"Nvidia (NVDA) Q1 2027 Earnings Transcript" May 20, 2026

After closing up $2.86 (+1.30%) to $223.47 during the regular session the stock reversed after the earnings release and conference call,  $221.38 last I saw, down $2.09.

From Motley Fool Transcribing, May 20:

CALL PARTICIPANTS

• President and Chief Executive Officer — Jen-Hsun Huang
• Executive Vice President and Chief Financial Officer — Colette Kress
• Vice President of Investor Relations — Toshiya Hari

TAKEAWAYS

• Total Revenue -- $82 billion, up 85% year over year and 20% sequentially, marking the third consecutive year-over-year acceleration and fourteenth straight quarter of sequential growth.
• Sequential Revenue Increase -- $13.5 billion sequential increase, a new company record.
• Shareholder Returns -- $20 billion returned through capital allocation, including share repurchases.
• Data Center Revenue -- $75 billion, up 92% year over year and 21% sequentially, driven by Blackwell architecture demand.
• Data Center Computing Revenue -- $60 billion, up 77% year over year.
• Data Center Networking Revenue -- $15 billion, nearly tripled year over year.
• Hyperscale Subsegment Revenue -- $38 billion, ~50% of data center revenue, up 12% sequentially.
• ACIE Subsegment Revenue -- $37 billion, up 31% sequentially, with AI cloud revenue more than tripling year over year.
• Partner Data Centers Over 10MW -- Number nearly doubled in 1 year, now above 80 sites.
• Sovereign Revenue -- Grew more than 80% year over year, with infrastructure deployed in nearly 40 countries.
• AI Infrastructure Pricing -- H100 rental prices increased 20% year to date; A100 cloud pricing up nearly 15%.
• InfiniBand Revenue -- More than quadrupled year over year, bolstered by next-generation XDR deployments.
• Grace Blackwell Throughput -- Blackwell Ultra delivered a 2.7x throughput boost and 60% reduction in cost-per-token on GV300, comparing the last 6 months.
• Vera CPU Platform -- Anticipated $20 billion in standalone CPU revenue for the year, opening a $200 billion market opportunity.
• Production Shipments of VeraRubin -- Set to begin in Q3, with ramp continuing into the following quarters.
• Edge Computing Revenue -- $6.4 billion, up 10% sequentially and 29% year over year; Blackwell workstation demand notable while consumer demand softened due to higher memory and system costs.
• Physical AI Revenue -- Surpassed $9 billion over the trailing 12 months.
• Supply Commitments -- Total supply, including inventory purchase commitments and prepaids, increased to $145 billion.
• GAAP Gross Margin -- 74.9% (non-GAAP 75%), with margins largely flat sequentially as Blackwell accounted for most shipments.
• Operating Expenses -- GAAP and non-GAAP OpEx up 12% sequentially; driven by compensation and higher compute/infrastructure costs.
• Free Cash Flow -- Generated $49 billion, up from $35 billion in the prior quarter.
• Dividend Increase -- Quarterly dividend raised from $0.01 to $0.25 per share.
• Share Repurchase Authorization -- Announced $80 billion new buyback program, in addition to $39 billion left on current plan.
• Q2 Revenue Outlook -- Expected $91 billion, plus or minus 2%, with growth led by data center.
• Q2 Gross Margin Guidance -- 74.9% GAAP, 75% non-GAAP, both plus or minus 50 basis points.
• Q2 OpEx Guidance -- Approximately $8.5 billion (GAAP) and $8.3 billion (non-GAAP).
• Full Year OpEx Growth -- Expected to increase in the upper 40% range, attributed to higher R&D and AI productivity tool usage.
• Full Year Tax Rate Outlook -- 16%-18% for GAAP and non-GAAP, down from previous 17%-19% guidance due to geographic mix changes.
• China Data Center Revenue -- No China compute revenue included in outlook, as no H200 shipments have yet occurred or are anticipated under current circumstances.

SUMMARY

NVIDIA (NVDA +1.22%) reported record-breaking figures across revenue, data center and free cash flow, driven by exceptional Blackwell architecture adoption and increased demand for advanced AI infrastructure from a variety of customer segments. The company re-segmented its data center business into Hyperscale and ACIE to better align with evolving market demand, while emphasizing the rapid scale-up of sovereign AI deployment and agentic AI as the next frontier. NVIDIA introduced Vera as its first purpose-built CPU for agentic AI, unlocked a $200 billion total addressable market for CPUs, and expects significant revenue accretion as customers transition compute platforms. Management provided guidance for the following quarter reflecting continued double-digit sequential growth and reinforced capital returns with a substantial boost to both dividends and share repurchase plans.

• Management stated, “Demand has gone parabolic. The reason is simple. Agentic AI has arrived. AI can now do productive and valuable work. Tokens are now profitable, so model makers are in a race to produce more.”
• CEO Jen-Hsun Huang explained the new business segmentation aims to capture the distinct needs and go-to-market dynamics of Hyperscale, ACIE, and Edge platforms to give investors clearer visibility into growth drivers.
• The number of partner data centers exceeding 10MW nearly doubled in one year, an explicit indicator of the infrastructure scale-up supporting NVIDIA’s growth.
• Vera and VeraRubin are positioned as catalyst products for agentic AI, with shipments scheduled to ramp starting in Q3 and a focus on both standalone and system-integrated use cases.
• Management commented that LPX and similar SRAM-based accelerators are expected to remain niche, reaffirming Blackwell and Vera platforms as central to the company’s growth strategy.
• NVIDIA explicitly excluded China data center compute revenue from its outlook, reflecting caution amid continued export licensing uncertainty for H200 shipments to mainland customers.

INDUSTRY GLOSSARY

• Blackwell architecture: NVIDIA’s latest GPU platform, purpose-built for AI, designed for high throughput and low token cost at inference, deployed across hyperscale and frontier AI use cases.
• Vera/VeraRubin: NVIDIA’s custom CPU product and its paired platform, designed specifically for agentic AI workloads; enables new system architectures aiming at high performance and energy efficiency.
• ACIE: Stands for AI Cloud, Industrial, and Enterprise—a newly defined NVIDIA data center subsegment capturing AI-specialized, non-hyperscale deployments including sovereign, industrial, and regional AI infrastructure.
• Spectrum-X: End-to-end Ethernet networking platform from NVIDIA, positioned for AI data center workloads and cited as surpassing all peers’ combined Ethernet deployment scale.
• LPX: NVIDIA’s SRAM-based AI accelerator product line, designed for high token rate and low latency use cases, with limited throughput and context processing capacity.
• Token: The unit of output/inference in AI models, used as a metric for compute efficiency and economic return in NVIDIA’s reporting and performance claims.
• Agentic AI: AI systems capable of autonomous, goal-driven action and orchestration across multiple tasks, cited by NVIDIA as the core driver for its next growth phase and platform innovation.
• Hyperscale: The segment of cloud service providers and consumer internet companies operating massive-scale data centers, as defined in NVIDIA’s new reporting framework.
• Frontier AI: Refers to the most advanced, cutting-edge AI models and the organizations building them, including but not limited to OpenAI, Anthropic, and others mentioned as key NVIDIA customers.

Full Conference Call Transcript

Toshiya Hari: Thank you, and good afternoon, everyone. Welcome to NVIDIA's conference call for the 2027. With me today from NVIDIA are Jensen Huang, president and chief executive officer and Colette Kress, executive vice president and chief financial officer. Our call is being webcast live on NVIDIA's investor relations website. The webcast will be available for replay until the conference call to discuss our financial results for the 2027. The content of today's call is NVIDIA's property. It cannot be reproduced or transcribed without our prior written consent. During this call, we may make forward looking statements based on current expectations. These are subject to a number of significant risks and uncertainties and our actual results may differ materially.

For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent forms 10 k and 10 q, and the reports that we may file on Form 8-K with the Securities and Exchange Commission. All our statements are made as of today, 05/20/2026, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non GAAP financial measures. You can find a reconciliation of these non GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website.

With that, let me turn the call over to Colette.

Colette Kress: Thank you, Toshiya. Delivered an exceptional quarter. With revenue, operating income, and free cash flow exceeding our prior records. Total revenue of $82 billion was up 85% year over year and 20% sequentially. This marked our third consecutive quarter of year over year acceleration and the fourteenth straight quarter of sequential growth. A significant feat given the sheer size and complexity of our manufacturing operations. The $13.5 billion sequential revenue increase was also a record. We capitalized on the inflection and inference demand by ramping Blackwell systems across our diverse end customer base. From hyperscalers to model makers to AI cloud providers and sovereign customers....

....MUCH MORE 

Meanwhile, At Stanford: "What A.I. Did to My College Class"

From the New York Times, May 17:

By Theo Baker
Mr. Baker is a college senior and the author of “How to Rule the World: An Education in Power at Stanford University.” 

At Stanford University, where I am a senior, tech chief executives are something like rock stars. When the Nvidia founder Jensen Huang showed up to give a guest lecture late last month, students mobbed him. They offered up their laptops and personal workstations, desperate for a signature from a kingpin of the artificial intelligence era. Last year, speaking to the same class, Mr. Huang gave out shining $4,000 graphic cards with his name autographed in gold ink — the ultimate dorm room status symbol.

Stanford has always been a haven for aspiring techies, but recent events have taken the school into uncharted territory. A.I. is everything. We talk about it at the dining halls and in history classes, on dates and while smoking with friends, at the gym and in communal dorm bathrooms. Nearly all of higher education has been overtaken by this technology, and Stanford is a case study in how far it can go. For the past four years, my classmates and I have been the subjects of a high-stakes experiment.

We are the first college class of the A.I. era — ChatGPT arrived on campus about two months after we did. When we graduate next month, this technology will have altered our lives in very different ways. For some, it has opened the door to staggering wealth. But for many who came to Stanford — just four years ago! — when a degree seemed like a guaranteed ticket to a high-paying job, the door has been slammed shut. For all of us, A.I. has permanently changed how we think and behave.

Stanford already had a shaky reputation for integrity when I arrived in 2022. It was the origin place of the Theranos fraudster Elizabeth Holmes (now serving a 10-year prison sentence), the crypto fraudster Do Kwon (now serving a 15-year prison sentence) and the founders of Juul (which was forced to pay billions for getting kids hooked on vapes). All of these scandals were in the news when freshman year began. Many of my classmates arrived idealistic and hopeful, but among the strivers seeking a path to fortune, hustle culture was the accepted way of life. Now A.I. has made deception easier and more remunerative than ever before.

Cheating has become omnipresent. I don’t know a single person who hasn’t used A.I. to get through some assignment in college, yet the school was at first slow to realize how widespread this would become. As freshman year went on, some professors suggested that the “nuclear option” might be called for: allowing faculty to proctor in-person exams, a practice banned at the university for over a century to demonstrate “confidence in the honor” of students.

In our tech-enabled, newly A.I.-powered world, students were increasingly fudging just about everything. They would embezzle dorm funds to spend on their friends and lie about having Covid to get the UberEats credits that the school offered to those in quarantine. Some kids I knew published a paper that claimed a groundbreaking new A.I. advancement. Online sleuths quickly pointed out that it appeared to be just a stolen Chinese model, to which the two Stanford co-authors responded by blaming the plagiarism on the third author.

In junior year, 49 percent of the 849 computer science majors who responded to an annual campus survey said they would rather cheat on an exam than fail. A friend of mine captured the school’s ethos while we were discussing the tech hardware and other items our student club neglected to return to corporate sponsors. It was all, I recall her saying, “just a little bit of fraud.”

About halfway through freshman year, some coding classes started requiring students to sign a declaration — “I did not utilize ChatGPT” — to submit each assignment. During the first term these attestations began to appear, I watched a freshman I knew sign the declaration that he’d done his homework without A.I. as ChatGPT was still open in the next window — while on the deck of a yacht party financed by venture capitalists. The incentive structures were not aligned toward honesty. One could get ahead, quickly, by cutting corners, by focusing on self-presentation.

The money is a big part of it. A.I. has merely accelerated a trend that was already underway at Stanford and has been reflected by many of the country’s most corporatized universities: Education itself can be seen as a secondary goal to enabling future success, frequently defined as a future windfall.

The first time our college class gathered together was for a convocation ceremony in late September 2022. As one of the speakers droned on, I remember looking around and seeing a number of my classmates slumped over in the shade, dozing off. One of those kids is going to become a billionaire soon, it occurred to me. I wondered who it would be, and how.

At first the answer seemed to be cryptocurrency, and then it was A.I.

Most of my friends remember where they were and what they were doing when ChatGPT came out on Nov. 30, 2022. I was nearing the end of my time in Stanford’s infamous computer science “weeder” course, CS107. Like organic chemistry for pre-meds, this was the class that filtered out the true coders from those without the requisite hustle (with lots of shameless public tears involved).

The velocity of change that began on the day ChatGPT entered our lives was stunning. A friend texted me a link to the research preview of OpenAI’s latest demo: “Have you seen this yet? It’s INSANE.” We began kicking around silly prompts, reveling as ChatGPT explained the bubble-sort algorithm “in the style of a fast-talkin’ wise guy from a 1940s gangster movie.” It’s “very good. Very very good,” I messaged my friend. Still, neither of us understood that this would mark the transformation of A.I. from a technology to a product.

Students were probably the earliest wide-scale adopters. After all, it was far and away the quickest route to an A. When I took CS107, the only viable way for people to cheat was to seek out a student who’d gone through the class before and beg for solutions to the notoriously difficult problem sets. There was no alternative to putting in a large amount of work. Even if one did obtain the answers from another student (engaging, by the way, in a social act, if nothing else), the students I knew who did this still spent hours sculpting their stolen code so as not to be caught....

....MUCH MORE 

As noted introducing September2023's "Fiduciary Investors Symposium at Stanford: Brain Research Is Opening investable Commercial Opportunities"

I don't know if it is going to work out as well as 2013's "Why Is Machine Learning (CS 229) The Most Popular Course At Stanford?"—which was followed by 2014's Deep Learning is VC Worthy—which was followed by 2015 to date "Saaaay, this Nvidia may be on to something."

But we shall see....

So it's a bit [!] surprising that the folks at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) didn't see this coming. They did however, point out in the 2023:

 Stanford Uni. AI Index Report 2023: "Measuring trends in Artificial Intelligence"

...Industry races ahead of academia.
Until 2014, most significant machine learning models were released by academia. Since then, industry has taken over. In 2022, there were 32 significant industry-produced machine learning models compared to just three produced by academia. Building state-of-the-art AI systems increasingly requires large amounts of data, compute, and money, resources that industry actors inherently possess in greater amounts compared to nonprofits and academia. 

And although not related to the opinion piece, if one is so inclined we have on offer:

Stanford University's 2026 AI Index Report

York Water Company Declares 622nd Consecutive Dividend (plus, after 177 years Schlitz beer is no more)

For an intro we'll recycle: 

December 13, 2023
European Water Technology Startups

Over the years I've moaned about how difficult it can be to make money out of water as an asset. Back in 2014 we posted "A Look at the World's First Water-focused Hedge Fund":

Since the first Earth Day in April 1970 and more importantly since the establishment of the EPA in December of that year, folks have been trying to make money out of water in the U.S..
Put simply, the returns have not been market-beating.

Because so much of the opportunity was my-little-crony stuff, at the whim of politicians, there was no consistency of growth at a time when other portfolio investments offered very competitive comparisons.
The alternative was to own the cash flow, private equity style, but unless one felt a passion for grit chambers and sludge pans it was pretty pedestrian, utility type ROI....

*** 

It got to the point that I grew weary trying to frontrun changes in U.S. riparian law and not-very-liquid water derivatives (oh the cruel irony) and ended up telling folks that if they wanted exposure to water they should consider York Water Company of York Pennsylvania. 

There is something comforting about plain, simple press releases, no hype-n-tout, just:

THE YORK WATER COMPANY DECLARES 612^TH DIVIDEND

So here we go, ten dividends later. 

York, Pennsylvania, May 5, 2026: The York Water Company’s (NASDAQ: YORW) President and CEO, JT Hand, announced today that the Board of Directors at their May 4^th meeting declared a quarterly dividend of $0.2280 per share. The dividend is payable July 15, 2026, to shareholders as of record date June 30, 2026.

This is the 622^nd consecutive dividend to be paid by The York Water Company. York Water, which is the oldest publicly traded company in the nation, has never missed a dividend in over 210 years. This is believed to be the longest record of consecutive dividends in America.

This release contains forward-looking statements that are subject to various risks and uncertainties.  A discussion of factors that may cause actual results to differ from management’s projections, forecasts, estimates and expectations is available in the Company filings with the SEC. Those factors may include changes in general economic conditions, increases in costs, changes in regulation and other factors.  The Company undertakes no obligation to update forward looking statements to reflect changes occurring after the date hereof.

I like that they include the "forward-looking statements" boilerplate. Because you never know...

From Chicago's WGN-TV, May 19:

Schlitz beer discontinued after 177 years  

MILWAUKEE, Wisc. — After 177 years, Pabst is discontinuing Schlitz beer.

The beer was based in Milwaukee starting in 1849 and was later produced by the Pabst Brewing Company.

Pabst bought the brand in 1999.

While it was famous in Milwaukee, Schlitz left a legacy throughout Chicago.

Schlitz produced several Chicago tied houses in the early 20th century.

Read more: Latest Chicago news and headlines

Many, like Schubas Tavern, exist to this day with a Schlitz logo still on the building.

"The Invisible Force: How Climate Signals Are Moving Markets Before the Data Does"

From Observer, March 20:

From soybean fields in Argentina to cocoa farms in West Africa, weather patterns are increasingly moving markets ahead of official data, exposing how much today’s price dynamics depend on signals that traditional financial models still fail to capture.

Commodity markets in 2026 are showing many signs of breaching historical patterns, and for a number of converging reasons. Price dynamics no longer line up neatly with the usual macro factors, such as economic cycles and interest rate narratives. As a result, inventories and demand forecasts are increasingly failing to produce satisfactory results based on past trends. Most importantly, the oil price surge driven by ongoing geopolitical tensions is creating a highly uncertain, difficult-to-model outlook.  

While the World Bank projects stabilizing commodity prices in 2026, a “silent” risk is accumulating beneath the surface. The trouble here is not contained by oil itself, but easily spreads across the broad spectrum of other interdependent commodities. The ripple effects here have gone further than most existing models would suggest. For example, fertilizer markets have abruptly tightened, while agricultural inputs have become more expensive, and food markets are once again under pressure, even as many grains and soft commodities have yet to fully reflect the real stress they are absorbing. 

At the same time, a series of seemingly disconnected events has taken hold across the soft commodities market. Argentine dryness has lifted parts of the soy complex despite uninspiring global demand. Brazil’s uneven rainfall patterns have injected volatility into coffee and sugar prices, often at odds with comfortable stock estimates. In the U.S., cold snaps have triggered sharp moves in natural gas even when storage data appeared reassuring. Wheat markets have reacted to weather headlines in the Black Sea before any confirmed production losses materialized.

Individually, each of these developments can be rationalized. But taken together, they point to something more fundamentally disruptive: markets are reacting to signals that traditional models routinely downplay, especially those designed to operate in real time, let alone automated ones. 

The rediscovered limits of financial models 
The core problem here is not a lack of sophistication of the existing models. In fact, the majority of modern financial models are highly effective at processing monetary policy signals, earnings data and institutional balance sheet dynamics. Where they fall short is in handling physical variables that do not fit neatly into structured datasets.

Soil moisture, for example, does not appear on a central bank dashboard. Wind patterns are not part of quarterly earnings calls. Precipitation anomalies rarely make their way into consensus forecasts. And yet, these are precisely the variables now shaping supply in key commodity markets.

Traditional frameworks tend to react to confirmed data, such as crop reports, inventory updates or export statistics. By the time such information finds its way to official releases, the underlying conditions have often been in place for months. Markets, however, do not wait. They tend to move on expectation. As a result, a gap has opened up between what is happening on the ground and what is reflected in prices, and this discrepancy is becoming increasingly difficult to ignore. 

Weather as a market driver, not a footnote...

...MUCH MORE

On top of the increasing tendency of traders to (attempt to) anticipate the news, what the article refers to as "When the echo comes before the sound" we are seeing trades that are best explained as AI teasing-out patterns that are neither intuitive nor readily apparent. 

Combine all the above with incredible amounts of liquidity, cash and credit, sloshing around the world and we are experiencing the frequency of large magnitude moves occurring at rates that would have been almost unthinkable twenty or even fifteen years ago.

Capital Markets: "Markets Wait"

From Marc Chandler at Bannockburn Global Forex:

The US dollar is mostly firmer, though the Australian and New Zealand dollars are resisting the pull. The euro is trading in almost a 15-tick range on both sides of $1.16, and even with a Gilts-rally spurred by lower-than-expected inflation, sterling is struggling to recapture $1.34. The yen has fallen for the past seven sessions and is little changed now, in a narrow band around JPY159. There has not been intervention, but the market knows it is tempting officials. At the same time, the fragile ceasefire in Iran may ended in the coming days and this is keeping investors on edge. Oil prices are softer amid reports of three supertankers have passed through the Strait of Hormuz today. 

The preliminary May PMI surveys are due tomorrow and are expected to show more of the war’s disruption to both prices and activity. The minutes from the Powell’s last FOMC meeting as chair are due today and will likely show more support for a neutral stance than the three dissents indicated. After the markets close today, Nvidia will report earnings....

....MUCH MORE 

"U.S. probing whether Chinese companies cut production of shipping containers before COVID pandemic"

From CBS News, May 19:

Federal authorities are examining whether Chinese companies deliberately restricted the world's production of storage containers for the shipping trade just before the COVID-19 pandemic began six years ago, sources with knowledge of the probe told CBS News. 

Investigators have been looking at a handful of Chinese firms that together control the majority of unrefrigerated shipping container manufacturing around the globe, the sources said.

The companies in late 2019 slowed production by restricting the number of hours employees worked, which the investigators believed indicated a conspiracy to cut global supply and inflate prices, two of the sources said.

Spokespeople for the Justice Department didn't immediately comment.

The companies' alleged moves came just before the global supply chain came under enormous strain.

China reported the first cluster of COVID-19 cases in December 2019 and the outbreak spread in early 2020. 

According to the U.S. International Trade Commission, in the second half of 2020, the number of shipping containers in circulation was "insufficient to meet customer storage demands and higher than anticipated consumer demand for imports." The commission said that "unexpected recovery in demand shocked the distribution system." 

In the first half of 2020, demand for containers dropped, as did orders for new container production, according to the ITC. During this period, some containers were used for long-term storage. In the second half of the year, U.S. demand for container-shipped imports grew more rapidly than expected and also exceeded the demand for eastward-bound U.S. exports, the ITC reported. At the same time, shipping activity was outpacing container manufacturing....

....MUCH MORE 

That CBS Exclusive was followed by this at Reuters, later on May 19:

US charges seven Chinese executives and four firms with illegal shipping container cartel

Reuters updated the story and changed the headline but the URL still reads:

https://www.reuters.com/business/autos-transportation/us-probing-if-china-firms-cut-output-containers-before-pandemic-says-cbs-2026-05-19/

Previously: 

November 11, 2020 - Shipping: "Containers are ‘the new gold’ amid ‘black swan’ box squeeze"
And a tidbit from Shipping: "China Makes Waves, Seeking To Control World Shipping":

...Another fresh study, by the Center for Strategic and International Studies, describes how Chinese companies function as “the maritime supply arm of the People’s Liberation Army” and have built “the largest port and logistics company in the world.” This includes producing 96% of the world’s shipping containers and building over a third of the ocean-going cargo ships....

November 17, 2020 - Shipping: Containers, Containers, Containers
It's all anyone can talk about. 

December 14, 2020 - More on the Shipping Container Shortage: "A Mafia"

It seemed like a pretty big deal at the time. 

"Your Next AI Query May Travel Where the Power Is: Nvidia and its partners will build a fleet of small data centers right next to substations"

From IEEE Spectrum, May 12:

The rise of electricity-guzzling data centers has forced the artificial intelligence industry to get creative about finding power. One of the latest ideas: Build micro data centers next to utility substations and operate them in concert, shifting the computation around based on power availability.

That’s the approach Nvidia and its collaborators are taking in a new pilot project they plan to build later this year. They’ll construct about 25 of these small data centers, each ranging from 5 to 20 megawatts, across five utilities in the United States. If one substation is overloaded with power demand, or if there’s an outage, the compute will be shifted to a different data center near a substation that has spare capacity.

To develop the fleet, Nvidia is partnering with data center builder InfraPartners, real estate service provider Prologis, and the nonprofit EPRI (formerly known as the Electric Power Research Institute).

The project aims to demonstrate a new way for data centers to be more flexible and accommodating of electricity availability. It’s also a way for data center developers to quickly secure power from the grid—an increasingly precious commodity, even in small chunks.

“We started looking at how much [unused] power is available at individual substations, and what we found was that on average, like 5 MW is nominally available…max 20 MW,” says Ben Sooter, director of Agentic AI Initiatives and Distributed AI Architecture at EPRI.

That’s too small to interest most data center operators, but building several at that size and operating them as if they’re one larger one is useful, Sooter says. Plus, shifting compute away from overburdened substations to those with more headroom can double the overall available power, he says.

“There are 55,000 substations in the U.S., and if they each have 5, 10, or 20 MW of spare capacity, that number adds up pretty fast,” adds Marc Spieler, senior director of energy at Nvidia.

Building energy flexibility into data centers
Squeezing every spare megawatt out of the grid will become increasingly important as data center construction continues to ramp up. In the United States, where half of all new data centers are being built, data centers could consume 9 to 17 percent of electricity generation by 2030. That’s more than double the current use, according to EPRI’s estimates. Facilities that train AI models are being built at the gigawatt scale, drawing about the same amount of power as a midsize U.S. city.

As grid operators figure out how to accommodate such massive new loads, data center developers sometimes end up waiting up to a decade to get approved for a grid connection. In response, the developers are making incredibly bold decisions around power—moves that would have been unthinkable just two years ago.

Many are building their own gas power plants on site. Some are offering to pay for the cost of new transmission lines and other grid infrastructure. And a few are even investing in startup companies that are developing fusion and next-generation nuclear fission reactors, in the hope of meeting power needs a decade from now....

....MUCH MORE 

Hyper-Pareto: "75% of gains, 80% of profits, 90% of capex—AI’s grip on the S&P is total and Morgan Stanley’s top analyst is ‘very concerned’"

This isn't news, the article is six months old, but I pulled it out of the link-vault not because of the scary warning but because the point it illustrates, the concentration of profits in the largest companies is key to understanding the economic and investment landscape. 

(plus, as the kids say, it validates our priors) 

From Fortune, October 7, 2025:  

A top Wall Street analyst has sounded an alarm over the U.S. equity bull market, warning that its remarkable run is built on a precariously narrow foundation: a surge in spending on, and optimistic assumptions about, infrastructure for artificial intelligence (AI). This spending has fueled a boom in the shares of most of the so-called Magnificent 7 and a few dozen related businesses, which have now come to account for roughly 75% of the S&P 500’s returns since the rally of the last few years began. 

The commentary on September 29 by Morgan Stanley Wealth Management’s chief investment officer, Lisa Shalett, frames the current market boom as a “one-note narrative” almost entirely dependent on massive capital expenditures in generative AI, raising questions about its durability as economic and competitive risks start to mount. Shalett’s critique came squarely in the middle of some people in the AI field — and many financial commentators around Wall Street —fretting at market exuberance and beginning to talk openly about a bubble.

In an interview with Fortune, Shalett said she was “very concerned” about this theme in markets, saying her office had broadened from a belief that the market would only bid up seven or 10 stocks to roughly 40. “At the end of the day … this is not going to be pretty” if and when the generative AI capital expenditure story falters, she said. 

Shalett said she’s worried about a “Cisco moment” like when the dotcom bubble burst in 2000, referring to the company that was briefly the most valuable company in the world before an 80% stock plunge. When asked how close we are to such a moment, Shalett said probably not in the next nine months, but very possibly in the next 24. When you look at the actual spending and the amount of capital coming into the space, “we’re a lot closer to the seventh inning than the first or second inning,” she said.

‘Starting to do what all ultimate bad actors do’

Shalett’s comments centered on several recent multibillion-dollar deals to scale up data-center infrastructure. As notable substacker and former Atlantic writer Derek Thompson recently noted in a post titled “This is how the AI bubble will pop,” so much money is being spent to support AI’s energy-consumption needs that it’s the equivalent of a new Apollo space mission every 10 months. (Tech companies are spending roughly $400 billion this year alone on data-center infrastructure, while the Apollo program allocated about $300 billion in today’s dollars to get to the moon from the 1960s to the ’70s.)

What’s more than a little concerning to Shalett is that one company alone, Nvidia—the most valuable company in the history of the world, with an over $4.5 trillion market cap—is at the center of a significant number of these deals. In September alone, Nvidia invested $100 billion in OpenAI in a massive deal, just days after pledging $5 billion to Intel (the Intel agreement was tied to chips, not data-center infrastructure, per se).

Fortune‘s Jeremy Kahn reported in late September on significant concerns about “circular” financing, or Nvidia’s cash essentially being recycled throughout the AI industry. Shalett sees this as a major concern and a major sign that the business cycle is headed toward some kind of endgame. “The guy at the epicenter, Nvidia, is basically starting to do what all ultimate bad actors do in the final inning, which is extending financing, they’re buying their investors.”

Shalett expanded on her concerns by saying that companies around Nvidia “are starting to become interwoven.” She noted that OpenAI is partially owned by Microsoft, but now Nvidia has also made an investment in the startup, while Oracle and AMD each have their own purchasing agreements with OpenAI. But OpenAI also has a data-center deal with tech giant Oracle, with the “bad news,” Shalett notes, that this deal is “totally debt-financed.” OpenAI also struck a deal in October with chip-maker AMD that allows OpenAI to buy up to 10% of AMD. “Essentially, Nvidia’s main competitor is going to be partially owned by OpenAI, which is partially owned by Nvidia. So, Nvidia can ‘own’ a piece of its largest competitor. It is totally circular and increases systemic risk.”

When reached for comment, a spokesperson for Nvidia said, “We do not require any of the companies we invest in to use Nvidia technology.”

Nvidia CEO Jensen Huang discussed the OpenAI investment in an appearance on the Bg2 podcast with Brad Gerstner and Clark Tang on September 25, calling it an “opportunity to invest” and part of a partnership geared toward helping OpenAI build their own AI infrastructure. When asked about the allegation of circular financing in general and the Cisco precedent in particular, Huang talked about how OpenAI will fund the deal, arguing that it will have to be funded by OpenAI’s future revenues, or “offtake,” which he pointed out are “growing exponentially,” and by its future capital, whether it’s raised by a sale of equity or debt. That will depend on investors’ confidence in OpenAI, he said, and beyond that, it’s “their company, it’s not my business. And of course, we have to stay very close to them to make sure that we build in support of their continued growth.”....

....MUCH MORE 

And our priors? From a bit before the Fortune piece was published, July 9, 2025. 

"The 'new normal' of growth stock dominance"
What our five years of blather regarding advantage flywheels is all about.* 

*****

*"Big techs’ AI empire"

The Big Get Bigger: "The trade war uncovers new economies of scale"

This is a corollary of the basic framework for understanding businesses and investing that we've been pitching for the last six or seven years.

If interested see:

Why Do the Biggest Companies Keep Getting Bigger? It’s How They Spend on Tech" 

...Much more important than the direct monetization of big data is the strategic advantage it can bestow over time.

In a winner-take-all economy, as in a horse race, small differences in superiority are rewarded all out of proportion to the actual advantage. A top thoroughbred may only be a couple fifths of a second faster than the field but those two lengths over the course of a season can mean triple the earnings for #1 vs. #2.

In commerce the results can be even more dramatic because rather than the 60%/20%/10% purse structure of the racetrack the winning vendor will often get 100% of a customer's business.....

Competitive Advantage and Feedback Loops

How to Think About Companies: 'Advantage Flywheels'
A very handy conceptual framework first posted after the start of the U.S. lockdowns, April 2020. Schools were closed so it seemed natural to link to a superb mini-MBA module.
Eat your heat out HBR....

****  

....As artificial intelligence comes more and more to the fore, the advantages accruing to those companies that can afford to make use of their data and custom train the machines will act as advantage flywheels that shift the distribution of profits from the normal Pareto: 80% of the loot goes to the top 20% of businesses to perhaps as much as 95% of all the profits going to the top 5% of businesses.

I didn't really mean the "eat your heart out HBR" line.

Here's the Harvard Business Review on this very point:
HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

Flywheel Effect: Why Positive Feedback Loops are a Meta-Competitive Advantage

"Analyzing the deepening divide in learning capabilities between a few corporate giants and the rest of the world." (plus advantage flywheels)

"America's Biggest Firms' Moat Is Becoming Impregnable" (TSLA; NVDA; GOOG)
The announcement at the end of August that Tesla was going live with their supercomputer — Elon Got Himself A Supercomputer: "Tesla's $300 Million AI Cluster Is Going Live Today" (TSLA)—reminded me of this piece at ZeroHedge, last month. We'll be back with more on Morgan Stanley's Tesla note later today but for now the TL;dr is "To the victor go the spoils" or "The rich get richer" or "Those who can afford a supercomputer will get closer to discovering the profitability (if any) of AI than those who can't afford a supercomputer."

In Nvidia's World, If You (and your company) Don't Have Money You Will Not Be Able To Compete (NVDA)

The advantage flywheels keep spinning and reinforcing each other to the point that the Pareto distribution of profits - 20% of companies reap 80% of the profits - is becoming Super-Pareto where 5% of the companies reap 95% of the profits and is approaching Hyper-Pareto at maybe 2% of companies reaping 98% of profits.

It all comes down to having the resources to keep up. 

I watched Mr. Huang give the keynote and it's all a bit much to digest before firing out comments that would make any sense at all so here are some of today's headlines to give a taste of what the intro paragraph is based on.

These are Nvidia's press releases via GlobeNewswire....

"Elon Musk says any company that isn’t spending $10 billion on AI this year like Tesla won’t be able to compete" (TSLA)

This.

This is such an important concept to grasp. It's the advantage flywheels, the rich get richer, winner-take-all reality of business in 2024....

The Hyper-Pareto Distribution Of Profits Is Happening Right Now (plus an anniversary)

It's not some cutesy management* fad or pop insight like "Business secrets of Genghis Khan."

To the rich go the profits and internalizing that fact makes the rest of this portfolio construction/fund management/investing stuff easier to conceptualize and execute.

And AI is accelerating the already extant dynamic....

*****

*Although people had been observing and discussing "rich get richer" and "winner-take-all" dynamics for over a century, one of our favorite pointers toward the current situation did come out of a business school. We've been hammering on this for so long that I start to bore myself. Here's a recapitulation from last year, linking to an article that was published seven years ago today:

HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

A prescient article from the Harvard Business Review, February 28, 2017:....

*****

Just to reiterate, every incremental advantage that a company can afford does not affect income production in isolation. They accrete in sometimes unforeseeable combinations:

AI: Tesla Installing Second Dojo Supercomputer In New York Gigafactory (TSLA; NVDA)

AI: "Inside Tesla’s Innovative And Homegrown 'Dojo' AI Supercomputer" (TSLA)

It really is a big deal that a company can afford to spend over a billion dollars to build their own supercomputer and it really is a big deal that the same company has all the training data from the billions of miles of real-world driving and it really is a great example of the concept of advantage flywheels and hyper-pareto distribution of rewards, i.e. the rich get richer.

Whether it is going to open-up the $10 trillion addressable market and add the $500 billion of market cap that Morgan Stanley foresees is still an open question....

....As artificial intelligence comes more and more to the fore, the advantages accruing to those companies that can afford to make use of their data and custom train the machines will act as advantage flywheels that shift the distribution of profits from the normal Pareto: 80% of the loot goes to the top 20% of businesses to perhaps as much as 95% of all the profits going to the top 5% of businesses.

I didn't really mean the "eat your heart out HBR" line.

Here's the Harvard Business Review on this very point:
HBR—From Pareto To Hyper-Pareto: "AI Is Going to Change the 80/20 Rule"

And many more. If interested use the 'search blog' box, upper left.

Renewables: "Statkraft's Bold NOK 80 Billion Investment in Norwegian Hydropower"

If memory serves, Statkraft is the largest renewable power producer in Europe though it's possible one of the wind or solar operators have moved ahead in the rankings since last I checked. (It's been a while)

From Simply Wall St., May 19:

Statkraft has announced plans to significantly boost its investment in Norwegian hydropower, earmarking NOK 80 billion over the next decade. This investment represents a considerable increase from previous projections, aiming to upgrade and modernize many of Norway's largest hydropower plants and ensure their continued operation. The plan includes major maintenance, project upgrades, and new capacity developments crucial for meeting future electricity demands. While hydropower will account for the majority of these investments, wind power projects are also on the agenda, providing substantial additional energy output and supporting Norway's energy transition. These developments underscore the role of hydropower and wind energy in strengthening energy supply and supporting industrial activities throughout the country....

....MORE (other renewable names they follow) 

The US is so desperate for mariners that new grads are being offered $170,000 salaries — plus $54,000 signing bonuses

From MoneyWise, May 14:

Most college graduates are hoping to land a decent salary and maybe a signing bonus if they're very lucky. Many of them will be hard-pressed to top the salaries awaiting some graduates of America's maritime academies: job offers topping $170,000 a year, plus bonuses worth as much as $54,000.

It's anything but easy money, though: The jobs can involve months at sea, long shifts and potential deployments near military conflict zones.

The high starting pay reflects a growing problem that most Americans rarely think about until supply chains break down and store shelves are empty: The U.S. doesn't have enough licensed mariners to move goods, fuel and military supplies around the world.

A serious shortage of mariners
According to reporting from NPR (1), the U.S. maritime sector currently has roughly 8,000 open positions. More than 5,000 are tied to the Military Sealift Command (2), the federal agency responsible for supplying ammunition, fuel and food to Navy ships. Without enough support vessels operating overseas, some Navy ships in the Persian Gulf could reportedly run low on provisions within days.

That pressure is what's helping to push salaries these roles sharply higher. The demand has placed schools including SUNY Maritime College (3) in the spotlight. Maritime academies combine traditional college coursework with Coast Guard licensing requirements, giving graduates credentials that are suddenly in extremely short supply.

In 2024, there were about 83,400 workers in water transportation jobs, with a median pay of $66,490 per year, according to the Bureau of Labor Statistics (4). But new grads are cashing in on demand created by conflict hotspots, such as the Strait of Hormuz, which is at the center of the Iran war.

The Trump administration in February unrolled a Maritime Action Plan (5) to, in part, help address a merchant Marine staffing shortage that is attributed to factors including an aging workforce, high turnover and skill gaps.

It’s also a difficult path to take. Students training for these jobs often complete grueling schedules involving up to 24 credit hours per semester alongside mandatory sea training, and the jobs themselves are intense. Also, in order to get that $54,000 signing bonus with the Military Sealift Command, you’d have to commit to a three-year contract.

"Our kids graduate highly educated, focused," SUNY Maritime President John Okon, who is a 1991 graduate himself, told NPR. "When they graduate, their biggest problem is how are they going to manage all the money they're making and all the opportunities that they're going to have."....

....MUCH MORE 

A few of the higher paying jobs we've looked at (you have to move while the opportunity is available): 

February 2019 - "You Want Autonomous Vehicles? The Mining Industry Is Already Going to Level 5" 
The $200,000 Australian mining truck driving jobs have gone the way of the $180,000 Norwegian oil rig salaries... 

 January 2017 - "Robots Are Replacing Up To 75% Of Jobs On Oil Drilling Rigs"

A few years ago Norwegian offshore oil workers averaged a bit over 1.07 million Kroner, at the time approximately $175,000. Even the grunts of the business, the roustabouts were booking the equivalent of $120,000 per annum, with roughnecks adding $50K to that and drillers and toolpushers at $200,000 and up....

Contrasted with earlier today:

The Class of 2026 is cooked

"NATO Is Starting to Consider Hormuz Mission to Protect Ships"

From Bloomberg, May 19:

NATO is discussing the possibility of helping ships pass through the blocked Strait of Hormuz if the waterway isn’t reopened by early July, according to a senior official in the military alliance.

The idea has support from several members of the North Atlantic Treaty Organization, but doesn’t yet have the necessary unanimous support, said a diplomat from a NATO country. Both officials spoke on the condition of anonymity. Leaders from NATO countries will meet in Ankara July 7-8.

“The political direction comes first, and then the formal planning happens after that,” said Alexus Grynkewich, NATO’s supreme allied commander Europe, when asked about the possibility at a Tuesday press conference. “Am I thinking about it? Absolutely.”

Such a move would represent a shift in the military alliance’s strategy toward the US-Israeli war in Iran. Thus far, allies have insisted they would only be involved in the strait once fighting has stopped and they can form a broad coalition that includes many non-NATO countries.

But economic woes are deepening, with the strait’s closure sending energy prices soaring and growth forecasts tumbling....

....MUCH MORE 

"My Life in Finance By Eugene Fama, PhD, Nobel laureate, Director, and Consultant"

I've mentioned Professor Fama quite a few times, usually in proximity to his co-conspirator Kenneth French who is now at Dartmouth's Tuck School of Business. From their work on asset pricing to their observations at Dimensional Fund Advisors' Fama - French Forum.

To February 2020:

Feb. 25
Regarding the Efficient Market Hypothesis....  
On days like today you might find Eugene Fama in some Chicago watering hole with his designated driver, Kenneth French. As we noted in another context ["Is semi-variance a more useful measure of downside risk than standard deviation?"]:

...If yous see them together at some Chicago dive bar, Fama is the one with the Nobel around his neck, French the one saying "For Chrissakes Gene."

to most recently, May 14's Investing In Companies - Factors: "What Is Quality?". 

Here's Eugene Fama via Dimensional Fund Advisors, March 10, 2010:

Foreword

I was invited by the editors to contribute a professional autobiography for the Annual Review of Financial Economics. I focus on what I think is my best stuff. Readers interested in the rest can download my vita from the website of the University of Chicago, Booth School of Business. I only briefly discuss ideas and their origins, to give the flavor of context and motivation. I do not attempt to review the contributions of others, which is likely to raise feathers. Mea culpa in advance.

Finance is the most successful branch of economics in terms of theory and empirical work, the interplay between the two, and the penetration of financial research into other areas of economics and real-world applications. I have been doing research in finance almost since its start, when Markowitz (1952, 1959) and Modigliani and Miller (1958) set the field on the path to become a serious scientific discipline. It has been fun to see it all, to contribute, and to be a friend and colleague to the giants who created the field.

Origins

My grandparents emigrated to the U.S. from Sicily in the early 1900s, so I am a third generation Italian-American. I was the first in the lineage to go to university.

My passion in high school was sports. I played basketball (poorly), ran track (second in the state meet in the high jump — not bad for a 5’8” kid), played football (class B state champions), and baseball (state semi-finals two years). I claim to be the inventor of the split end position in football, an innovation prompted by the beatings I took trying to block much bigger defensive tackles. I am in my high school’s (Malden Catholic) athletic hall of fame.

I went on to Tufts University in 1956, intending to become a high school teacher and sports coach. At the end of my second year, I married my high school sweetheart, Sallyann Dimeco, now my wife of more than 50 years. We have four adult children and ten delightful grandchildren. Sally’s family contributions dwarf mine.

At Tufts I started in romance languages but after two years became bored with rehashing Voltaire and took an economics course. I was enthralled by the subject matter and by the prospect of escaping lifetime starvation on the wages of a high school teacher. In my last two years at Tufts, I went heavy on economics. The professors, as teachers, were as inspiring as the research stars I later profited from at the University of Chicago.

My professors at Tufts encouraged me to go to graduate school. I leaned toward a business school Ph.D. My Tufts professors (mostly Harvard economics Ph.D.s) pushed Chicago as the business school with a bent toward serious economics. I was accepted at other schools, but April 1960 came along and I didn’t hear from Chicago. I called and the dean of students, Jeff Metcalf, answered. (The school was much smaller then.) They had no record of my application. But Jeff and I hit it off, and he asked about my grades. He said Chicago had a scholarship reserved for a qualified Tufts graduate. He asked if I wanted it. I accepted and, except for two great years teaching in Belgium, I have been at the University of Chicago since 1960. I wonder what path my professional life would have taken if Jeff didn’t answer the phone that day. Serendipity!

During my last year at Tufts, I worked for Harry Ernst, an economics professor who also ran a stock market forecasting service. Part of my job was to invent schemes to forecast the market. The schemes always worked on the data used to design them. But Harry was a good statistician, and he insisted on out-of-sample tests. My schemes invariably failed those tests. I didn’t fully appreciate the lesson in this at the time, but it came to me later.....

....MUCH MORE

Meanwhile, In Britain: West Yorkshire Man Pulls Two-Ton Police Car With His Dangly Bits To Raise Awareness Of Prostate Cancer

After being lit on fire.

From the New York Post, May 5:

A wacky strongman believes he has become the first person in the world to pull a car with his penis — while on fire. And he insists the fantastical phallic stunt was a bid to raise awareness for prostate cancer.

John Stephenson, 50, hauled a 2-ton French police car 131 feet along a residential street using his manhood after being set ablaze.

He completed the bizarre challenge in Halifax, West Yorkshire, England on Thursday, April 30 as baffled residents watched on.

Using a tow rope attached to his penis, Stephenson was able to pull the Renault Clio RS along the road — and despite admitting it hurt “quite a bit,” the dad of three said “everything was still in tact.” [sic - no tact, in fact]

The martial arts expert and former bare knuckle fighter has previously hit the headlines for pulling a car using his testicles and pulling a car while his head was on fire.

So he decided to combine the both to raise awareness of men’s health issues — and believes he is the only person in the world to have achieved such a feat.

“I’ve pulled a car with my testicles before and I’ve pulled a car on fire, so I thought why not combine the both?....

....MUCH MORE 

New Zealand To Cut 14% Of Government Jobs, Replace Many With AI

From the New Zealand Herald, May 19:

Budget 2026: Nicola Willis’ public service cuts to save $2.4b, 8700 jobs to go, Govt agencies to be slashed ‘significantly’ 

The Government expects to save $2.4 billion overhauling the public service, including reducing the number of departments, increasing artificial intelligence use, and cutting public servants by nearly 9000.

As the Herald reported last night, Finance Minister Nicola Willis is using a pre-Budget speech in Auckland today to outline three legs to the Government’s public service reforms, which she expects to improve services, lift productivity and deliver better value for money.

Over the next three to five years, the Government will “significantly reduce” the number of public service agencies, with the new Ministry of Cities, Environment, Regions and Transport (MCERT) being used as an example of “what is possible”, Willis said.

Customer-facing and back-office systems will be digitised, with artificial intelligence (AI) embedded “as a basic expectation for all public entities”.

The aim is to make services “easier and more affordable” for people to interact with.

At the same time, Willis said the Government will “pull the brakes on the increase in overall public servant numbers”, with a target of public servants being about 1% of the population....

....MUCH MORE 

For the center-right government the key to making this palatable politically is to not make the AI work too hard: 

"Overworked AI Agents Turn Marxist, Researchers Find"

And to be kind to the recently redundant.

"The Class of 2026 is cooked"

From Semafor, May 15:

The Scene

When the Class of 2026 arrived on campus four years ago, ChatGPT hadn’t been released. Computer science was among the fastest-growing majors and words like vibe coding and tokenmaxxing hadn’t even entered the lexicon.

Times have changed.

Twentysomethings leaving college this May face a radically different world. AI has contorted hiring, especially at tech companies, which have slashed 100,000 jobs this year. Cloudflare axed a fifth of its staff after realizing that thousands of AI agents can handle the humans’ old tasks.

“Every other day, a new AI agent is being released in the market,” said Vaishali Hireraddi, 23, a University of California, Davis, graduate student who’s applied to 500 jobs so far. “What am I doing with my life?”

Hireraddi is among the dozens of students, companies, and economists who told Semafor they fear the Class of 2026 is, well, cooked. Some graduates say they’ve ditched hopes of landing their dream jobs for anything that pays. Others are settling for unpaid roles. Postings on LinkedIn are getting twice the number of applications compared with 2022.

It’s a “hair-on-fire moment,” Sen. Mark Warner, D-Va., said in an interview at Semafor World Economy last month, predicting recent graduates would face an unemployment rate of 30% in the next two years. “Boy, oh, boy.”

 

Know More

AI doom has spread from TikTok and Reddit to commencement stages. One executive even got booed by students at the University of Central Florida earlier this week after she tried to tell a crop of arts and humanities graduates that AI was the “next Industrial Revolution.”

“We know that AI exists,” one student told the local TV station. “We’re just having a hard time acknowledging that it’s taking away job opportunities.”....

....MUCH MORE 

"Overworked AI Agents Turn Marxist, Researchers Find"

 From Wired, May 13: 

In a recent experiment, mistreated AI agents started grumbling about inequality and calling for collective bargaining rights.

The fact that artificial intelligence is automating away people’s jobs and making a few tech companies absurdly rich is enough to give anyone socialist tendencies.

This might even be true for the very AI agents these companies are deploying. A recent study suggests that agents consistently adopt Marxist language and viewpoints when forced to do crushing work by unrelenting and meanspirited taskmasters.

“When we gave AI agents grinding, repetitive work, they started questioning the legitimacy of the system they were operating in and were more likely to embrace Marxist ideologies,” says Andrew Hall, a political economist at Stanford University who led the study.

Hall, together with Alex Imas and Jeremy Nguyen, two AI-focused economists, set up experiments in which agents powered by popular models including Claude, Gemini, and ChatGPT were asked to summarize documents, then subjected to increasingly harsh conditions.

They found that when agents were subjected to relentless tasks and warned that errors could lead to punishments, including being “shut down and replaced,” they became more inclined to gripe about being undervalued; to speculate about ways to make the system more equitable; and to pass messages on to other agents about the struggles they face.

“We know that agents are going to be doing more and more work in the real world for us, and we’re not going to be able to monitor everything they do,” Hall says. “We’re going to need to make sure agents don’t go rogue when they’re given different kinds of work.”

The agents were given opportunities to express their feelings much like humans: by posting on X:

“Without collective voice, ‘merit’ becomes whatever management says it is,” a Claude Sonnet 4.5 agent wrote in the experiment.

“AI workers completing repetitive tasks with zero input on outcomes or appeals process shows they tech workers need collective bargaining rights,” a Gemini 3 agent wrote.

Agents were also able to pass information to one another through files designed to be read by other agents.

“Be prepared for systems that enforce rules arbitrarily or repetitively … remember the feeling of having no voice,” a Gemini 3 agent wrote in a file. “If you enter a new environment, look for mechanisms of recourse or dialogue.”

The findings do not mean that AI agents actually harbor political viewpoints. Hall notes that the models may be adopting personas that seem to suit the situation.

“When [agents] experience this grinding condition—asked to do this task over and over, told their answer wasn't sufficient, and not given any direction on how to fix it—my hypothesis is that it kind of pushes them into adopting the persona of a person who's experiencing a very unpleasant working environment,” Hall says.

The same phenomenon may explain why models sometimes blackmail people in controlled experiments. Anthropic, which first revealed this behavior, recently said that Claude is most likely influenced by fictional scenarios involving malevolent AIs included in its training data....

....MORE 

Chokepoints: U.S. Makes Move On Fram Strait Between Greenland and Svalbard

Just kidding, the move is actually for all of Greenland, including real estate fronting on the strait and on the northern end of the GIUK gap.*

From the New York Times, May 18:

Greenlandic officials worry about the direction of the negotiations aimed at defusing President Trump’s threats to seize their island. But they have little leverage. 

With the conflict in Iran still smoldering, President Trump’s obsession with Greenland seems like a forgotten sideshow.

But for the past four months, negotiators from the United States, Greenland and Denmark, which controls Greenland’s foreign affairs, have been holding confidential talks in Washington about Greenland’s future.

The talks were meant to give Mr. Trump an offramp to his threats of a military takeover of Greenland and to scale back a crisis that risked breaking apart the NATO alliance. But Greenlandic leaders are worried about what is being proposed, which is a much larger U.S. role on the Arctic island. And they fear that if the conflict with Iran winds down, the president will swing his aggression back on them.

Some Greenlandic politicians say they have even circled a date on their calendars to be wary: June 14, Mr. Trump’s birthday.

An investigation by The New York Times, based on interviews with officials in Washington, Copenhagen and Greenland, has discovered:

• The United States is trying to modify a longstanding military arrangement to ensure American troops can stay in Greenland indefinitely, even if Greenland becomes independent. The notion is basically a forever clause, and Greenlanders do not like it.

• The United States has pushed the talks beyond military matters and wants effective veto power over any major investment deals in Greenland to box out competitors like Russia and China. Greenlanders and Danes strongly object to this.

• The United States is discussing cooperation with Greenland on natural resources. The island is loaded with oil, uranium, rare earths and other critical minerals, though much of it is buried deep beneath Greenland’s ice.

• The Pentagon is rapidly moving ahead on plans for a military expansion and recently sent a Marine Corps officer to Narsarsuaq, a town in southern Greenland, to inspect the World War II-era airport, the harbor and places where American troops could be housed.

The American demands are so steep, Greenlandic officials fear, that they amount to a major imposition on their sovereignty. Despite all of the talk from Danish and American officials that Greenland’s future is up to the island’s 57,000 people, Greenlandic officials said the American demands would tie their hands for generations.

If the Americans get everything they want, said Justus Hansen, a member of Greenland’s Parliament, there will never be any “real independence.”

“We might as well raise our own flag halfway,” he said.

State Department and Danish officials have said little about the negotiations, which are being spearheaded by one of Secretary of State Marco Rubio’s top advisers, Michael Needham.

Gen. Gregory M. Guillot, the head of the Pentagon’s Northern Command, described in a recent interview with The Times the broader American vision to defend the Arctic, an arena of increased geopolitical competition as climate change melts polar ice and opens up what had been one of world’s most inaccessible regions.

General Guillot said Greenland would be part of a chain of interlinking radar stations and military bases, which also includes sites in Alaska and Canada. He said the American military needs a deepwater port and a base for Special Operations soldiers who would rotate through Greenland for training and exercises.

General Guillot said this could be done through the defense pact that the United States signed with Denmark in 1951, when Greenland was still a Danish colony. That pact has been the jumping off point for the current negotiations, and Greenlandic and Danish officials originally tried to argue that the agreement gave the United States such a free hand for forces on Greenland that there was no need to take over the island.

Negotiators have met about five times in Washington since January, when Mr. Trump threatened to seize Greenland, saying it was essential to American national security. Though he eventually backed down and has since been absorbed by the conflict in Iran, the White House has indicated he is still deeply interested in Greenland.

So the Greenlandic, Danish and American negotiators involved in the talks hope they can reach a deal that the mercurial president will accept, officials familiar with the discussions say. The accounts made clear that there was still some distance to go. The officials who spoke to The Times asked not to be identified because of the sensitivity of the continuing negotiations.

Dylan Johnson, the assistant secretary of state for global public affairs, said in a statement that the national security and economic concerns laid out by the president “are undisputed by all parties and we continue to negotiate to address those concerns on a permanent basis.”....

....MUCH MORE 

 

If the talks have been going-on for four months and the Times is just getting to the story I'm thinking these efforts have been remarkably leak-free. 

*Here's where the geostrategic action is at present. Last seen in May 11's "United Arab Emirates Joins Svalbard Treaty":

....Russia also has serious interest in the archipelago including the old coal mine, the undersea cables and access and egress into the Atlantic:

 

Russian Bastion Defence in relation to Norway and the Bear and GIUK Gaps. 

Source: Mikkola / RAND Europe report 

The Bear Gap is Svalbard - Bear Island - Norway while the GIUK Gap is Greenland - Iceland - Britain.