It May be Time to Stop and Take an AI Breather
Brie Clayton May 19, 2026
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If the rock you stay on starts to roll, jump clean. Or you'll go with it and be squashed. Only a fool stays aboard. Kyoami, Ran , Kurosawa Productions, 1985
O.K., we get it.
We need AI to solve really complex problems like curing diseases, improving the quality of life for 20 percent of the people around the world living in extreme poverty (less than $2 a day), feeding 2.3B people facing moderate/severe food insecurity, stemming/reversing global climate change (even if you think it's BS), figuring out how support/deal with 1.5B people 65 by 2050 and eliminating the possibility of another pandemic.
A few folks are using it today to address these problems however, most of its use is directed at doing your work so you don't have to and enabling your boss to reduce his/her headcount, making cute/insulting pictures and stealing stuff from other people.
Damn, in addition to being so cool, so cute and so beneficial, AI promises to have so much potential for everyone.
The AI techies say all we have to do is keep giving it more and more data, sit back and relax and life will be good great.
Well, they also need more than just data.
A big data center hosts 10K to 100K servers housing millions of GPUs.
More, Bigger - AI GPUs may be small, but AI data centers are big and require a lot of resources - water and power - to keep them running at peak performance. And every country/company wants to lead the parade.
Ramping Up - All of the usual cloud and data collectors - Google, Meta, Oracle, Amazon, Tencent, Baidu and Microsoft - are busy investing in bigger, better, faster AI0 data centers. Emerging hypercenter firms are adding large facilities to keep pace with AI demand.
Actually, they're referred to as hyperscale data centers designed from the ground up to handle the growing AI workload.
No, they aren't your hole-in-the-wall data centers, we're talking big we mean really big!
Expansion - Even before an AI data center is completed the company is busy planning for the next great phase of their processing capabilities. Texas may be short on a few things like water, electricity but it's big on what hyperscale AI facilities need - land - but it's not alone. States and countries everywhere are making room for newer, bigger, badder AI centers like Meta's Hyperion facility.
Source - Storage Newsletter
They need AI data centers big data centers and lots of them, everywhere.
The global AI data center market is expected to grow from $18B last year to $94B by 2032.
That kind of growth brings tears to Jensen Huang's eyes (Nvidia CEO). He saw the value of his GPU company surpass $5T because his chips (and a few other players around the globe) are at the very heart of AI.
A big data center hosts 10K to 100K servers housing millions of GPUs.
Overwhelming - Ever since the early 1940s when the first electronic computer appeared on the screen the systems have gotten faster, more reliable in processing/crunching data. AI made it easier and faster to crunch/process more data to produce even more data.
Don't worry, that won't happen because the data centers are designed to quickly and accurately handle anything you can throw at them and keep consuming, processing, digesting and delivering/storing all that data, no matter how brilliant or dumb it is they don't judge.
Every day more than 2.5 quintillion bytes of data are created. That figure rose to more than 463 EB last year (1 quintillion bytes equals 1EB, 1000EB equals 1ZB).
That includes your streaming entertainment, emails, documents, social media (written, video) posts, gaming, web browsing, synthetic content and file sharing-anything/everything digital.
Of course, to slice/dice/move all that data around those data centers require power.
Yeah, you have to share your home/office power with those power-hungry data centers.
The small data center your organization has tucked into the corner of the building (5,000-20,000 sq ft) only requires 1-5MW of power while your home only uses about 30 kWh a day.
Source - IE
Cascading Effect - As AI permeates every corner of business and our lives it continues to tap, use and produce more data while constantly sucking up more resources to keep itself going and growing.
Of course, that didn't take into consideration the hellacious amount of power AI data centers require.
AI-heavy racks require 30-50 kW per rack with today's Nvidia GPUs consuming 1,200W and Nvidia's next-generation AI chips will need up to 15,000W each.
By 2030, the world's data centers will be consuming about 220-327GW.
More, Bigger - AI GPUs may be small, but AI data centers are big and require a lot of resources - water and power - to keep them running at peak performance. And every country/company wants to lead the parade.
Yes, that's a little more power than 225M homes require; but what's a little brownout or blackout now and then as long as your videos and hallucinations entertain and inform/convince.
Slow Shift - While coal and natural gas are presently the leading sources of power generation, countries and companies are moving as rapidly as possible to replace the generation source to more environmentally friendly sources - solar, wind, hydropower and a newer, more safe nuclear approach.
Countries and companies around the world are doing their darndest to keep pace with and get ahead of the power demand.
Unfortunately, the electrical grid is a little fragile and under significant strain right now because it's old and AI data centers are pushing for more and more reliable power.
In some areas, there's a seven-year wait to get connected to the electrical grid.
But don't worry, some government officials are aggressively pushing to ha
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It May be Time to Stop and Take an AI Breather 
