163 summarised stories about AWS, each linking back to the original source. Browse all topics →
Amazon Web Services 1 month ago 33 ● 3 sources
Anthropic announced Claude Fable 5.1’s availability on Amazon Bedrock and Claude Platform on AWS. Claude Fable 5.1 is a Covered Model with data retention for up to 30 days and requires AWS’s aws_review mode for invocation. Customers can also opt into Enterprise Frontier Safeguards, including zero data retention until December 31, 2026, changing how prompts/outputs are stored and reviewed.
Amazon Web Services 1 month ago 29
Atos ran an AWS AI League event to upskill 400 engineers in agentic AI by moving from theory to building multi-agent systems. The program ran over 3 days and covered tasks scored on performance and efficiency. The engineers left with hands-on capability using Amazon Bedrock, Bedrock AgentCore, AWS Lambda, Kiro, and Amazon SageMaker, and internal champions emerged for client delivery.
Amazon Web Services 1 month ago 15
Boomi introduced Boomi Scribe, an AI agent on AWS that automatically generates and keeps up-to-date documentation for Boomi integration workflow processes as they change. It uses Amazon Bedrock with Claude Haiku 4.5 and can compare DAG versions to highlight component differences, with one example workflow shown at Version 3. As a result, developers get live documentation plus change insights stored in Amazon S3, reducing manual documentation work and helping maintain audit-ready coverage.
The New Stack 1 month ago 25
Vibe-coded internal tools are creating a new form of shadow IT that bypasses OAuth logs by deploying infrastructure directly into cloud accounts. The risk described peaks when a misconfigured app runs for 6 weeks before CSPM flags a public endpoint tied to an over-permissioned IAM role. Webflow argues security must shift from detection-focused playbooks toward an enforced baseline (platform and process controls) plus review and behavioral telemetry before CSPM findings.
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16 October 2026
AI’s center of gravity this week moved toward something less glamorous than headlines about “smarter” models: scaling the stuff models actually learn from. AI4Bharat and NVIDIA released Nemotron-pretraining-Indic-v1, backed by an open, GPU-accelerated synthetic data generation pipeline for 22 Indian languages. The corpus is massive—about 2.8 trillion tokens—split across 2,601.0 billion native-script tokens and 224.6 billion romanized tokens. The practical pitch is even sharper: builders can reuse not just the data, but the full prompt/quality/repair recipe, then continue-pretraining to push results on Nemotron 3.5 Super VL, with the promise that an Indic continued-pretraining stage helps benchmarks.
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