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014 - Project Q9: Where Robotics and AI meet (with Sander Harrewijnen)
In this episode, Johan is joined by long-time colleague Sander Hardewijnen to pull back the curtain on Project Q9 — an ambitious internal project at ITQ that combines a Unitree Go 2 Pro robotic dog, private AI, computer vision, and modern cloud-native development practices.
From gesture recognition trained on 30,000 hand images to a Skynet-obsessed dog posting on LinkedIn, this episode is a deep dive into what happens when you give great engineers a suitcase full of robot and say, "see where it goes."
The conversation also covers the state of open-source AI coding assistants (OpenClaw vs NemoClaw), the realities of vibe coding in a production context, and what partner platforms like Red Hat OpenShift AI and SUSE AI actually enable beyond conversational AI.
Sander's blog: https://harre.dev
Q9's LinkedIn page: https://www.linkedin.com/in/q9-the-dog-2206863b1/
Chapters
00:00 Welcome & Introduction01:20 Icebreaker: Best AI Fail02:12 NemoClaw vs OpenClaw: Security & Sandboxing04:49 Running OpenClaw in an Isolated VLAN05:32 OpenClaw as a Personal Assistant: Home Assistant, News & Efteling API09:11 OpenClaw in the ITQ WhatsApp Group11:10 Introducing Project Q913:22 Why Robotics + Cloud-Native + AI?16:16 Technical Anatomy of Q918:30 Partner Platform Showcase: Broadcom, Red Hat & SUSE19:20 Debunking the GPU Myth23:05 Building the Gesture Recognition Model25:00 Training Progression: Epochs, Accuracy & Landmarks30:21 Hand Landmark Detection & the Gesture Pipeline32:34 Crowd Reactions at KubeCon33:57 Fine-Tuning vs Training From Scratch36:16 Use Case 2: Q9's LLM-Powered LinkedIn Persona40:41 Running LLMs on Partner Inference Platforms42:26 What's Next for Q9?43:44 Digital Twins in NVIDIA Omniverse + ROS245:10 Key Takeaways48:53 Responsible Vibe Coding49:58 Open-Sourcing Q9 — Coming Soon
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By Johan van AmersfoortIn this episode, Johan is joined by long-time colleague Sander Hardewijnen to pull back the curtain on Project Q9 — an ambitious internal project at ITQ that combines a Unitree Go 2 Pro robotic dog, private AI, computer vision, and modern cloud-native development practices.
From gesture recognition trained on 30,000 hand images to a Skynet-obsessed dog posting on LinkedIn, this episode is a deep dive into what happens when you give great engineers a suitcase full of robot and say, "see where it goes."
The conversation also covers the state of open-source AI coding assistants (OpenClaw vs NemoClaw), the realities of vibe coding in a production context, and what partner platforms like Red Hat OpenShift AI and SUSE AI actually enable beyond conversational AI.
Sander's blog: https://harre.dev
Q9's LinkedIn page: https://www.linkedin.com/in/q9-the-dog-2206863b1/
Chapters
00:00 Welcome & Introduction01:20 Icebreaker: Best AI Fail02:12 NemoClaw vs OpenClaw: Security & Sandboxing04:49 Running OpenClaw in an Isolated VLAN05:32 OpenClaw as a Personal Assistant: Home Assistant, News & Efteling API09:11 OpenClaw in the ITQ WhatsApp Group11:10 Introducing Project Q913:22 Why Robotics + Cloud-Native + AI?16:16 Technical Anatomy of Q918:30 Partner Platform Showcase: Broadcom, Red Hat & SUSE19:20 Debunking the GPU Myth23:05 Building the Gesture Recognition Model25:00 Training Progression: Epochs, Accuracy & Landmarks30:21 Hand Landmark Detection & the Gesture Pipeline32:34 Crowd Reactions at KubeCon33:57 Fine-Tuning vs Training From Scratch36:16 Use Case 2: Q9's LLM-Powered LinkedIn Persona40:41 Running LLMs on Partner Inference Platforms42:26 What's Next for Q9?43:44 Digital Twins in NVIDIA Omniverse + ROS245:10 Key Takeaways48:53 Responsible Vibe Coding49:58 Open-Sourcing Q9 — Coming Soon