Edge computing

yeah yeah and somehow this makes apple more valuable

um Hey, the two edge computing plays I mentioned that are kind of the obvious ones being Apple and then Qualcomm, they are both green.

So maybe our little Qualcomm position here will be like our mini Apple where it goes up when this other stuff goes down.

It's like a barbell, a tech barbell where one goes up, one goes down.

But you also have this tiny little data center that everyone just hones in on that becomes where all your compute gets processed.

Now, that may be 40 years from now.

So if that happens, Qualcomm is equipped to do well on device and edge computing.

It would.

I've closely followed Infineon for years.

It is one of the premier technology ingredient companies, supplying the essential components that help enable AI data centers, automotive systems, the Internet of Things, edge computing, and much more.

This year marked the 10th anniversary of OktoberTech Silicon Valley.

The event brought customers, partners, and innovators together to discuss AI, power, mobility, security, and the next generation of intelligent devices.

For Infineon, the opportunity is to help customers build the electronic foundation for that transition.

Not every AI task needs to travel to a distant data center.

At October Tech, speakers highlighted the growing importance of edge computing, where devices process information closer to where it is generated.

That can support faster responses and, in some applications, reduce the need to send sensitive information to the cloud.

So it can run on enterprise, it can be hosted in a telco building, or it can be on the device itself.

Now, the interesting thing about edge computing is that for me, if you think about the matrix, Everyone inside the matrix is potentially an agent, and you can apply the same thought about edge computing.

Everything is potentially an edge computing node.

Everything from your phone to the, again, tower, to whatever you want, could potentially become a source of edge computing.

Now, the question, of course, that a lot of people are asking is who owns this edge computing thing? So we know that telcos have built physical infrastructure to connect people.

And we also know that sometimes they have separated some of that infrastructure.

And that was, you know, due, as we saw in the latest podcast, to reduce debt, you know, attract investors, so on and so forth.

But maybe, again, because of AI, this whole conversation like where is the edge, who owns the edge, is becoming relevant again.

But these two kind of product sets, being product recognition and loss prevention, are quite commonly cited in this day and age.

You can walk around an NRF trade show floor or indeed any conference and you might hear quite a few AI companies speaking to a similar tune.

And so really the key innovation for us and how we differ to the rest of the market is our approach.

And the clue really is in the name, the Edge and Edgeify.

And so How we think through AI is our general modus operandum is these in-store environments have devices such as the Zebra devices that already have sufficient compute on board for us to be able to actually run our software layer, the AI layer, directly on that device.

And so that device could be a point of sale terminal, either a self-checkout or a lane pause.

It could be actually on the barcode scanner itself, like a Zebra MP scanner, or indeed a mobile device.

very quickly um to that variance so there's a way to fast track this supplement what we already know and what we've learned and adjust the model in the inventory accordingly i i love that

Well, especially in, you know, I hate, you know, Stuart, everyone's talking about it and it's artificial, it's artificial intelligence.

And, you know, once we start getting into metadata, now we've got this element of enterprise AI or OT AI, or, you know, where people want to stream, sometimes they're streaming, but data, sometimes when you're doing, let's say, compute, or you're doing inference, you're going to do this at the edge.

Yep.

And so walk me through in, you know, where you're seeing video soft work with AI readiness or artificial intelligence at the edge.

Yeah, you've got a good point there.

So VideoSoft's next phase of development is bringing in AI to make, to automate and make more efficient, even more efficient the product, right? But the key thing there is off-the-shelf AI does not always address the unique requirements of the use case of the customer that wants to use it.

Therefore, our strategy our philosophy is we work together with our partners to extend the solution to fix those problems specifically using the ai kind of engines and routines

yeah

And I think the state is really giving it a very, it seems like the state's giving it a very strong thought process and being very diligent and tactical.

But that sector that you highlighted is critical for edge computing in these many data centers.

Very important.

Interesting.

You really do.

Today, our mission is to unpack exactly how 6G, artificial intelligence and edge computing are rapidly turning those static passive poles into, you know, highly intelligent localized data centers.

Yeah, that's the perfect way to describe it.

And more importantly, we want to help you understand how this technological leap fundamentally changes the value of your lease.

Got it.

What's fascinating here is how the industry is solving that exact physics problem.

They're relying on the concept of edge computing.

Okay.