Serve live, governed data in AI-built apps with Amazon Quick
TutoSartup excerpt from this article:
Your governed Amazon Quick Sight datasets, the SPICE and Direct Query tables that hold your business metrics, couldn’t be queried live from an app... Any dataset numbers an app showed were baked in when the agent built it... In this post, we introduce Live Data in Apps, which AI-built Amazon Quick apps can use to query governed Quick Sight datasets in real time instead of relying on static, bui...
Your governed Amazon Quick Sight datasets, the SPICE and Direct Query tables that hold your business metrics, couldn’t be queried live from an app... Any dataset numbers an app showed were baked in when the agent built it... In this post, we introduce Live Data in Apps, which AI-built Amazon Quick apps can use to query governed Quick Sight datasets in real time instead of relying on static, bui...
Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors
TutoSartup excerpt from this article:
In my previous post: Building persistent memory for multi-agent AI systems with Amazon S3 Vectors, we explored why memory engineering is the foundational discipline for production multi-agent systems... We showed how Amazon S3 Vectors, a capability of Amazon Simple Storage Service (Amazon S3), meets the architectural requirements for agent memory: semantic retrieval, rich metadata, strong consiste...
In my previous post: Building persistent memory for multi-agent AI systems with Amazon S3 Vectors, we explored why memory engineering is the foundational discipline for production multi-agent systems... We showed how Amazon S3 Vectors, a capability of Amazon Simple Storage Service (Amazon S3), meets the architectural requirements for agent memory: semantic retrieval, rich metadata, strong consiste...
Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS
TutoSartup excerpt from this article:
In this post, we share how Amazon Payments applied AI-based personalization to a product acquisition funnel, using a multi-objective contextual multi-armed bandit (MAB) on Amazon SageMaker AI... We cover the intuition behind bandits, our extension to optimize an entire conversion funnel, and the AWS architecture behind the solution... Growing role of multi-armed bandits in the generative AI era A...
In this post, we share how Amazon Payments applied AI-based personalization to a product acquisition funnel, using a multi-objective contextual multi-armed bandit (MAB) on Amazon SageMaker AI... We cover the intuition behind bandits, our extension to optimize an entire conversion funnel, and the AWS architecture behind the solution... Growing role of multi-armed bandits in the generative AI era A...
Accelerating airline retailing innovation: how Datalex modernized with AWS Experience-Based Acceleration and agentic AI
TutoSartup excerpt from this article:
Stream 1: Microservice prototyping extracted a slice of the Reservation component from the existing n-tier architecture and refactored it into a modern Spring Boot microservice running on Java 21... Stream 2: DevSecOps pipeline built an end-to-end continuous integration and continuous delivery (CI/CD) pipeline using AWS services including Amazon Elastic Container Service (Amazon ECS), Amazon E...
Stream 1: Microservice prototyping extracted a slice of the Reservation component from the existing n-tier architecture and refactored it into a modern Spring Boot microservice running on Java 21... Stream 2: DevSecOps pipeline built an end-to-end continuous integration and continuous delivery (CI/CD) pipeline using AWS services including Amazon Elastic Container Service (Amazon ECS), Amazon E...
Major Asset Classes | September 2026 | Performance Review
TutoSartup excerpt from this article:
The big winner was commodities with a strong 4...5% gain last month... The increase extends the winning streak for raw materials to a third straight monthly advance, as measured by the iShares S&P GSCI Commodity-Indexed Trust (GSG), an energy-heavy portfolio...2%, based on Vanguard Real Estate (VNQ), the ETF’s steepest monthly decline in nearly two years... The rout in the bond market beca...
The big winner was commodities with a strong 4...5% gain last month... The increase extends the winning streak for raw materials to a third straight monthly advance, as measured by the iShares S&P GSCI Commodity-Indexed Trust (GSG), an energy-heavy portfolio...2%, based on Vanguard Real Estate (VNQ), the ETF’s steepest monthly decline in nearly two years... The rout in the bond market beca...
Amazon S3 Tables now support all Apache Iceberg V3 data types
TutoSartup excerpt from this article:
You can create V3 tables or upgrade existing V2 tables to take advantage of V3 features like deletion vectors, row lineage, and new data types such as variant, nanosecond timestamps, unknown, geometry, and geography... It lets you manage petabyte-scale tables with features like schema evolution, hidden partitioning, and time travel queries, while keeping your data in open Parquet files in data la...
You can create V3 tables or upgrade existing V2 tables to take advantage of V3 features like deletion vectors, row lineage, and new data types such as variant, nanosecond timestamps, unknown, geometry, and geography... It lets you manage petabyte-scale tables with features like schema evolution, hidden partitioning, and time travel queries, while keeping your data in open Parquet files in data la...
Amazon S3 Vectors now supports metadata pre-filtering for higher recall on filtered searches
TutoSartup excerpt from this article:
Each vector carries up to 2 KB of filterable metadata, and a single query supports up to 100 filter constraints... Semantic search, retrieval-augmented generation (RAG), and agentic applications all need the same thing from a filtered query: a similarity search that covers the vectors matching the filter, and returns the closest of them... Higher recall means more of that material reaches the age...
Each vector carries up to 2 KB of filterable metadata, and a single query supports up to 100 filter constraints... Semantic search, retrieval-augmented generation (RAG), and agentic applications all need the same thing from a filtered query: a similarity search that covers the vectors matching the filter, and returns the closest of them... Higher recall means more of that material reaches the age...