Chapter 1: What is the focus of the AI infrastructure series?
A one-week special series on AI infrastructure. From American Public Media, this is Marketplace Tech. I'm Megan McCarty Carino. A couple weeks ago, I walked through an office building in Cupertino, California, into an industrial-looking room with exposed pipes and a concrete floor.
So this is our networking hardware lab here in AWS.
Satish Vangala is the director of network product development at Amazon Web Services.
Network is almost like a data highway or information highway. You have these massive AI clusters of graphics or CPUs that are there. They all exchange information.
And just like interstates and highways, if you don't have the right infrastructure, you can end up with pretty bad bottlenecks, right?
I think that's the whole point of what we do here is to ensure that your experience feels instant. That means that we need to have a network that has no traffic jams or no delays.
As we've talked about, spending on AI has gotten so big that it's outpacing consumer spending as a driver of GDP. And today, we're going to look at one tiny innovation, one of thousands being made in the effort to build out that infrastructure. It's literally humming in this lab.
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Chapter 2: How does AWS ensure efficient networking for AI?
What's going on in here?
So I'll walk you through some of the things that we do here, and then we can kind of go through some of the stations, and I'll explain you in detail.
All right, let's go. There were wires everywhere. Workers in jeans and T-shirts hovered over screens filled with code.
This is our 800-gig generation product, so that means we have more lanes for data exchange. In one room on a wall of computer servers... These are typically what you would see in a data center.
Satish pulled out a rack of little yellow plugs. Kind of like the Ethernet cables you might stick into your home computer. AWS has built about 9 million kilometers of fiber cable to link computers around the world. It's enough to stretch to the moon and back 11 times. And it's all connected with fiddly little plugs like these.
Plugging in these many connections, like these are 60, 32 ports, it's slowing us down.
So the ergonomics of actually plugging those individually.
Individually, it takes a lot of time and doing it reliably is also a challenge.
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Chapter 3: What innovations are being developed at the AWS lab?
So what we have done here is that we kind of looked into this problem and how we could actually miniaturize it so that we can actually reduce it. So these are 64 fibers that we connected and here we got a single connector that actually can do exactly the same thing that we are doing in a smaller form factor here. So that enables us to reduce our deployment time by more than 50%.
Those little innovations, like a cable that's easier to plug in, might seem small, but that's the infrastructure required to make almost $2 trillion of AI investment pay off. We'll be right back. This is Marketplace Tech. I'm Megan McCarty Carino. Inside, a research and development lab of Amazon Web Services that is working on new technology for the AI infrastructure build-out.
Satish Vangala, Director of Network Product Development, showed me these devices, they're called transponders, that convert electric signals, aka data, into light waves.
and then the light gets sent over a fiber optic cable to any distance you want, and that's the information highway that connects across.
They look a little bit like nail clippers.
Yeah, they look like nail clippers, yes.
I mean, when we were looking at, you know, just the little sockets and how you're engineering all of this stuff, it just really calls to mind how the infrastructure build-out, it's all these little pieces that have to come together to make it work. What are the challenges on your side, on the networking side, to meeting that demand?
I think meeting that demand, that's the first goal that we have.
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Chapter 4: How does AWS address the challenges of scaling AI infrastructure?
Second, as I said, how do we scale faster? And that's where we are innovating in that process as well. And then finally, we are looking at building our systems, resilient systems, so that when we do deploy them at scale, we are able to operate our network at a very high reliability.
So those are the main three challenges that we are really looking at so that we can deliver capacity at scale at very fast pace.
Chapter 5: What are the future implications of AI infrastructure investments?
And that means that we need to make sure that all the components that are used to build the network are ready and are able to deploy at scale.
On the program tomorrow... I understand this is actually a data center.
Yes, you wouldn't believe it walking by. And it has a very interesting story, how we shape the internet today.
We're going back in time. Maria Hollenhorst and Daniel Shin produced this episode. I'm Megan McCarty Carino, and that's Marketplace Tech. This is APM.
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Chapter 6: What role do transponders play in the AI information highway?
I'm Kathy Worzer, and in this new season, I sit down with researchers, doctors, and industry experts who are leading the way in medical innovation. From cutting-edge technology to breakthrough treatments, we'll explore how new solutions are improving and even saving lives. Follow Tomorrow's Cure wherever you listen to podcasts.