Fine-tune a search agent with multi-turn RL on Amazon SageMaker AI

TutoSartup excerpt from this article:
What you need is a training approach that optimizes the agent across the full multi-turn trajectory... It trains the agent to make good decisions across a full sequence of steps, bakes in your environment-specific behavior, and gives you control over output quality... It frames an agentic task as a sequence of decisions, uses multi-turn rollouts to generate training data, and optimizes the model ...

Total Return Forecasts: Major Asset Classes | 2 October 2026

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The long-run return forecast for the Global Market Index (GMI) continued to edge higher in September... Fueled by a decline in financial markets last month, GMI’s projected return increased for a fifth straight month... The expected return is calculated as the average of three models, defined below... Today’s revised GMI return forecast is 8...3%, up slightly from last month’s estimate but s...

Announcing AWS Well-Architected Agent, an AI-powered intelligence to optimize your cloud environment (preview)

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The agent evaluates your environment as an experienced cloud architect would... The agent automatically generates and prioritizes recommendations by impact and effort against those goals...AWS Well-Architected Agent in action To get started, create an agent profile to define the scope of what Well-Architected Agent can access and provide recommendations on, complete the IAM role setup to acc...

Serve live, governed data in AI-built apps with Amazon Quick

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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

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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

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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

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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...