AI at the Edge: The Expanding AI Ecosystem in 2025 – Predict 2025

Hi, I am Olivia Blanchard. I am the research director and practice lead for AI devices automotive and AI device semiconductors at the RUM Research Group. And so what we're thinking here in, in our holistic practice, looking at all of our dif different technology categories is that AI devices is actually taking off this year.

Uh, and it's, it's probably going to be one of the bigger trends in, uh, in the overall tech sector. Up until now, we've had AI living in the cloud, in, in terms of training inferencing services. Most of it has been handled in the cloud through data centers and cloud services.

But what we're doing this year, or what we're seeing this year rather, is a, a migration, not away from the cloud, but into devices towards the edge. So essentially it's an expansion of, uh, of the AI ecosystem from the cloud outward to the edge to devices, and these devices are IPCs. That's obviously one of the big, uh, developments for this year.

I'll come back to it in a second. Another one is, uh, AI enabled mogul devices, which actually is new, but we're going to start seeing a lot more on device agentic AI entering the market this year. And also all of the other devices that are sort of peripherals to, uh, PCs and mobile.

So that's the wearables like your watches and xr. So smart glasses. It's also drones.

It's also smart cameras, smart speakers, all of the, the, the little ecosystem of, of intelligent devices that you can interface with, either by voice or, or other types of, uh, of interfaces. And we're also seeing an expansion of that into the automotive space where cars aren't just about self-driving and a DAS, they're also about ag agentic experiences inside the vehicle for the drivers and passengers. So all of these things together are essentially driven by advancements in two areas.

One is, uh, semiconductors. So the small semiconductors, the semiconductors that go into your devices, your PCs, your mobile phones, your watches, your smart glasses, your speakers, your, all of your wearables. And the vehicles are getting much better.

Uh, a lot of them are equipped with, uh, something called an NPU, which is a neural processing engine or unit that allows AI workloads to happen on device. And increasingly what we're seeing is not just inference, which is sort of the AI interacting with you on devices, it's also the training itself. And, and we're, we're now able with IPC's mobile devices and, and, and vehicles to train AI directly on the device without necessarily needing a, um, a cloud connection or connection to the cloud or, or to a data center.

So that's, that's a huge thing because it allows training of AI to be remain local, to be secure and to be a little bit more immediate. And that's also with the inferencing, which is kind of the interactions that we have with ai. AI models are becoming a lot more efficient to train.

And so what used to have to be trained in the cloud a year ago that required, you know, 70, a hundred billion parameters can now is, is much smaller now and can run directly on devices or can be trained directly on the device. So we're gonna see an expansion of training AI models from the cloud into smaller solutions like small servers, more local, and also some of that training being, uh, being moved to AI devices. All of that and more, uh, can be found in our ebook about our predictions for 2025.

Uh, we're talking about not just AI devices, but a lot of other technology categories as well. That'll play into this big AI revolution that we have. Also, I recommend that you follow us on the socials.

So we're on LinkedIn, obviously, uh, we're on X anywhere. You can find us, uh, anywhere. You can find me where I talk about AI devices, and also follow us on our websites where you'll find a lot of other resources.

com. Thanks a lot. Happy reading, and I hope to see you at.