Artificial Intelligence: Three Months, Six Different Facets

Since mid-December, except for the DeepSeek brouhaha AI has been relatively quiet.  There have been small expansions here and there, and sales of chips for it have stayed strong.  It has neither crapped out nor exploded.  Here are some looks at various views of it.

First, though, I address something my regular readers may have wondered about.  Why have I not been posting on the actions of the Trump administration, many important to American jobs and the American economy?  The answer is simple: they are changing too quickly.  We have gone back and forth on tariffs, job cuts, and foreign policy so swiftly that recounting those actions, and their reversals, is not suited to a weekly blog.  I sense that President Donald Trump is using them as bargaining tools more than for true policy changes, so the actions of other countries and other organizations, along with his choices of responses, will determine what will become permanent, what is temporary but briefly implemented, what is temporary without execution, and what turn out to be only threats.  For various reasons, I do not think the quantity and intensity of these edicts will continue for anywhere near a four-year presidential term, so we will be able to assess their significance, when the roller coaster slows down or stops, sooner.  In the meantime, I recommend reading the New York Times, if you want to keep track of the daily situation.

Back to the topic, the first piece here is “Business leaders commiserate over scaling roadblocks at AI Summit” (Patrick Kulp, Emerging Tech Brew, December 12^th).  You might think that a conference three months ago would be ancient AI history, but no, it doesn’t move that fast.  The “scaling” was more about selling, “failure to launch,” or a need to “fully commercialize” AI, as two conference presenters put it.  Progress can be slower than some may have thought, as well; for example, it may seem conceptually easy to book airline flights, but that “is still four or five years off.” 

“Why Does OpenAI Need So Much Money?”  This query, placed by Cade Metz on December 17^th in the New York Times, is in response to the company consuming $10 billion in the 18 months starting early 2023, and expecting to do the same with $10.6 billion ending in mid-2026.  The reasons are needing “enormous amounts of data” calling for “larger and larger amounts of computing power from giant data centers,” thereby using chips and electricity which are scarce in the quantities it requires.  And it may get even more expensive, as OpenAI “chases the dream of artificial general intelligence” (AGI), potentially “a machine that can do as much as the human brain, or more.”

Progress announced by a certain Chinese firm has not shrunk these numbers, and even if it was honestly represented, it may never, as “DeepSeek Doesn’t Scare OpenAI, Thanks to the ‘Jevons Paradox’” (Talmon Joseph Smith, The New York Times, February 14^th).  That holds “that as a resource becomes more efficient to use, demand will increase.”  It dates from 1865, when it applied to coal, and has a “decent track record” since then.  As we will see, not all pressures on AI are pushing it up, but this one has real potential to do that.

What does it mean when the “Microsoft CEO Admits That AI Is Generating Basically No Value” (Victor Tangermann, Futurism, February 22^nd)?  The executive, Satya Nadella, “has had it with the constant hype surrounding AI,” and, per the author, “argued that we should be looking at whether AI is generating real-world value instead of mindlessly running after fantastical ideas like AGI.”  The CEO also asked that “when we say this is like the Industrial Revolution, let’s have that Industrial Revolution type of growth.”  As “OpenAI’s top AI agent… still moves at a snail’s pace and requires constant supervision,” Nadella’s statement “could be seen as a way for Microsoft to temper some sky-high expectations.”  Yet he, himself, agreed during the previous month to invest $80 billion in the Stargate industry project.  So maybe, as bizarre as that sounds, it doesn’t mean much at all.

Per a Goldman Sachs-connected survey, “A majority of small businesses are using artificial intelligence” (Kennedy Hayes, Fox Business, February 27^th).  The majority found was 69%, and most found it was saving both time and money.  I do not know the minimum size of these ventures. 

Yet one business application has its enemies, as shown in “Interviewing on AI:  Tech companies love AI.  Just don’t try it to use it to get a job at one” (Dan DeFrancesco, Business Insider, February 28^th).  Amazon has been whining that “AI tools give candidates an “unfair advantage,” and that it doesn’t allow Amazon to evaluate their “authentic” skills, according to “guidelines” given to its internal recruiters.  Too bad, so sad.  Sorry if that is harsh, but companies, especially those of Amazon’s caliber, use plenty of proprietary technological methods to assess, consider, and reject candidates.  Fair is fair for jobseekers to use software of their own.  More power to them – and more power to everyone understanding, comprehending, and assessing the true merits of artificial intelligence.