Physical AI systems – including robotics, smart vision systems, and other sensor-driven devices- are becoming more capable, taking in data from multiple sensors and inferencing in real-time. For many teams however, building a product on embedded Linux can still be slow and difficult. Using traditional platforms such as Yocto, many engineers face a steep learning curve – particularly when teams need to move quickly from prototype to deployment.
Does developing a physical AI system have to be hard? We don’t think so.
In this technical session, Peridio, NXP, and ipXchange will show you can use Avocado OS to build and deploy physical AI applications, covering how to reduce Yocto overhead, containerization, and NXP’s scalable portfolio. We will also show a live demonstration of the operating system on NXP i.MX 8M Plus.
What you’ll learn:
- How Avocado OS by Peridio reduces Yocto complexity and provides a user-friendly developer experience.
- How to containerise applications for deployment across multiple hardware targets
- How NXP’s i.MX portfolio supports scalable edge AI applications throughout a product’s lifecycle.
- A live demonstration of computer vision deployed onto an NXP i.MX 8M Plus EVK using Peridio.
Free