Modal introduces Role-Based Access Control for all Team and Enterprise users, built on Environments to provide granular permissions for humans and AI agents.

This article details how to deploy a fully local voice conversation pipeline for the Reachy Mini robot, eliminating the need for cloud servers or API keys. It uses a cascaded approach combining VAD, STT, LLM, and TTS, with recommended defaults: llama.cpp with Gemma 4, Silero VAD, Parakeet-TDT 0.6B v3 STT, and Qwen3-TTS. Various LLM options are provided, including local MLX, Transformers, vLLM, or remote Responses API.

Daniel Stenberg describes the unprecedented pressure on the curl team due to a flood of credible AI-assisted security reports, with report rates 4-5 times higher than 2024 and over one per day on average. Despite the high volume and detail, the vulnerabilities found are mostly low or medium severity.

The shift to agentic AI creates new CPU requirements for AI factories: fast cores, massive memory bandwidth, and sustained high performance under all-core load. Initial Phoronix benchmarks show NVIDIA's Vera CPU delivers. With 88 custom Olympus cores, 1.2 TB/s memory bandwidth, and an efficient power envelope, Vera outperforms previous-generation Grace by 1.6x and leads against latest x86 processors in code compilation, file compression, video transcoding, and more. Its LPDDR5X memory subsystem achieves 90% peak bandwidth while consuming under 30 watts—over 4x memory bandwidth per core versus traditional x86. NVIDIA has shipped early Vera CPUs to leading AI companies and cloud providers, with partner availability expected in the second half of the year.

Despite 97% of telecom executives adopting AI, most initiatives stall due to 'data debt'—fragmented, ungoverned, and semantically opaque data. NVIDIA's report indicates the bottleneck is data availability, not model quality. Databricks Unity Catalog addresses this with a unified semantic layer and governance, enabling cross-system data federation, fine-grained access control, and rich semantic context to move AI from demo to production.

Amazon Bedrock AgentCore payments is now available in preview, providing instant payments to paid external services with no manual billing setup per provider, stablecoin support for cost-effective microtransactions making sub-cent transactions economically viable, and configurable spending guardrails for fine-grained control over agent budgets and transaction limits.

In this post, we provide a solution to build highly scalable, serverless multi-agent generative AI systems on AWS using LangGraph Agents as orchestrators integrated with Amazon Bedrock AgentCore Memory and Amazon Bedrock AgentCore Observability.

Learn how to build a multi-agent campaign review system that demonstrates parallel reasoning, context persistence, and traceable execution paths using an integrated architecture combining NVIDIA NIM for GPU-accelerated inference, Amazon Bedrock AgentCore for managed runtime, and Strands Agents for serverless orchestration.

This post demonstrates AgentWatch, a proactive AWS monitoring solution that checks infrastructure every 15 minutes, summarizes CloudWatch metrics, logs, and alarms across multiple accounts, and delivers actionable reports to Slack. It responds to natural language queries and implements three human-in-the-loop patterns to balance automation with oversight.