Why the Cloud Is the Tip of the Iceberg
- AI grabs all the headlines, but what makes the rapid exchange of so much data possible?
- Although it isn’t a monolith, what we think of as “the cloud” is integral to rapid innovation.
- In his book “The Cloud Revolution: How the Convergence of New Technologies Will Unleash the Next Economic Boom and a Roaring 2020s,” Mark P. Mills argues that AI, among other technologies, will necessitate an even larger, more powerful cloud.
Ever since ChatGPT burst on the scene last year, pundits and prognosticators have opined about how AI will change our lives.
“It will change our lives. But it’s not going to do so in isolation,” says Mark P. Mills, the author of “The Cloud Revolution: How the Convergence of New Technologies Will Unleash the Next Economic Boom and a Roaring 2020s.”
Mark says we’re in the midst of a revolution — but not the kind of revolution we might think.
For a true revolution in terms of economic impact, he argues that we need progress in three different areas to happen at the same time: advances in our ability to gather and share information, breakthroughs in the capacity of machines and advances in the realm of materials like rare earth metals — the “physical stuff we use to make all this happen,” Mark says. “This is what we’re experiencing now.”
Mark joined host Kevin Coldiron on an Ideas Lab installment of Top Traders Unplugged to talk about the book and how cloud innovations will propel us forward in more ways than one.
“Forecasting is a tough art,” says Mark, who tends to classify forecasters in three ways: those who are paid to entertain, those who are paid to sell their book and those who are paid to be right.
As for his own book, Mark hopes it’s entertaining, but notes that his arguments are based on factual observations.
He strove to “lay out an architecture for forecasting the near future based on a truism … I stole a line from the management consultant Peter Drucker: ‘I only forecast things that have already happened.’”
In “The Cloud Revolution,” that means basing predictions on the trajectory of the industry so far, while thinking big about the impact of innovations the cloud will spark as it expands.
Bringing the cloud down to earth
We’re always hearing about “the cloud,” but how many of us really understand what it is and how it works? Kevin asks Mark to explain the cloud in physical terms.
“That’s what is fascinating and surprising to most people,” Mark replies. “No product or service exists without materials that were first mined from the earth. … But most people ignore that because it’s sort of hidden. [But] … if you’re an investor, it’s meaningful because sometimes there are new opportunities to invest and expand to new domains.”
The “cloud” as we know it is IT infrastructure. Cloud servers are located in data centers all over the world, but the information and data on these servers can be accessed from anywhere. Wireless networks are invisible, but they all depend on complex, kilowatt-consuming machines.
So how can we quantify or measure the cloud? Mark notes that if we tried to measure it in terms of distance, it would be billions of miles or meters — larger than any network humanity has ever built.
“It dwarfs the highway networks and old telephony networks by orders of magnitude,” he adds.
Quantifying the cloud
If we want to quantify the cloud in dollars, we’d begin by noting that capital spending on data centers and networks globally is now greater than capital spending on electric utility networks and production worldwide.
If we measured it in terms of square feet — most data centers are the size of a Walmart or bigger, “not filled with people or merchandise, but filled with hot silicon servers, storage devices, communications devices … just buildings full of machines,” says Mark. “The only analogous buildings, in an odd way, are skyscrapers, [which] under a single roof can house a million square feet. So can data centers.”
He points out that there are roughly 1,500 skyscrapers in the world that are at least as big as the Empire State Building, or about 1 million square feet. For comparison, there are about 5,000 data centers that large, and we’re building them at a far faster pace.
The first cloud data center came online in Santa Clara, California, in 1999 — “but the real build-out of the cloud started, give or take, in 2005,” Mark says. “That’s when the data center boom started. The kinds of features associated with your smartphone were made possible, essentially, by cloud architecture.”
The ‘end of the beginning’
Now, a decade-plus after it became commonplace, “we’re not even close to saturation in the cloud,” Mark says.
“We know this because of the velocity of the buildup underway with the conventional cloud … AI portends an even faster and more expansive buildout of the cloud, because of the physical nature of the machines needed to instantiate what we call artificial intelligence [or] machine learning.”
Mark says as AI evolves, it will essentially require building more complex and much larger infrastructure — which will inevitably take place in the cloud.
“We’re at the end of the beginning, not the beginning of the end of the build-out of the cloud,” he adds.
And it’s already happening: Amazon, Hewlett Packard, Google and Meta have all announced either “a pause, or a redirection and expansion, of cloud spending,” he explains. That’s because companies like these need to refocus their efforts on growing AI.
“Machine learning … requires incredible computational horsepower. It’s the most energy-intensive and most silicon-intensive use of computing, period, full stop. It’s orders of magnitude more power and logic-intense than traditional computation,” Mark explains.
Machines need to process billions upon billions of data points, which requires easily accessible supercomputers networked to the cloud. They have to be easily upgradeable, as well.
“The pace of change is so fast that cloud providers … [are] continually upgrading the hardware to bring you next-generation capabilities. [As a result,] the footprint of power and machinery … [and] the demands are now merging in all the applications people are imagining.”
AOL and AI
As the gap between the pace of innovation and computing power begins to close, Mark says we will see explosive growth in everything from medicine to manufacturing.
Industries of all kinds are experimenting with AI to save labor and time on routine tasks. But Mark thinks it will take another year or so for people to get up to speed with what tools like ChatGPT can do. “Then they’ll want that service,” he says. “And they’re not going to get that service by and large anywhere except for the cloud. That’s a step … as big as the advent of the cloud, or as big as the advent of the internet.”
He makes an analogy: Our current cultural fascination with AI is comparable to the public’s reaction to email and instant messaging in the era of “You’ve Got Mail.” He points out that in the early days of AOL, the media wrote about the power of the internet in rapturous wonder. But in hindsight, just 20-ish years later, we see that AOL’s offerings were rudimentary at best.
Now, we're just entering an era of “explosive growth” in AI and cloud computing. Whether or not stock prices properly reflect growth — or if we run the risk of repeating the 1999 dot-com bubble — “the enthusiasm is properly placed,” Mark says. “Because it is a big deal. And the structural change is accelerating.”
This is based on an episode of Top Traders Unplugged, a bi-weekly podcast with the most interesting and experienced investors, economists, traders and thought leaders in the world. Sign up to our Newsletter or Subscribe on your preferred podcast platform so that you don’t miss out on future episodes.
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