Prototyping edge AI applications traditionally requires writing heavy boilerplate code, managing complex cross-compilation, and struggling to bridge ML environments with deterministic hardware control. Arduino doesn’t think so.
Join us for an exclusive 90-min engineer-to-engineer technical session focused on building with App Lab on the Arduino UNO Q. Hosted by ipXchange and Arduino, this session will explore the board’s powerful dual-brain architecture and show you how you can speed up prototyping your next edge AI application.
We will be diving into the code and demonstrating how to deploy local machine learning models without building everything from scratch.
What you’ll learn:
- Understand how to leverage the Qualcomm Dragonwing™ QRB2210 alongside STM32U585 for simultaneous AI inference and real-time sensor control.
- Prototyping with App Lab “Bricks”, combining a Python environment with C++ hardware sketches to rapidly build applications.
- Learn how to use local machine learning models to control deterministic hardware IO.
- A walkthrough of ready-to-use App Lab examples, showing you how to develop local AI vision applications natively on the UNO Q.
Free