Pushing the most expensive electricity that there is

I personally suspect, and hope, that before much longer researchers will figure out how to run tech on considerably less electricity. And/or AI development will hit a wall.

New York Governor Kathy Hochul’s desire to build 5GW of new nuclear power in order to keep New York’s electric bills affordable and meet future energy demand has one pesky problem: the numbers simply don’t add up. That’s the overarching conclusion of a new report authored by the University of Pennsylvania’s Dr. Joseph Romm, which was presented in New York last week…

There are a myriad of possible reasons why both politicians believe new nuclear generation is a viable option moving forward, but it’s clear neither are paying attention to what just happened in Georgia – when two incumbent Republican Public Service Commission (PSC) members were removed from office by voters following massive increases in consumer electric bills. To be fair, neither Hochul nor Trump will be around to face the music if their plans are realized and New York starts the decades-long process to build 5GW worth of the world’s most expensive source of energy. - Beyond Nuclear

The bottom line regarding the AI market panic

This summarizes, very well, a lot of things.

Now that a company has figured out a way to produce an AI app that’s just as effective at producing satisfactory output as the big American companies, at a sliver of the cost, a $500 billion data center facility in the desert suddenly seems like an offensive boondoggle…

It’s worth underlining a couple things here. First, generative AI long seemed destined to become a commodity; that ChatGPT can be so suddenly supplanted with a big news cycle about a competitor, and one that’s open source no less, suggests that this moment may have arrived faster than some anticipated. OpenAI is currently selling its most advanced model for $200 a month; if DeepSeek’s cost savings carry over on other models, and you can train an equally powerful model at 1/50th of the cost, it’s hard to imagine many folks paying such rates for long, or for this to ever be a significant revenue stream for the major AI companies. Since DeepSeek is open source, it’s only a matter of time before other AI companies release cheap and efficient versions of AI that’s good enough for most consumers, too, theoretically giving rise to a glut of cheap and plentiful AI—and boxing out those who have counted on charging for such services.

Second, this recent semi-hysterical build out of energy infrastructure for AI will also likely soon halt; there will be no need to open any additional Three Mile Island nuclear plants for AI capacity, if good-enough AI can be trained more efficiently. This too, to me, seemed likely to happen as generative AI was commoditized, since it was always somewhat absurd to have five different giant tech companies using insane amounts of resources to train basically the same models to build basically the same products.

What we’re seeing today can also be seen as, maybe, the beginning of the deflating of the AI bubble, which I have long thought to only be a matter of time, given all of the above, and the relative unprofitability of most of the industry. - Blood in the Machine

Relying on AI in healthcare invites disaster

More totally irresponsible, and dangerous, crap from the tech greedheads.

Every so often these days, a study comes out proclaiming that AI is better at diagnosing health problems than a human doctor. These studies are enticing because the healthcare system in America is woefully broken and everyone is searching for solutions. AI presents a potential opportunity to make doctors more efficient by doing a lot of administrative busywork for them and by doing so, giving them time to see more patients and therefore drive down the ultimate cost of care. There is also the possibility that real-time translation would help non-English speakers gain improved access. For tech companies, the opportunity to serve the healthcare industry could be quite lucrative.

In practice, however, it seems that we are not close to replacing doctors with artificial intelligence, or even really augmenting them. The Washington Post spoke with multiple experts including physicians to see how early tests of AI are going, and the results were not assuring...

The problem with tech optimists pushing AI into fields like healthcare is that it is not the same as making consumer software. We already know that Microsoft’s Copilot 365 assistant has bugs, but a small mistake in your PowerPoint presentation is not a big deal. Making mistakes in healthcare can kill people. Daneshjou told the Post she red-teamed ChatGPT with 80 others, including both computer scientists and physicians posing medical questions to ChatGPT, and found it offered dangerous responses twenty percent of the time. “Twenty percent problematic responses is not, to me, good enough for actual daily use in the health care system,” she said. - Gizmodo

Big Finance is having its doubts about AI

For me the noteworthy thing is that even Wall Street, which is generally pretty gullible about The Next Big Thing, is displaying at least a measure of rational skepticism about artificial "intelligence."

For tech’s biggest players, this earnings season is starting to feel like a scene from the movie Jerry Maguire— and the “show me the money” demands aren’t working out any better than they did for Tom Cruise. Some analysts are even dubbing this the “show me the money” quarter, as Wall Street’s patience with massive AI spending begins to wear thin...

Almost two years after ChatGPT kicked off Silicon Valley’s AI gold rush, this week’s tech earnings revealed both the promise and the staggering price tag of the AI revolution. While companies reported significant gains from AI initiatives —Meta’s ad prices up 11%, Google Cloud revenue surging 35% to $11.4 billion, Amazon’s AWS growing 19% to $27.5 billion — their warnings about future spending sparked a broad market retreat…

Tech executives’ unwavering faith in AI’s potential stands in stark contrast to investors’ growing anxiety about the costs. - Quartz

Tech bros hype military AI

That anyone regards this with terminology like "promise" and "game-changing" is despicable.

Since the emergence of generative artificial intelligence, scholars have speculated about the technology’s implications for the character, if not nature, of war. The promise of AI on battlefields and in war rooms has beguiled scholars. They characterize AI as “game-changing,” “revolutionary,” and “perilous,” especially given the potential of great power war involving the United States and China or Russia...

While experts caution that militaries are confronting a “eureka” or “Oppenheimer” moment, harkening back to the development of the atomic bomb during World War II, this characterization distorts the merits and limits of AI for warfighting. It encourages policymakers and defense officials to follow what can be called a “primrose path of AI-enabled warfare,” which is codified in the US military’s “third offset” strategy. This vision of AI-enabled warfare is fueled by gross prognostications and over-determination of emerging capabilities enhanced with some form of AI, rather than rigorous empirical analysis of its implications across all (tactical, operational, and strategic) levels of war.

The current debate on military AI is largely driven by “tech bros” and other entrepreneurs who stand to profit immensely from militaries’ uptake of AI-enabled capabilities. - Bulletin of the Atomic Scientists

Will AI create or destroy jobs?

Heck if I know. I consider it impossible to predict with any confidence, at this time. This is from another take on the matter.

A new study by the International Labour Organization (ILO) has concluded that Generative Artificial Intelligence (AI) is more likely to increase jobs than destroy them by automating some tasks rather than taking them over entirely...

The study, “Generative AI and Jobs”, argues that most jobs and industries are only partially exposed to automation and are more likely to be complemented than replaced by the latest wave of generative AI, such as chatGPT.

Therefore, he argues that “the biggest impact of this technology is likely to be not job destruction, but rather potential changes in the quality of jobs, in particular work intensity and autonomy”...

The study, released by the ILO from its headquarters in this Swiss city, documents notable differences in the effects on countries at different levels of development, linked to economic structures and existing technology gaps. - Pressenza

Artificial intelligence and getting public benefits

I’m still an AI skeptic, at least of many of the claims that are out there. Remember how the internet itself was going to totally remake our lives, like “paperless offices,” the total end of traditional retailing, etc., etc? (Though certainly some people made a great deal of money from pronouncements like that being taken very seriously. Other people lost a great deal of money, too.) We will have to deal with AI, of sorts, in some ways, though.

One critical area that will almost certainly see dramatic changes in the years ahead is that of accessing public benefits programs — a realm already fraught with systemic barriers. While AI brings great potential to streamline burdensome processes and expand access to critical services, it also poses significant risks if deployed without care. As we stand at the precipice of an AI revolution, it’s critical that policymakers, tech companies and advocates work collectively to steer these technologies towards empowering people in need, rather than further isolating them. The promise is real, but far from guaranteed.

These developments come at a moment of growing recognition of how critical a robust, accessible safety net is to building and maintaining a prosperous society. Analysis on the expansion of the child tax credit during the Covid-19 pandemic found that increasing the benefit amount and making it available to more people lifted 3.7 million children out of poverty. In contrast, the addition of work requirements to enroll in the Supplemental Nutrition Assistance Program (SNAP, formerly known as food stamps), as proposed by Congressional Republicans early this year, would have reduced enrollment by an estimated 52% if it had been enacted, by making it more difficult for families in need to access the benefits. Given that SNAP is credited with keeping 3.3 million children out of poverty every year, this change would have drastically increased the number of children in poverty. These outcomes have major ramifications, not just for the families involved, but for society at large, as the long-term impact of child poverty has been calculated to cost more than $1 trillion every year. - In These Times