Saturday, 14 November 2026 Updated 2 hr ago 113 stories Sources RSS

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The attendee’s guide to the AWS re:Invent 2026 AI/ML track

AWS re:Invent 2026 includes more than 140 AI/ML track sessions. This attendee's guide helps you find the breakouts, chalk talks, workshops, and builders' sessions that fit your role and goals, spanning AI chips, models and inference…

The attendee’s guide to the AWS re:Invent 2026 AI/ML track

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Automating AWS Agent Registry updates with push-based architecture

This post shows how to keep the AWS Agent Registry current automatically. Using AWS CloudTrail, Amazon EventBridge, AWS Lambda, and AgentCore Identity, an event-driven pipeline detects MCP server changes and pushes updated tool metadata to…

Automating AWS Agent Registry updates with push-based architecture

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How DXC Technology built a multi-model AI substrate on Amazon Bedrock

DXC Technology runs mission-critical managed IT services for regulated organizations across 70 countries. Learn how DXC built DCX OASIS, its Human+AI operating model, on a governed multi-model substrate in Amazon Bedrock, separating a…

How DXC Technology built a multi-model AI substrate on Amazon Bedrock

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Accelerating generative AI delivery with reusable assets

Every generative AI team keeps rebuilding the same components: RAG pipelines, document processors, and agent scaffolding. This post shows how to access a curated catalog of 23 production-ready, open source reusable assets from the AWS…

Accelerating generative AI delivery with reusable assets

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Introducing Kimi K3.1 Pro on Amazon Bedrock

Kimi K3.1 Pro from Moonshot AI is now available on Amazon Bedrock. Learn how to get started through the OpenAI-compatible Chat Completions, Responses, and Converse APIs, optimize inference with explicit prompt caching…

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Amazon Bedrock tokenomics data lake

Running Amazon Bedrock across many accounts shows you the bill but not what happened inside each call. This post builds a centralized observability data lake that aggregates Bedrock invocation logs from every linked…

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How skills and agents work in AWS Quick

Repeatable tasks like status updates, release notes, and ticket creation can be encoded in AWS Quick through agents and skills. This post covers how agents, skills, and your data fit together in AWS Quick, how to build…

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Introducing Claude Fable 5.2 on AWS

Claude Fable 5.2 and Claude Mythos 5.2 are now available on Amazon Bedrock and Claude Platform on AWS. Learn what's new in both models, why Fable 5.2 matters for your technical workloads, and how to get started building with it on Amazon…

Introducing Claude Fable 5.2 on AWS

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How CrossnoKaye grounds physical AI with Amazon Bedrock AgentCore

CrossnoKaye brought physical AI to heavy industry with Amazon Bedrock AgentCore. Its ATLAS platform and AURA agentic system ground AI reasoning in live plant data and run verifiable Python in isolated AgentCore sandboxes, giving plant…

How CrossnoKaye grounds physical AI with Amazon Bedrock AgentCore

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Professional work deserves professional tools. Meet AWS Quick.

Introducing AWS Quick, formerly Amazon Quick, and the debut of our first brand campaign celebrating teams who keep business moving. AWS Quick is the AI workspace built only for work, where teams use AI agents to research, analyze, and act…

Professional work deserves professional tools. Meet AWS Quick.

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Taxonomy of agentic primitives in AWS Quick

As we built Amazon Quick, its agents grew from answering questions to taking actions, and the same primitives kept getting rebuilt under different names. This post shares the taxonomy we converged on — triggers, agents, capabilities, and…

Taxonomy of agentic primitives in AWS Quick

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Serverless MCP server for AI agent data lake access on Amazon ECS Fargate

Learn how to build a serverless Model Context Protocol (MCP) server on Amazon ECS with AWS Fargate that gives AI agents secure, metadata-driven access to an enterprise data lake. Exposing a new dataset requires only a JSON file, with no…

Serverless MCP server for AI agent data lake access on Amazon ECS Fargate
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