InfoQ Homepage Search Content on InfoQ
-
Anthropic Introduces Web Search Functionality for Claude Models
Anthropic has announced the addition of web search capabilities to its Claude models, available via the Anthropic API. This update enables Claude to access current information from the web, allowing developers to create applications and AI agents that provide up-to-date insights.
-
Google Enhances AlloyDB Vector Search with Inline Filtering and Enterprise Observability
Google enhanced its AlloyDB service with inline filtering and enterprise observability for vector search. This fully-managed PostgreSQL-compatible database now allows direct filtering during queries, offering improved speed and efficiency. Enhanced monitoring features provide deep insights, addressing scaling vector search operations challenges.
-
Techniques and Trends in AI-Powered Search by Faye Zhang at QCon SF
At QCon SF 2024, Faye Zhang gave a talk titled Search: from Linear to Multiverse, covering three trends and techniques in AI-powered search: multi-modal interaction, personalization, and simulation with AI agents.
-
Native Vector Support in Azure SQL Database in Public Preview
Azure SQL Database now supports native vector storage and processing, streamlining AI development by integrating vector search with SQL queries. This update simplifies database management, enhances data analysis, and boosts performance by eliminating data movement. Ideal for diverse applications, it empowers sectors like e-commerce and healthcare with advanced, context-aware functionalities.
-
Optimizing Uber's Search Infrastructure: Upgrading to Apache Lucene 9.5
Uber Engineering recently announced an upgrade to their search infrastructure, transitioning from Apache Lucene 8.0 to version 9.5. This upgrade improves Uber's search capabilities, performance and efficiency across their various services.
-
Grab Employs LLMs for Conversational Data Discovery with GPT-4, Glean and Slack
Grab responded to the challenges of finding valuable datasets among 200k+ tables by enhancing Hubble, the data discovery tool, with new capabilities leveraging GenAI technologies. The company reduced the data discovery process by incorporating LLMs to generate dataset documentation and created a Slack bot to bring effective data discovery to data consumers.
-
Generative AI Capabilities for Logic Apps Standard with Azure OpenAI and AI Search Connectors
Microsoft has announced that the Azure OpenAI and Azure AI Search connectors for Logic Apps Standard are now generally available, following an earlier public preview. These connectors are fully integrated into Azure Integration Services, providing developers with powerful tools to enhance application functionality with advanced AI capabilities.
-
Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently
Netflix engineers recently published how they use Elasticsearch Percolate Queries to "reverse search" entities in a connected graph. Reverse search means that instead of searching for documents that match a query, they search for queries that match a document, powering dynamic subscription scenarios where there is no direct association between the subscriber and the subscribed entities.
-
Google Expands Vertex AI Search and Conversation Capabilities
At its Google Cloud Next conference, Google officially introduced new capabilities for its enterprise AI platform, Vertex AI, which aim to enable more advanced user workflows, among other things.
-
Vector Engine for Amazon Opensearch Serverless Now in Preview
AWS announced the preview release of vector storage and search capability within Amazon OpenSearch Serverless. The capability is intended to support machine learning augmented search experiences and generative AI applications.
-
Microsoft Introduces the Public Preview of Vector Search Feature in Azure Cognitive Search
At its annual Inspire conference, Microsoft recently announced the public preview of Vector search in Azure Cognitive Search, a capability for building applications powered by large language models. It is a new capability for indexing, storing, and retrieving vector embeddings from a search index.
-
AWS OpenSearch Serverless Now Generally Available
Amazon recently announced the general availability of OpenSearch Serverless, a new serverless option for Amazon OpenSearch service, which automatically provisions and scales the underlying resources for faster data ingestion and query responses.
-
Pinecone 2.0 Aims to Bring Vector Similarity Search to Production
Pinecone recently introduced version 2.0 of its vector similarity search solution aiming to make it easier for companies to build recommendation systems, image search, and similar applications. InfoQ has taken the chance to speak with Edo Liberty, founder and CEO of Pinecone.
-
Better SEO with Structured Data and Rich Snippets
Martin Splitt, search developer advocate for Google, recently explained at the Chrome Developer Summit 2020 how to use structured data to make a website eligible for rich results in Google Search. Rich results support semantic searches, stand out from ordinary search results, and may increase the click-through rate.
-
Space-Efficient Full-Text Search with Rust and WebAssembly
Matthias Endler, backend engineer for Trivago, published a client-side full-text search engine designed for space efficiency by leveraging Bloom filters. Tinysearch is written in Rust, transpiled to WebAssembly, and used in the browser. Tinysearch claims sizes between 50 and 100KB and can only index full words.