Tag: vector index
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Cloud Blog: From query to cart: Inside Target’s search bar overhaul with AlloyDB AI
Source URL: https://cloud.google.com/blog/topics/retail/from-query-to-cart-inside-targets-search-bar-overhaul-with-alloydb-ai/ Source: Cloud Blog Title: From query to cart: Inside Target’s search bar overhaul with AlloyDB AI Feedly Summary: Editor’s note: Target set out to modernize its digital search experience to better match guest expectations and support more intuitive discovery across millions of products. To meet that challenge, they rebuilt their platform with…
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Cloud Blog: Redefining enterprise data with agents and AI-native foundations
Source URL: https://cloud.google.com/blog/products/data-analytics/new-agents-and-ai-foundations-for-data-teams/ Source: Cloud Blog Title: Redefining enterprise data with agents and AI-native foundations Feedly Summary: The world is not just changing; it’s being re-engineered in real-time by data and AI. The way we interact with data is undergoing a fundamental transformation, moving beyond human-led analysis to a collaborative partnership with intelligent agents. This…
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Cloud Blog: How to integrate your Cloud SQL for MySQL database with Vertex AI & vector search
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/integrate-your-cloud-sql-with-vertex-ai-and-vector-search/ Source: Cloud Blog Title: How to integrate your Cloud SQL for MySQL database with Vertex AI & vector search Feedly Summary: Search is a critical component of many modern applications – whether searching for products in an online storefront, finding solutions to your customers’ support cases, or building the perfect playlist. But…
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AWS News Blog: Introducing Amazon S3 Vectors: First cloud storage with native vector support at scale (preview)
Source URL: https://aws.amazon.com/blogs/aws/introducing-amazon-s3-vectors-first-cloud-storage-with-native-vector-support-at-scale/ Source: AWS News Blog Title: Introducing Amazon S3 Vectors: First cloud storage with native vector support at scale (preview) Feedly Summary: Amazon S3 Vectors is a new cloud object store that provides native support for storing and querying vectors at massive scale, offering up to 90% cost reduction compared to conventional approaches…
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Cloud Blog: A deep dive into AlloyDB’s vector search enhancements
Source URL: https://cloud.google.com/blog/products/databases/alloydb-ais-scann-index-improves-search-on-all-kinds-of-data/ Source: Cloud Blog Title: A deep dive into AlloyDB’s vector search enhancements Feedly Summary: If you’re building a generative AI application or an AI agent, there’s a high likelihood you’ll need to perform simultaneous searches on structured and unstructured data. For example, the prompt “Show me all pictures of sunsets I took…
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Cloud Blog: Announcing open-source enhancements to LangChain PostgreSQL
Source URL: https://cloud.google.com/blog/products/ai-machine-learning/open-source-enhancements-to-langchain-postgresql/ Source: Cloud Blog Title: Announcing open-source enhancements to LangChain PostgreSQL Feedly Summary: At Google Cloud Next ‘25, we announced upgrades to the core LangChain Postgres package and became a major contributor to the library. These improvements underscore our vision that every application developer is a gen AI developer – one that is…
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Cloud Blog: AlloyDB AI drives innovation for application developers
Source URL: https://cloud.google.com/blog/products/databases/alloydb-ai-drives-innovation-from-the-database/ Source: Cloud Blog Title: AlloyDB AI drives innovation for application developers Feedly Summary: The transformative power of AI and intelligent agents is driving profound changes, where software can understand natural language questions and commands — and even autonomously act on our behalf. At the heart of this revolution is the “AI-ready” enterprise…
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Hacker News: Sharding Pgvector
Source URL: https://pgdog.dev/blog/sharding-pgvector Source: Hacker News Title: Sharding Pgvector Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the implementation of a sharding strategy for handling vector indices in the pgvector database, focusing specifically on large-scale embeddings. It highlights the challenges of scaling vector searches and presents an approach using two indexing…