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Broadcom has launched VMware Private AI Cloud, combining VMware Cloud Foundation 9 (VCF 9) with the VMware AI Factory software layer to operate enterprise AI workloads in private-cloud environments. The platform targets AI infrastructure capital costs, operational complexity, and token-related spending through storage optimization, token monitoring, and GPU/vGPU usage tracking, while providing access to more than 150 open-source and commercial AI models.
The service extends VCF Private AI governance with an AI Gateway for centralized model access, prompt routing, and policy controls across on-premises and cloud deployments. Broadcom also introduced agent-security capabilities including AgentMinder for authentication, authorization, monitoring, and audit of autonomous-agent actions, plus sandboxing and runtime restrictions intended to limit agent permissions, network communications, and resource consumption; TrueSource supplies curated, hardened open-source artifacts for AI deployments.
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Broadcom stated that VMware Private AI Cloud launched in August 2024, combining enterprise private-cloud and private-AI infrastructure built around VMware Cloud Foundation.
Broadcom unveiled VMware Private AI Cloud at VMware Explore in Las Vegas, positioning it for production inference and agentic-AI workloads with data sovereignty, compliance, and predictable-cost goals. The offering includes VCF 9 capabilities for NVMe memory tiering, storage deduplication, token monitoring, and GPU/vGPU tracking, alongside centralized AI Gateway governance.
Broadcom launched AgentMinder to authenticate, authorize, monitor, and audit autonomous AI-agent activity. The platform requires agents to identify themselves and declare intended actions, enforcing runtime security and least-privilege controls on tool calls.
Broadcom launched TrueSource, combining its open-source offerings with clean-room builds and hardened container images for Java, Python, and Node.js, plus supported data-service artifacts for PostgreSQL, RabbitMQ, MySQL, and Valkey.
Broadcom's VMware division expanded VMware Cloud Foundation with VMware AI Factory and added VCF Private AI capabilities including multitenant model sharing, an AI gateway, and a secure agent framework. The company also validated more than 150 AI models for on-premises VCF deployments.
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Palo Alto Networks and Google Cloud have announced an expanded, multibillion-dollar partnership aimed at embedding advanced security capabilities directly into Google Cloud’s AI and infrastructure services. The agreement, reportedly valued at nearly $10 billion over several years, will see Palo Alto Networks’ Prisma AIRS platform integrated with Google Cloud offerings such as Vertex AI and Agent Engine, providing end-to-end protection for AI workloads, data, and development tools. This collaboration is a response to the increasing frequency of attacks on AI infrastructure, with Palo Alto Networks reporting that 99% of surveyed organizations experienced at least one attack on their AI systems in the past year. The partnership is designed to address the complexity of securing hybrid and multicloud environments as enterprises rapidly scale AI deployments. By aligning Palo Alto’s network and AI security solutions with Google Cloud’s infrastructure, the companies aim to deliver a unified security experience, reduce operational complexity, and ensure consistent enforcement of security policies. The deal also involves Palo Alto Networks migrating key internal workloads to Google Cloud, further deepening the strategic relationship between the two firms.
Jun 29, 2026
Apple said some **Apple Intelligence** requests that exceed on-device limits will now run in Google Cloud under an expanded **Private Cloud Compute (PCC)** architecture, while simpler tasks continue to be processed locally and other cloud workloads remain on Apple-operated servers. The company said its newer model stack includes on-device `AFM 3 Core` and `AFM 3 Core Advanced`, Apple-hosted `AFM 3 Cloud` and `ADM 3 Cloud`, and `AFM 3 Cloud Pro`, which runs on Google-owned NVIDIA hardware for more demanding queries. Apple said the privacy model is unchanged despite the move to third-party infrastructure, with protections built around stateless processing, non-targetability, no privileged runtime access, and verifiable transparency. To enforce those guarantees on Google Cloud, Apple said it is using **NVIDIA Confidential Computing**, **Intel TDX**, Google’s **Titan** security chip, Apple-signed software attestation, and a cryptographically verifiable append-only ledger of approved hardware; the company also plans to publish PCC binaries and extend researcher access through the **Apple Security Bounty** program.
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The U.S. Commerce Department withdrew an early draft **AI hardware export rule** that would have tied access to advanced American accelerators to foreign investment in U.S. AI infrastructure, while officials said a broader replacement framework is still being developed. The abandoned proposal reportedly envisioned a tiered licensing model based on computing scale, with expedited approval for smaller shipments and tighter conditions for large AI cluster deployments, underscoring that Washington is still recalibrating how it will control the global distribution of high-end AI compute. At the same time, **ByteDance** is moving ahead with access to a **36,000-GPU Nvidia Blackwell cluster** in Malaysia through cloud operator *Aolani Cloud*, in a deal Nvidia said complies with current U.S. export controls. The planned deployment, reportedly worth about **$2.5 billion** and built from **500 NVL72 GB200 systems**, highlights how Chinese firms may still obtain substantial overseas AI compute capacity through third-country infrastructure even as direct chip access remains restricted. A separate analysis of **Huawei’s HarmonyOS** and China’s broader AI ecosystem is not about this specific export-control development and should be excluded.
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