furtiman

This is a talk that I made back in February at TechEX conference in London.

edge AI is becoming ingrained in the industry. This is especially evident now in 2025; edge AI is no longer a mythical creature or two separate words in a sentence, but a set of technologies and practices that is proven to deliver real value and is being adopted by largest players in all kinds of verticals. But how does this latest and greatest category advance IoT — a recent technology that has found mass adoption across all sectors? The convergence of IoT, AI, and edge computing is now reshaping industries. It enables smarter, faster, and more efficient systems. In the talk I highlighted how these technologies are evolving and why their integration is critical for the future of innovation.

In this video I talk about a plugin that I made in Edge Impulse (platfrom for building edge AI).

The general approach can be applied anywhere and standalone though - use a foundational audio classifier to look at your unlabeled audio dataset! This approach is two-fold: first - we give the model a few sampels of an event or sound type we are looking for and determine to which class from the ones the model knows it belongs. It can be though of as encoding our sound events in the model "language".

After that we give larger samples that may or may not contain these events and tell the model to only react when those classes identified earlier are identified.

This way we can explore large audio datasets quickly. There is a good chance that some classifications are not exactly right - but it gives you a subset of you audio to actually take a look at - instead of having to listen though all of it!

Imagine you have a product. And you want it to react to a very specific keyword. Aaand you plan to sell millions of it all over the world. Problem? You don't speak French. Or Chinese. Or Spanish. You could hire lots of people on mechanical turk or a similar platform. But that needs a large upfront investment. Enter Generative AI. In this video I'll show you how you can use Edge Impulse to get all the voice samples you need, train the keyword spotting model and deploy it to the extremely tiny Cortex M0+ based Arduino RP2040 Connect. Magical stuff.

This is amazing to hear! Good luck with any other project you're gonna build next!

I can recommend checking out building for more different hardware targets - there is a lot of interesting chips that can take advantage of Edge ML and are awesome to work with