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ExternalAI
AWS Machine Learning Blog

Automated agent evaluation with Amazon Bedrock AgentCore and GitHub Actions

Wire Amazon Bedrock AgentCore Evaluations into a GitHub Actions pipeline: deploy an AI agent and an OAuth-protected MCP server to AgentCore runtime, invoke the agent with test prompts, score the responses, and automatically block pull requests when agent behavior regresses.

Advanced (300)Amazon Bedrock AgentCoreTechnical How-to
AWS Machine Learning BlogRead original
ExternalAI
AWS Machine Learning Blog

Benchmarking small LLM inference on SageMaker AI: G7 vs G5 and G6

Benchmark two 30B Mixture-of-Experts models, Qwen3-Coder-30B and NVIDIA Nemotron-3-Nano-30B, across G5, G6, G6e, and G7 GPU instances on Amazon SageMaker AI. Compare throughput, latency, and cost-per-token, and see how G7's NVIDIA Blackwell GPUs deliver measurable price-performance gains for real-time LLM inference.

Advanced (300)Amazon EC2Amazon SageMaker AI
AWS Machine Learning BlogRead original
External
The Hacker News

Slim Spider Steals Crypto Custody Secrets From Brazilian Financial Institution

A previously undocumented financially motivated threat actor has been linked to attacks targeting Brazilian financial institutions since at least March 2026. Cybersecurity company CrowdStrike is tracking the Brazil-based activity cluster under the name Slim Spider. "The adversary demonstrates deep operational knowledge of Brazilian financial infrastructure, including the instant payment

The Hacker NewsRead original
ExternalAI
AWS Machine Learning Blog

How HPE Zerto built an agentic troubleshooting system with Amazon Bedrock

HPE Zerto built an agentic troubleshooting system powered by Amazon Bedrock that runs on-premises inside the customer environment. This post describes the multi-agent architecture, the on-premises deployment model built with Strands Agents, and the engineering challenges of grounding agents in live disaster recovery data.

Advanced (300)Amazon BedrockCustomer Solutions
AWS Machine Learning BlogRead original
ExternalAI
AWS Machine Learning Blog

How DiDi built intelligent contact center QA with Amazon Bedrock

DiDi built a transparent, self-owned contact center quality assurance (QA) system on Amazon Bedrock, replacing an opaque third-party tool. Intent verification accuracy rose from 38% to 86%, compliance scoring topped 90%, and Voice of Customer trend analysis dropped from hours to minutes across Spanish and Portuguese support.

Amazon BedrockCustomer Solutions
AWS Machine Learning BlogRead original

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