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Agents & Automation

Amazon Bedrock AgentCore Adds Policy and Lambda Interceptors for Secure Agents

CurrentLens
Jun 2, 2026

AWS demonstrates layering deterministic Policy checks with Lambda interceptors in the Bedrock AgentCore gateway using a lakehouse data agent to enforce geography-based controls.

Agents & Automation

Amazon Bedrock AgentCore Accelerates Agent Development Process

CurrentLens
Apr 23, 2026

Amazon introduces new features in Bedrock AgentCore, enhancing agent development speed and efficiency.

Agents & Automation

AWS launches Spring AI SDK for Amazon Bedrock AgentCore

CurrentLens
Apr 17, 2026

AWS has released an open-source Spring AI AgentCore SDK that embeds Bedrock AgentCore capabilities into Spring AI and targets production-ready agent workflows.

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Science & Healthcare

Africa CDC and WHO launch $518M continental Ebola response plan

CurrentLens
Jun 6, 2026

A six-month 'One Response' plan targets the Bundibugyo Ebola outbreak with unified coordination, surveillance, clinical care and community engagement across affected countries.

Policy & Safety

HASC adds right-to-repair language to FY27 defense policy bill

CurrentLens
Jun 6, 2026

The House Armed Services Committee inserted right-to-repair provisions into its FY27 defense policy draft, aiming to ease barriers that limit troops' ability to fix equipment.

AI Creative

Startups Pull Users Off Phones With In-Person Games and DIY Cyberdecks

CurrentLens
Jun 6, 2026

TechCrunch highlights founders building physical social products: Board raised funding for in-person games, and cyberdeck DIYs are going viral.

Agents & Automation

MicroPython WASM Sandbox Enables Safer Datasette Plugin Execution

CurrentLens
Jun 6, 2026

Simon Willison published an alpha MicroPython-in-WASM sandbox (micropython-wasm) and a Datasette plugin (datasette-agent-micropython) to run plugin code with constrained access.

Models & Launches

DKPS method cuts model-evaluation queries using cached responses

CurrentLens
Jun 6, 2026

An arXiv paper introduces a DKPS-based approach that uses cached model outputs to predict benchmark scores while substantially reducing the number of queries.