introducing Vertex AI RAG Engine: Scale your Vertex AI RAG pipeline with confidence

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/introducing-vertex-ai-rag-engine/ Source: Cloud Blog Title: Introducing Vertex AI RAG Engine: Scale your Vertex AI RAG pipeline with confidence Feedly Summary: Closing the gap between impressive model demos and real-world performance is crucial for successfully deploying generative AI for enterprise. Despite the incredible capabilities of generative AI for enterprise, this perceived gap may be…

  • Cloud Blog: How retailers are accelerating AI into production with NVIDIA and Google Cloud

    —

    by

    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/topics/retail/how-retailers-are-accelerating-ai-with-nvidia-and-google-cloud/ Source: Cloud Blog Title: How retailers are accelerating AI into production with NVIDIA and Google Cloud Feedly Summary: Retailers have always moved quickly to connect and match the latest merchandise with customers’ needs. And the same way they carefully design every inch of their stores, the time and thought that goes into…