This Peridio webinar covers NVIDIA-focused AI native IoT solutions. Come learn about their product lines' strengths and cons and the benefits of developing in their ecosystem.
In our latest webinar, we had the privilege of bringing together some of the sharpest minds in Generative AI and edge technology to discuss how advancements in NVIDIA's platforms are transforming autonomous systems. Hosted by Peridio, this insightful session focused on the future of AI-driven edge computing and robotics.
Meet the Experts
The panel featured industry leaders who are pushing the boundaries of what's possible in AI:
- John Pratt (CTO, Pattern Labs), whose work in autonomous vehicles is revolutionizing airport logistics with NVIDIA technologies.
- Adam Benzion (SVP, Edge Impulse), simplifying machine learning for edge devices.
- Dan Walkes (Founder, Trellis Logic), offering expert insights into building edge AI systems on NVIDIA platforms.
- Justin Schneck (Chief Product Officer, Peridio), with a wealth of knowledge in scaling embedded products for real-world applications.
The Heart of the Discussion
- How NVIDIA's Jetson is Driving Edge Innovation
The discussion kicked off with John explaining how NVIDIA's Jetson series—particularly the Jetson Xavier—enables Pattern Labs to run heavy-duty AI models on portable, battery-powered vehicles. From automating airport operations to processing massive amounts of sensor data in real-time, Jetson has become the backbone of their autonomous systems, proving that you don't need a data center to deliver desktop-class performance. - Simulations and Synthetic Data: A Game-Changer for AI Development
Both Adam and John shed light on the power of simulation and synthetic data for AI training. Whether it's testing AI models in virtual environments or generating realistic data sets for edge devices, simulations are dramatically speeding up development cycles. Adam pointed out how this technology, once reserved for large companies, is now more accessible, allowing developers to test AI systems without needing constant access to physical hardware. - Bringing Machine Learning Models to Life on the Edge
Adam shared how Edge Impulse simplifies the journey from model training to deployment. Leveraging tools like NVIDIA TAO and DeepStream, developers can now fine-tune and deploy powerful AI models on edge devices. This has opened the door to real-time decision-making, with AI models performing complex tasks—such as object detection and environment sensing—at the edge, where fast responses are crucial. - The Role of Synthetic Data in Robotics and IoT
One of the highlights of the discussion was the growing importance of synthetic data in robotics and IoT. Both Justin and Dan emphasized how synthetic data is reducing development time while allowing teams to train models more effectively. Justin explained how the use of synthetic data bypasses many privacy concerns and enables faster prototyping, making it an essential tool for modern AI development.
Looking to the Future: What's Next for AI and Edge Computing?
As we look ahead, it's clear that Generative AI and edge computing are poised to reshape industries. Our panelists shared a forward-looking vision where these technologies become even more integrated into everyday operations—powering autonomous vehicles, enhancing IoT systems, and driving smarter, more efficient industrial solutions.
Whether you're new to edge AI or already working with platforms like NVIDIA Jetson, this webinar provided a wealth of insights into how Generative AI is driving the future of connected systems. If you missed the session, be sure to catch the full recording [here].
Stay tuned for more expert-led webinars as we continue to explore cutting-edge developments in AI, edge technology, and autonomous systems.
