Private AI Takes Center Stage at VMware Explore with Broadcom’s Tasha Drew

Aug 30, 2025

Tasha Drew, Director of Engineering for AI at Broadcom, dives into the exciting realm of private AI services unveiled at VMware Explore. She discusses the critical importance of protecting sensitive data and managing compliance through private AI integration. Tasha explains why businesses are shifting from public to private AI to address cost and data challenges. Listeners will also learn about VMware’s innovative Intelligent Assist, designed to streamline AI deployments, and the latest private AI features promising enhanced operational efficiency.

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INSIGHT

Three Pillars Of Private AI

Private AI rests on three pillars: protecting IP, managing sensitive/regulatory data, and role-based control of fine-tuned models.
Models fine-tuned on private data become as sensitive as that data and require strict access controls.

INSIGHT

Public Cloud For Sandbox, Private For Production

Organizations experiment in public cloud because GPU procurement and services are fast, then move workloads private when cost, compliance, or data proximity matter.
Moving to private cloud becomes attractive once teams model infrastructure needs and see production cost and compliance constraints.

ADVICE

Deliver Models As A Service

Build an AI platform that lets IT deliver models as a service and optimize GPU utilization to save money.
Design platform features that show clear efficiency and cost savings to justify private AI investments.

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At VMware Explore in Las Vegas, the buzz wasn’t just about generative AI, but about where and how it should run. My guest is Tasha Drew, Director of Engineering for the AI team in the VMware Cloud Foundation division at Broadcom, who has been at the center of this conversation. Fresh off the main stage, where she helped debut VMware’s new Private AI Services and Intelligent Assist for VMware Cloud Foundation, Tasha joins me to unpack what these announcements mean for enterprises grappling with privacy, cost, and integration challenges.

Tasha explains why private AI is resonating so strongly in 2025, outlining the three pillars that define it: protecting sensitive intellectual property, managing regulated or high-value data, and ensuring role-based control of fine-tuned models. She shares how organizations often start their AI journey in the public cloud, but as experimentation turns to production, cost pressures, data compliance, and proximity to data drive them toward private AI.

We also dive into VMware’s own evolution toward building an AI-native private cloud platform. Tasha highlights the journey from deep learning VMs and Jupyter notebooks to full AI platform services that empower IT teams to deliver models efficiently, save money, and accelerate deployment of retrieval-augmented generation (RAG) applications. She introduces Intelligent Assist for VMware Cloud Foundation, an AI-powered guide that helps teams navigate complex deployments with context-aware support and step-by-step instructions.

Beyond the technology, Tasha reflects on the broader ecosystem shifts, from partnerships with NVIDIA and AMD to the role of Model Context Protocol (MCP) in breaking down integration barriers between enterprise systems. She believes MCP represents a turning point, enabling seamless workflows between platforms that historically lacked incentive to work together.

This conversation captures a pivotal moment where private AI is moving from theory into enterprise adoption. For leaders weighing their next move, Tasha provides both the strategic framing and the technical insight to understand why private AI has become one of the most talked-about forces shaping enterprise IT today.