One of several large concerns about AI is getting enough resources for it, namely electricity and data center capacity. Here’s a fast look at seven articles showing it can’t make it on what’s out there now.
“How Amazon
goes nuclear” (Dan DeFrancesco, Business Insider, October 25th)
started with “What’s bigger than tech’s ambitious plans for generative AI? The amount of energy needed to power
it.” It may call for a large,
controversial source, as “Amazon has led a $500 million financing round for a
company developing modular nuclear reactors.”
Google has started similar endeavors, and “should these data center
efforts continue to struggle, companies’ big bets on generative AI could also
falter.”
Otherwise,
“AI’s leaders puzzle over energy question” (Marissa Newman, Bloomberg Tech
Daily, October 30th).
That puzzling, happening at Dubai’s Future Investment Initiative which
was “mostly centered on AI,” included how to deal with a possible 40%
next-decade rise in electricity use – not that much more for AI, but overall. The Saudi Arabian Oil Company’s CEO “made his
pitch” on data centers there using natural gas at relatively low cost. Others saw merit.
Stateside,
“Exxon Plans to Sell Electricity to Data Centers” (Rebecca F. Elliott, The
New York Times, December 11th).
That will also be powered by natural gas, generated at a large power
plant, possibly completed by late 2029, of undisclosed cost and location, and
will be a new line of external business for ExxonMobil.
With these
new facilities, it is fair to consider “How A.I. Could Reshape the Economic
Geography of America” (Steve Lohr, The New York Times, December 26th). Cities “well positioned to use A.I. to become
more productive” include “Chattanooga and other once-struggling cities in the
Midwest, Mid-Atlantic and South,” such as Dayton, Scranton, Savannah, and
Greenville, each of which has “an educated work force, affordable housing and
workers who are mostly in occupations and industries less likely to be replaced
or disrupted by A.I.” A variety of other
businesses, many connected with trucking and freight, stand to benefit.
What is “The
19th-Century Technology That Threatens A.I.” (Azeem Azhar, still The
New York Times, December 28th)?
It’s electricity, on which “America has a long way to go.” In Virginia, “a hotbed for data centers,”
those wanting “to connect to the grid” could face a seven-year wait, and “some
counties in the state are introducing limits” on them. Our country, per the author, has “a patchwork
of conflicting regulations, outdated structures and misaligned investment
incentives” slowing or stopping infrastructure building, along with “a skills
gap in labor shortages in construction and engineering, a complex permitting
process trapping projects in years of bureaucratic review across multiple
agencies,” “high costs of capital,” and “local opposition.” Overall, per Azhar, “if the United States
truly wants to secure its leadership in A.I., it must equally invest in the
energy systems that power it.”
In answer to
a question arising naturally from the first source above, Bradley Hoppenstein,
writing in CNBC, told us “Why tech giants such as Microsoft, Amazon,
Google and Meta are betting big on nuclear power” (December 28th). It’s because of “the energy demands of their
data centers and AI models” that “nuclear power has a lot of benefits,”
including having no carbon, its providing “tremendous economic impact,” and
“can be always on and run all the time.”
However, we haven’t seen anywhere near as much opposition from
anti-nuclear groups as we probably will.
On the front
page of Sunday, December 29th’s New York Times business
section was “Data Centers Are Fueling a New Gold Rush” (Karen Weise). They named installations being built in less
populated areas of Washington state, resulting in “electricians flocking to
regions around the country that, at least for now, have power to spare” and “a
housing crunch” almost certain to create more jobs.
The
electricians in Washington were matter-of-fact about the boom not lasting
forever. When work runs out there, they
hope to find it elsewhere, and probably will, even in the same industry. No matter what happens in the long run with
artificial intelligence, it is building economies now. Don’t expect that to stop this year – or the
next.