Tech Talks Daily

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

  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.

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• Inside Audi’s Smart Factory Vision at VMware Explore

  Factories don’t usually make headlines at tech conferences, but what Audi is doing inside its production labs is anything but ordinary. At VMware Explore in Las Vegas, I sat down with Dr. Henning Löser, Head of the Audi Production Lab, to talk about how the automaker is reinventing its factory floor with a software-first mindset. Henning leads a small team he jokingly calls “the nerds of production,” but their work is changing how cars are built. Instead of replacing entire lines for every new piece of technology, Audi has found a way to bring the speed and flexibility of IT into the world of industrial automation. The result is Edge Cloud 4 Production, a system that takes virtualization technology normally reserved for data centers and applies it directly to manufacturing. In our conversation, Henning explained why virtual PLCs may be one of the biggest breakthroughs yet. They look invisible to workers on the line but give maintenance teams new transparency and resilience. We explored how replacing thousands of industrial PCs with centralized, virtualized workloads not only reduces downtime but also cuts energy use and simplifies updates. And yes, we even discussed the day a beaver chewed through one of Audi’s fiber optic cables and how redundancy kept production running without a hitch. This episode is about more than smart factories. It’s about how an industry known for heavy machinery is learning to think like the cloud. From scalability and sustainability to predictive maintenance and AI-ready infrastructure, Audi is showing how the car of the future starts with the factory of the future. If you’ve ever wondered how emerging technologies like virtualization and private cloud are reshaping the shop floor, this is a story you’ll want to hear.

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• Fear vs FOMO: Kantar’s View on AI Adoption in Marketing

  In this episode of Tech Talks Daily, I speak with Jane Ostler from Kantar, the world’s leading marketing data and analytics company, whose clients include Google, Diageo, AB InBev, Unilever, and Kraft Heinz. Jane brings clarity to a debate often clouded by headlines, explaining why AI should be seen as a creative sparring partner, not a rival. She outlines how Kantar is helping brands balance efficiency with inspiration, and why the best marketing in the years ahead will come from humans and machines working together. We explore Kantar’s research into how marketers really feel about AI adoption, uncovering why so many projects stall in pilot phase, and what steps can help teams move from experimentation to execution. Jane also discusses the importance of data quality as the foundation of effective AI, drawing comparisons to the early days of GDPR when oversight and governance first became front of mind. From Coca-Cola’s AI-assisted Christmas ads to predictive analytics that help brands allocate budgets with greater confidence, Jane shares examples of where AI is already shaping marketing in ways that might surprise you. She also highlights the importance of cultural nuance in AI-driven campaigns across 90-plus markets, and why transparency, explainability, and human oversight are vital for earning consumer trust. Whether you’re a CMO weighing AI strategy, a brand manager experimenting with new tools, or someone curious about how the biggest advertisers are reshaping their playbooks, this conversation with Jane Ostler offers both inspiration and practical guidance. It’s about rethinking AI not as the end of creativity, but as the beginning of a new partnership between data, machines, and human imagination.

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• AlgoSec on AI, Automation, and the Next Era of Network Management

  The enterprise network is under pressure like never before. Hybrid environments, cloud migrations, edge deployments, and the sudden surge in AI workloads have made it increasingly difficult to keep application connectivity secure and reliable. The old model of device-by-device, rule-based network management can’t keep up with today’s hyperconnected, API-driven world. In this episode of Tech Talks Daily, I sit down with Kyle Wickert, Field Chief Technology Officer at AlgoSec, to discuss the future of network management in the age of platformization. With more than a decade at AlgoSec and years of hands-on experience working with some of the world’s largest enterprises, Kyle brings an unfiltered view of the challenges and opportunities that IT leaders are facing right now. We talk about why enterprises are rapidly shifting to platform-based models to simplify network security, but also why that strategy can start to break down when dealing with multi-vendor environments. Kyle explains the fragmentation across cloud, on-prem, and edge infrastructure that keeps CIOs awake at night, and why spreadsheets and manual change processes are still far too common in 2025. He also shares why visibility, intent-based policies, and policy automation are becoming non-negotiable in reducing risk and friction. Kyle doesn’t just talk theory. He shares a real-world case study of a European financial institution that automated policy provisioning across firewalls and cloud infrastructure, integrated it with CI/CD pipelines, and reduced its change rejection rate from 25% to 4%. It’s a compelling example of how the right approach to network management can deliver measurable improvements in agility, security, and business satisfaction.  

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• Claroty on Combating Model Poisoning and Adversarial Prompts

  AI is rapidly becoming part of the healthcare system, powering everything from diagnostic tools and medical devices to patient monitoring and hospital operations. But while the potential is extraordinary, the risks are equally stark. Many hospitals are adopting AI without the safeguards needed to protect patient safety, leaving critical systems exposed to threats that most in the sector have never faced before. In this episode of Tech Talks Daily, I speak with Ty Greenhalgh, Healthcare Industry Principal at Claroty, about why healthcare’s AI rush could come at a dangerous cost if security does not keep pace. Ty explains how novel threats like adversarial prompts, model poisoning, and decision manipulation could compromise clinical systems in ways that are very different from traditional cyberattacks. These are not just theoretical scenarios. AI-driven misinformation or manipulated diagnostics could directly impact patient care. We explore why the first step for hospitals is building a clear AI asset inventory. Too many organizations are rolling out AI models without knowing where they are deployed, how they interact with other systems, or what risks they introduce. Ty draws parallels with the hasty adoption of electronic health records, which created unforeseen security gaps that still haunt the industry today. With regulatory frameworks like the UK’s AI Act and the EU’s AI regulation approaching, Ty stresses that hospitals cannot afford to wait for legislation. Immediate action is needed to implement risk frameworks, strengthen vendor accountability, and integrate real-time monitoring of AI alongside legacy devices. Only then can healthcare organizations gain the trust and resilience needed to safely embrace the benefits of AI. This is a timely conversation for leaders across healthcare and cybersecurity. The sector is on the edge of an AI revolution, but the choices made now will determine whether that revolution strengthens patient care or undermines it. You can learn more about Claroty’s approach to securing healthcare technology at claroty.com.

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