On August 5, AWS made native vector search generally available in Amazon DynamoDB across all commercial regions and GovCloud, enabling single-digit-millisecond latency at 99%+ recall for up to 4,096 d…
AWS announced new services and updates in its weekly roundup for August 17, 2026, including Amazon EC2 application status checks, AWS IAM role manager, and the availability of OpenAI Daybreak on Amazo…
AWS launched native vector search for Amazon DynamoDB on August 5, 2026, with general availability, enabling developers to store vector embeddings and run approximate nearest neighbor queries directly…
A team demonstrated an AI agent orchestrating a complete migration of 1 TB of production data from Elasticsearch 7.10 to OpenSearch 3.x on Amazon OpenSearch Service in 33 minutes. The agent, using Kir…
Amazon OpenSearch Service has introduced purpose-built APIs for agentic memory, enabling AI agents to store and retrieve persistent, semantically searchable conversation data. The system, built on the…
A developer found that BM25's default length normalization parameter (b=0.75) systematically penalizes long RAG chunks, causing exact-answer chunks to rank below irrelevant headings. The analysis show…
OpenSearch Software Foundation executive director Bianca Lewis said at Open Source Summit India that OpenSearch, which began in 2021 as a fork of Elasticsearch, is now a completely independent project…
A Technical Architect and AWS Community Builder who teaches cloud topics at universities in Colombia passed the AWS Certified Generative AI Developer – Professional (AIP-C01) exam and shared the reaso…
A developer seeking advice on building a retrieval-augmented generation (RAG) system for government and internal organizational documents asks about optimal chunk sizes for BM25 and semantic search (c…
A pattern in RAG implementations shows that retrieval, not the language model, is the root cause of incorrect answers, according to a technical analysis. The article argues that semantic search using …
A new benchmark, ORCA-bench, shows that frontier language model agents achieve only 25.3% root cause analysis accuracy on Medium-difficulty oncall tasks and 10.0% on Hard tasks, with the best performa…
A developer who built CourtGPT.ai to serve 6.7M+ legal records shares 18 months of lessons on production RAG systems. Key findings include that hybrid search (BM25 + vector) achieves 92% recall at top…
PGSync Pro adds real-time semantic and hybrid search to PostgreSQL, re-embedding vectors only when meaning changes and keeping data within the user's infrastructure. The tool, built on the open-source…
Amazon Kendra is a managed enterprise search service that uses a proprietary ML model to index documents and return relevant snippets or generated answers. The service connects to data sources like S3…
Oracle's Siebel 26.6 introduces RAG-powered search using an OpenSearch vector pipeline to solve the problem of support reps re-solving the same ticket due to keyword search limitations, according to a…
OpenSearch 3.7, released in July 2026, delivers a 5.5x faster vector search at k=1000 and native Prometheus querying in OpenSearch Dashboards without requiring reindexing or data migration. The update…
OpenSearch is a common choice for vector search in production RAG systems, but tuning vector retrieval involves trade-offs between recall and latency. The article explains how Approximate Nearest Neig…
AWS engineers demonstrated troubleshooting agentic AI using OpenTelemetry and OpenSearch to gain insights into system performance and data before and during production.…
Attribute Knowledge RAG (AK-RAG) prevents large language models from inventing nonexistent fields by indexing governed attribute catalogs instead of documents, forcing field selection through retrieva…
Retrieval-augmented generation (RAG) pipelines are failing in production because most teams focus on the retrieval and generation layers while neglecting data quality, according to experts. Mayank Bho…