Enabling AI/ML at the Edge With or Without Connectivity

About This Tech Talk

AI/ML at the edge is often associated with data eventually reaching the cloud, but many real-world applications can collect data and make decisions locally without the need for connectivity. This session will explore how developers can add AI/ML inferencing to standalone or wired devices, with the flexibility to incorporate wireless capabilities when ready. This level of flexibility is key to driving the growth of TinyML.

We will examine various use cases from both connected and non-connected perspectives, highlighting applications that benefit from this flexibility. We will be joined by a Silicon Labs partner, ETA Compute, to demonstrate how quickly you can start building and deploying complex models, such as vision, on our latest SoCs.

Join us to explore these use cases, learn how Silicon Labs supports the migration path for AI/ML in connected and non-connected devices, and discover the available tools for AI/ML developers.

You can view the accompanying slides and recorded session below.