The Private AI Lab

Johan van Amersfoort

The Private AI Lab is a monthly podcast where we explore the future of Artificial Intelligence behind the firewall. Hosted by Johan from Johan.ml, each episode invites industry experts, innovators, and thought leaders to discuss how Private AI is reshaping enterprises, technology, and society. From data sovereignty to air-gapped deployments, from GPUs to governance — this podcast uncovers the real-world experiments, failures, and breakthroughs that define the era of Private AI. 🎙️ New episode every month. 🌐 More at Johan.ml

  1. 012 - From Sepsis to Sovereign Cloud: OpenShift AI in Healthcare (with Vincent Tsugranes)

    13 HR AGO

    012 - From Sepsis to Sovereign Cloud: OpenShift AI in Healthcare (with Vincent Tsugranes)

    AI in healthcare didn’t start with ChatGPT. Long before generative AI, hospitals were using machine learning for sepsis detection, imaging diagnostics, and predictive analytics. In this episode of The Private AI Lab, Johan sits down with Vincent Tsugranes, Chief Architect at Red Hat, to explore what’s real, what’s hype, and why platform matters more than ever. They discuss: Why 95% of AI projects fail The evolution from OpenShift Data Science to OpenShift AI Models-as-a-Service inside hospitals vLLM vs LLMD for large-scale inference Guardrails, hallucinations, and enterprise risk Sovereign cloud and why healthcare is moving on-prem again What “ambient AI” might mean in the next 12 months This episode is for architects, platform engineers, healthcare IT leaders, and anyone building private AI in regulated environments. 00:00 – Red lights & farming with AI 02:10 – The first AI spark moment 04:00 – When “AI” became AI (ChatGPT moment) 07:20 – Why 95% of AI projects fail 11:00 – Machine learning vs modern AI 13:30 – Platform vs point solutions 16:00 – The history of OpenShift AI 19:00 – What is OpenShift AI under the hood? 22:00 – Hardware enablement & NVIDIA 25:00 – vLLM explained 27:30 – LLMD and distributed inference 30:00 – Healthcare use cases (sepsis, imaging, insurance) 33:00 – Models-as-a-Service inside hospitals 36:00 – Guardrails & hallucination risks 39:00 – Observability & FinOps explosion 42:00 – OpenShift 5 and platform intelligence 44:30 – Sovereign cloud in healthcare 48:00 – The future: ambient AI & rising power bills

    51 min
  2. 011 - Open Source AI Just Leveled Up — Meet NVIDIA Nemotron Super

    6 DAYS AGO

    011 - Open Source AI Just Leveled Up — Meet NVIDIA Nemotron Super

    Recorded live at NVIDIA GTC 2026, this episode dives into one of the biggest announcements in open AI: Nemotron Super. Together with Joey Conway, we explore how NVIDIA is pushing open source AI forward — with models that are not only powerful, but also efficient and enterprise-ready. We discuss: The evolution from Llama-based models to Nemotron Why reasoning + agentic capabilities matter How NVIDIA balances performance and efficiency What NVFP4 means for running AI locally And why this could be a turning point for AI behind the firewall Chapters 00:00 Intro 01:56 Welcome 02:37 GTC insights 03:31 Nemotron buzz 04:53 Model evolution 07:14 Core design principles 09:05 Reasoning capabilities 10:52 Scaling challenges 12:00 Architecture deep dive 13:12 Performance improvements 14:14 Quantization strategy 15:39 NVFP4 explained 16:16 DGX Spark use case 18:23 Broader adoption 19:37 Agentic AI impact 21:25 Try it yourself 22:03 Outro Links Try Nemotron: https://build.nvidia.com More episodes: https://johan.ml

    21 min
  3. 010 - Open Source AI at NVIDIA GTC (with Rhys Oxenham and Sanjeet Singh from SUSE)

    12 MAR

    010 - Open Source AI at NVIDIA GTC (with Rhys Oxenham and Sanjeet Singh from SUSE)

    Open source is becoming one of the most important forces in AI. In this episode of The Private AI Lab, Johan speaks with Rhys Oxenham and Sanjeet Singh from SUSE about the role of open source in building enterprise AI platforms. They explore: The difference between open source AI infrastructure and open-weight models Why enterprises are moving toward private AI deployments The growing importance of digital sovereignty Innovation happening in the open source AI ecosystem Why specialized models may challenge large frontier models How SUSE helps organizations deploy AI platforms securely The episode also previews NVIDIA GTC, where open source AI is a major theme. All Open Source AI sessions in the content catalog: https://www.nvidia.com/gtc/session-catalog/?search=open%20source Register for NVIDIA GTC today using the following link: https://nvda.ws/4qXGFjm

    36 min
  4. 009 - Getting excited for NVIDIA GTC with Dirk Glücker

    6 MAR

    009 - Getting excited for NVIDIA GTC with Dirk Glücker

    What should you expect from NVIDIA GTC 2026? In this pre-show episode of The Private AI Lab, Johan talks with Dirk Glücker, AI platform engineer and Kubernetes specialist, about the sessions, technologies, and trends worth watching at this year’s conference. They discuss: The unique culture of GTC compared to other tech conferences Key sessions around MLOps, distributed inference, and AI infrastructure What we might see in Jensen Huang’s keynote The evolution of AI factories and large GPU clusters Why networking and meet-the-expert sessions are invaluable Practical advice for navigating GTC (or watching remotely) If you’re building AI platforms, running GPU infrastructure, or following the latest developments in accelerated computing, this episode is a great primer before the event. Links mentioned: AI Fail video from Dirk: https://www.youtube.com/watch?v=CWGefSIVIKM All hybrid sessions in the content catalog: https://register.nvidia.com/flow/nvidia/gtc26/ap/page/catalog?tab.catalogallsessionstab=16566177511100015Kus&search.viewingexperience=1700085746191002Cnn0 Register for NVIDIA GTC today using the following link: https://nvda.ws/4qXGFjm Chapters: 00:00 – Welcome to the GTC pre-show 00:40 – Meet Dirk Glücker 01:20 – AI fail of the week: robot meets mirror 04:10 – Physical AI and robotics challenges 05:20 – What GTC is like for first-time attendees 07:50 – Highlights from last year’s conference 08:10 – DGX Spark and AI factories 09:10 – Why meeting experts at GTC matters 12:20 – How to plan your GTC schedule 13:00 – MLOps sessions worth attending 14:30 – AI coding agents and development automation 16:10 – Distributed inference at scale 17:00 – Inside NVIDIA’s inference ecosystem 18:00 – AI infrastructure and platform engineering 19:30 – Multi-tenant GPU clusters 21:00 – Pixar rendering pipelines and GPUs 22:00 – Formula One and AI performance 23:00 – Watching GTC remotely 24:00 – Open source inference and sovereign AI 26:30 – Overlapping sessions and planning strategy 27:10 – Predictions for Jensen Huang’s keynote 31:00 – AI factory networking infrastructure 33:00 – Exploring the GTC expo floor 37:00 – Tips for first-time attendees 44:00 – Final thoughts before GTC

    49 min
  5. 008 - Vibe Coding: Productivity Hack or Production Nightmare?

    19 FEB

    008 - Vibe Coding: Productivity Hack or Production Nightmare?

    Is vibe coding the ultimate productivity accelerator — or a fast track to 4AM production outages? In this episode of The Private AI Lab, Johan speaks with Andrew Morgan about the real state of vibe coding in 2026. They unpack the difference between vibe coding and vibe learning, explore the risks of blindly trusting AI-generated code, and debate whether this new wave of AI-native development is democratizing software engineering — or quietly lowering the bar. The conversation covers rogue agents, context window limits, guardrails, on-prem AI strategies, enterprise accountability, and why thinking might become the most important engineering skill of the next decade. This episode is for developers, platform engineers, architects, and anyone navigating AI-assisted software development. 00:00 – Welcome to The Private AI Lab 01:40 – Andrew’s biggest AI fail 03:00 – The sunken cost fallacy of prompting 04:45 – Rogue agents & expensive mistakes 06:30 – Skynet jokes (but not really) 07:20 – What is vibe coding? 09:00 – Trust, guardrails & blast radius 10:15 – The current tooling landscape 12:00 – Vibe coding inside teams 14:40 – Stack Overflow vs vibe coding 17:00 – Code completion on steroids 18:30 – Who’s using it most aggressively? 20:45 – Democratization or dilution? 23:00 – Accountability at 4AM 25:00 – Lazy engineers vs lazy vibecoders 27:00 – Debugging AI-generated code 30:00 – Crab dragons & technical debt 32:30 – DevOps knowledge & production readiness 35:00 – Human vs AI code reviews 37:30 – Private AI & vibe coding 40:00 – On-prem vs cloud agents 42:30 – Context windows & hallucinations 44:00 – The next 18 months 47:30 – Strong engineers vs weak engineers 49:30 – Security risks & red teaming 52:00 – Is thinking the new bottleneck? 54:00 – Final lab report & takeaways

    1hr 7min
  6. #007 - From Zero to Agentic AI — All Before Your Coffee Gets Cold (with Tasha Drew)

    5 FEB

    #007 - From Zero to Agentic AI — All Before Your Coffee Gets Cold (with Tasha Drew)

    What if deploying private, enterprise-grade AI didn’t take months—but only as long as it takes your coffee to cool? In this episode of The Private AI Lab, Johan van Amersfoort sits down with Tasha Drew to unpack how Private AI Services on VMware Cloud Foundation are changing the way enterprises build and consume AI. They discuss why AI needs a platform layer, how Broadcom integrates open source responsibly, what MCP means for enterprise AI, and how agentic AI workloads can be deployed securely, governed properly, and operated at scale—inside the private cloud. If you like to follow Tasha, you can do that on linkedin:https://www.linkedin.com/in/tashy/ Topics covered Why “training” is the most misused AI term From zero to RAG and agentic AI in minutes Private AI Services and the VCF strategy Model runtime, API gateways, and GPU efficiency Data indexing & retrieval for enterprise RAG Open source trade-offs: speed vs flexibility MCP, tool usage, and governance How Broadcom uses its own AI platform internally The future of agents: specialists over monoliths If you like to follow Tasha, you can do that on linkedin:https://www.linkedin.com/in/tashy/

    57 min
  7. #006 - The Subtle Art of Inference with Adam Grzywaczewski

    22 JAN

    #006 - The Subtle Art of Inference with Adam Grzywaczewski

    In this episode of The Private AI Lab, Johan van Amersfoort speaks with Adam Grzywaczewski, a senior Deep Learning Data Scientist at NVIDIA, about the rapidly evolving world of AI inference. They explore how inference has shifted from simple, single-GPU execution to highly distributed, latency-sensitive systems powering today’s large language models. Adam explains the real bottlenecks teams face, why software optimization and hardware innovation must move together, and how NVIDIA’s inference stack—from TensorRT-LLM to Dynamo—enables scalable, cost-efficient deployments. The conversation also covers quantization, pruning, mixture-of-experts models, AI factories, and why inference optimization is becoming one of the most critical skills in modern AI engineering. Topics covered Why inference is now harder than training Autoregressive models and KV-cache challenges Mixture-of-experts architectures NVIDIA Dynamo and TensorRT-LLM Hardware vs software optimization Quantization, pruning, and distillation Latency vs throughput trade-offs The rise of AI factories and DGX systems What’s next for AI inference

    53 min
  8. #005 - The Why, What, and How of MCP with Maxime Colomès

    8 JAN

    #005 - The Why, What, and How of MCP with Maxime Colomès

    In this episode of The Private AI Lab, Johan van Amersfoort talks with Maxime Colomès about the Model Context Protocol (MCP)—one of the most important emerging standards in AI today. MCP is often described as the USB-C of AI: a universal way for AI models to connect to tools, data sources, and real-world systems. Maxime explains what MCP is, how it works, and why its recent donation to the Linux Foundation is such a major milestone for the AI ecosystem. They explore real-world enterprise use cases, MCP security considerations, private AI architectures, and how MCP integrates with platforms like OpenShift AI. The conversation also touches on developer productivity, AI agents that can take action, and the future of personal, privacy-preserving AI assistants. Key topics What the Model Context Protocol (MCP) is and why it matters MCP vs traditional APIs and plugin systems Enterprise MCP architectures and gateways MCP and private AI / data sovereignty OpenShift AI and MLOps workflows Security risks and best practices with MCP Community MCP servers and registries Future MCP use cases and predictions

    1hr 3min
See All (13)

Trailer

About

The Private AI Lab is a monthly podcast where we explore the future of Artificial Intelligence behind the firewall. Hosted by Johan from Johan.ml, each episode invites industry experts, innovators, and thought leaders to discuss how Private AI is reshaping enterprises, technology, and society. From data sovereignty to air-gapped deployments, from GPUs to governance — this podcast uncovers the real-world experiments, failures, and breakthroughs that define the era of Private AI. 🎙️ New episode every month. 🌐 More at Johan.ml

Information

  • Creator
    Johan van Amersfoort
  • Years Active
    2025 - 2026
  • Episodes
    13
  • Rating
    Explicit
  • Copyright
    © Johan van Amersfoort
  • Show Website
    The Private AI Lab

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