AI & Society

VMware Cloud Foundation 9.1 became available on May 12, 2026, as build 25377994. The release covers infrastructure efficiency, Kubernetes operations, private AI, cyber resilience, platform scale, and lifecycle improvements. The headline features are significant, but they are not the whole story. [A] The more consequential change is architectural. VCF 9.1 consolidates more fleet lifecycle, software-depot, […]

A South Korean court awarded $644 million to Roh Soh-yeong, who had sought much more from her ex-husband, Chey Tae-won, the head of the conglomerate behind SK Hynix.

TL;DR The MCP gateway should be the governed capability-access layer beneath the trusted agent controller. It should admit approved servers, expose only permitted tools, validate schemas, enforce identity and routing rules, isolate credentials, detect capability changes, and preserve trace evidence. The gateway should not become the only security control. Each MCP server must still enforce

A.I. has rendered eye candy cheap. Viewers long for the visceral.

Learning to use A.I. effectively at work is all about using the same tried-and-true skills we use to be a better manager and collaborator.

Advances in A.I. are making it possible to create all kinds of music from scratch, but they also raise questions about what is legal and who will actually listen.

TL;DR Do not create a VMware Cloud Foundation workload domain every time a tenant, business unit, application, or security team asks for separation. In VCF 9.1, the correct design is usually to choose the smallest boundary that satisfies the strongest verified requirement. A subnet or segment separates network attachment. An NSX VPC separates application networking,

TL;DR A rack of healthy GPU servers is not a production-ready VCF Private AI platform. Production acceptance should prove the complete service chain: supported hardware, aligned ESXi and NVIDIA software, a healthy VCF 9.1 workload domain, stable NSX and shared infrastructure services, a ready Supervisor and VKS layer, functioning tenant controls, trusted Harbor and model

TL;DR Deploying VMware Private AI Foundation with NVIDIA on VCF 9.1 is not a single-product installation. It is an integrated platform deployment spanning the VCF workload domain, GPU-enabled ESXi hosts, NVIDIA drivers and licensing, vSphere Supervisor, namespaces, Private AI Services, Harbor, identity, networking, certificates, and the AI consumption model. The most important design decision happens

TL;DR The NVIDIA RAG Blueprint is not one application pod. It is a coordinated retrieval platform that combines an ingestion service, a RAG server, NVIDIA NIM microservices, NV-Ingest, a vector database, object storage, model caches, and supporting Kubernetes operators. For the current 2.6.0 release, Elasticsearch is the default vector database and SeaweedFS is the default