Big Tech’s AI Spending Is $3 Trillion Higher Than It Seems

Each quarter, big tech companies disclose their massive capital expenditures on artificial-intelligence infrastructure, from data centers to chips.

But those figures don’t come close to expressing the full extent of future spending to which Google parent Alphabet, Meta Platforms, Oracle and many others have committed. That is because a huge swath of their coming financial obligations aren’t reflected on their balance sheets.

Nine top tech companies had some $3 trillion of off-balance-sheet commitments mostly related to AI, according to a Wall Street Journal analysis of footnotes in their most recent securities filings. Those obligations are growing faster than traditional “capex,” which totaled about $600 billion over the past year they reported, and were about triple what the companies owe under their outstanding leases and long-term borrowings.

America’s blue-chip tech companies are placing these huge bets based on assumptions about what the demand for AI computing—and availability of AI hardware—will be in several years. Their hope is that they will easily meet all their obligations with future revenue as consumers and businesses adopt AI in every facet of American life.

If those assumptions about technology and demand prove wrong, these deals to clinch future capacity could become a monstrous burden for the tech companies and their investors.

Meta’s gigantic “Hyperion” data-center project in Louisiana, which is the size of about 1,700 football fields, helps explain how big obligations wind up off tech companies’ balance sheets.

Meta initially agreed to lease Hyperion for a four-year term starting in 2029, with options to renew for up to 20 years. It guaranteed that it would make bondholders whole if it doesn’t stay the entire two decades. The company doesn’t think payments under that guarantee are probable, so it hasn’t recorded any liability on its balance sheet.

In accordance with accounting rules, Meta’s Hyperion lease obligations will remain off balance sheet until it starts paying rent. It said its aggregate initial lease commitment is about $12.3 billion. Meta disclosed $347 billion in total obligations for leases that haven’t kicked in yet, including for Hyperion, as of June.

Across the companies the Journal analyzed, promises of payments under these uncommenced leases totaled $1.2 trillion in off-balance–sheet obligations, or about four times more than what was disclosed a year earlier. In addition to Meta, the Journal reviewed commitments for Alphabet, Amazon.com, Microsoft, Oracle, Nvidia, Broadcom, SpaceX and Advanced Micro Devices.

Data centers get stuffed with a lot of hardware, including the Nvidia chips that are used to train and run models and memory chips that store information. To buy all that, companies sign long-term contractual agreements well in advance to lock in production from their suppliers.

Those and other purchase obligations at the companies the Journal examined stand at a whopping $1.9 trillion. Under accounting rules, purchase commitments typically remain off balance sheet until a product or service is delivered. [...]

For the more anxious set on Wall Street, it is a worrying sign that some tech companies that once seemed to have fortress balance sheets have needed to tap the capital markets frequently.

Alphabet and Amazon recently posted results showing negative free cash flow, meaning their capital spending exceeded the cash they brought in from operating their businesses.

And that is before considering the implications of trillions in off-balance–sheet commitments. Whether or not the revenues ever arrive, purchase commitments and signed leases can’t be canceled, for the most part.

If things go wrong, tech companies will be paying an expensive tab for infrastructure that they can’t profitably use. These obligations could also lead increasingly indebted companies to have to borrow even more.

by Peter Rudegeair and Peter Santilli, Wall Street Journal | Read more:
Image: WSJ

The Reconstructionist: How PGA Tour CEO Brian Rolapp is Putting Golf Back Together

Brian Rolapp left the NFL to become CEO of the PGA Tour in the summer of 2025, walking away from two decades at a league he didn’t just rise inside of but helped build. The last several years of his career there he effectively ran the NFL business—the deals, the platforms and the broadcasts that turned an already dominant sport into the last appointment viewing left in American culture. He was the commissioner-in-waiting, the heir apparent to a job that pays more, commands more attention and carries far less daily uncertainty than the one he chose instead.

He left anyway, to lead a sport in the middle of an existential crisis it had largely caused itself. At age 54, he is a year into the job now, and his home office in Darien, Conn., has not caught up to the change. There is no golf memorabilia save for a family trophy, “The Rolapp Cup.” The football stuff has been left out of habit rather than sentiment, the residue of someone who has spent his career being told how good he is at what he does and has decided not to believe it. [...]

Ages 19 through 27 set the entire trajectory of his life, he says. He came home from his mission an almost-21-year-old college sophomore. Shortly after, his father died at 52. Rolapp met his wife, Cindy, not long after, married her, had his first child, and somewhere in that compressed timeframe became, in his own estimation, a person who knew what he wanted out of life at an age when most people don’t. “I think that’s kind of a rare thing,” he says, quietly enough that the sentence nearly disappears into the room.

The story of how he met Cindy is the one spot in hours of conversation where Rolapp’s voice picks up, faster, lighter, a story told at enough dinner parties to have worn itself smooth. He asked her out three times. The first go-around she said no; she had to watch her nieces. The second she had to do something for her grandmother. Rolapp assumed he was being gently but obviously turned down. A mutual friend assured him otherwise; that’s just who she is, she means it all literally. The third time, he asked if she wanted to get something to eat. Cindy said no; the Cowboys were playing the Cardinals on Monday Night Football, and she wanted to watch. She came over in sweatpants and a sweatshirt, having apparently spent zero time getting ready. His roommate told him after the game that if he didn’t ask her out again, he was an idiot.

Cindy has never cared, in the years since, what Brian does for a living, not out of indifference but by a deliberate boundary. “The only thing I care about,” he says, quoting her, “is that it doesn’t consume you, that it makes you a fuller human.” They do not talk about work at home. “Around the neighborhood, I was the NFL guy,” he says. “Now I’m probably the PGA Tour guy. Everyone else tries to define you by your job. I’m lucky to have a family that doesn’t.” For a while, that boundary lived in a small, deliberate joke—for years, Rolapp’s social media bio read simply “husband of one,” a wink at both the marriage and the faith it’s built on, a devout Mormon’s version of a punchline. It is, colleagues say, entirely on brand. Sincere enough to be meant, funny enough that nobody would mistake it for preaching. [...]

Rolapp’s title at the NFL was chief media and business officer. Officially, he ran league business operations; unofficially, he ran nearly everything at the NFL that wasn’t the games themselves. Media rights deals worth tens of billions of dollars went through his office along with the league’s digital strategy, built from basically nothing. When he started in 2003 the league was doing somewhere around $5 billion in revenue. This year, it will do roughly $23 billion. “I’m not saying I’m responsible for that,” he says, “but I was part of a hyper-growth stretch for a long time.”

Steve Bornstein, the former ESPN and NFL Network chief who recruited Rolapp from NBC to work at the NFL in 2003, says that’s underselling it. Bornstein says that Rolapp saw where the business was shifting—toward entertainment and media consumption onto phones and into digital spaces—years before that was conventional wisdom inside a league long organized around Sunday afternoons and cable carriage fees. What made him really effective, Bornstein says, had less to do with vision than with a habit most executives eventually lose. “It’s a person that listens and doesn’t just talk,” he says. “That’s his superpower. He listens, he synthesizes it, and then he asks intelligent, informed questions.”

Joe Siclare, the NFL’s longtime chief financial officer of 33 years, has never revised his first impression of Rolapp—smart, fluent in the media business in a way that never had to be re-earned. What Siclare remembers most isn’t the scope of Rolapp’s job so much as how he carried it. Rolapp rarely walked into a room already convinced he had the answer; he’d arrive with a position and let the facts move it, which Siclare came to see less as indecision than as a kind of discipline. “I think people felt like they worked with him, not for him.” [...]

Rolapp’s last stretch at the league is the clearest evidence of what all that listening and synthesizing produced. In March 2021, he oversaw the long-term media agreements that locked in Amazon, CBS, ESPN/ABC, Fox and NBC as the NFL’s broadcast partners for the next decade. He helped devise and implement the move of Sunday Ticket to YouTube, ending a more than 25-year run on satellite and transferring the league’s most devoted, highest-paying fans to a platform that didn’t exist when the package was created. He also led 32 Equity, the vehicle through which the league and its owners now make outside investments—one more example of building infrastructure for a business a decade before the rest of the industry admitted it needed one. 

“You’re only as good as your team,” Rolapp says, the closest thing to a mission statement in an otherwise unsentimental accounting of his own record.

That is precisely what makes his career change worth examining. Men who spend two decades succeeding inside one system rarely walk away from it at the moment of maximum leverage, and usually not for an organization in worse shape. “He was so valuable at what he did,” Lurie says, “that a lot of us, while genuinely happy for him, knew it was a devastating loss for the league.”

“I loved my job. I loved the NFL,” he says. “I probably could have done it forever.” He pauses on the word forever the way people do when they catch themselves nearly committing to something they no longer want. “To be honest, I was bored,” Rolapp says.

It’s a strange thing to admit about two decades that included a streaming buildout from scratch, a media-rights overhaul, and the slow migration of football from broadcast television to whatever comes after it—a stretch defined by constant change. That, Rolapp says, was also the problem. The change had become routine, the crises predictable, the same kinds of meetings producing the same kinds of decisions. There was less left to be curious about. He wasn’t looking for an exit, he says, but knew one was likely coming.

There was no obvious playbook for Rolapp’s new task. By the time he was named PGA Tour commissioner, the tour’s leadership had spent nearly two years locked in negotiations with Saudi Arabia’s Public Investment Fund and fans had grown exhausted by a schism that seemed indifferent to what they wanted.

What Rolapp did first was talk, in mostly informal sometimes hour-long conversations with players. The format, built around three questions, was almost naively simple for a man about to reorganize a multibillion-dollar sport: What do we do well? What don’t we do well? What would you change? What he found surprised him—a locker room that turned out to be smarter and more self-aware than its reputation suggested. He met players who loved the game without reservation but were more than ready to admit the tour itself had grown stale with too many events with too little imagination. As the months passed and the tour’s Future Competition Committee—the nine-person group led by Tiger Woods charged with reimagining the schedule—began to crystallize a direction, the conversations changed. “It became more of a validation of where we were going,” Rolapp says. “Still good. But different.”

This was different than the relationship he knew at the NFL, where the players’ union is collectively bargained, formal and distant by design. Golf was, at best, a fragile and personal trust between commissioner and competitors. That trust had frayed by the time Rolapp arrived, exacerbated by the tour’s surprise framework agreement with PIF in June 2023 that blindsided players who’d spent months publicly defending an institution that had been secretly negotiating with the enemy. Rolapp understood that whatever faith remained was thin, and that he wasn’t going to charm his way in. He went to work.

“I think he’s a guy that just kind of gets things done,” Scottie Scheffler said earlier this year at Bay Hill. “I met him last year at one of the playoff events. We sat down, and it was just, like, just getting right into it. He started asking questions and we started talking. It was like no nonsense—like, we’ve got an hour, let’s make the most of this hour. I loved it.”

“I clearly didn’t know a lot of things: how the tour worked, how the sport was set up, what was on the players’ minds,” Rolapp says. “But it’s also part of my leadership style. I’ve always believed humility and self-awareness are underrated leadership attributes, because they let somebody know what they don’t know. When you lose sight of that, that’s when leaders get in trouble, or they surround themselves with people who tell them what they want to hear, the classic yes men.”

by Joel Beall, Golf Digest |  Read more:

Image: Eric Ogden

[ed. Exactly what the sport needs. Contrast this leadership style with...oh, anyone else you can think of...]

‘Harry Potter’ Fans Succeed in Moving Construction Project to Avoid Dobby’s Grave

Harry Potter fans have succeeded in moving a construction project that would have originally gone through the “grave” of the character Dobby.

The 125-mile Greenlink power connector, which costs £430million, is intended to link power between the UK’s National Grid and Ireland, running between County Wexford and Freshwater West in Pembrokeshire.

However, the latter site is known to Potter fans as the site of house elf Dobby’s grave in the film Harry Potter And The Deathly Hallows, and contains a pile of stones with the words “here lies Dobby” that many flock to; fans have been asked not to lay stones by the National Trust, who own the site, due to the beach being an ecologically sensitive site.

It has now been revealed that the cable has now been rerouted after a BBC interview alerted fans, according to project manager Simon Ludlam.

“We did the shot, we finished I went back to London, and they then aired it a couple of weeks later,” he told the Energy Revolution podcast. “And we got hundreds of calls, I mean hundreds of calls.”

He further recalled: “I said, ‘Dobby, who’s Dobby? I don’t know Dobby?’ I said: ‘He’s a fictitious character in a fictitious book, the whole thing is fictitious, what are you talking about?’ [The colleague] said: ‘No it’s very, very serious’.”

They then discussed “exactly how to reroute the cable so we wouldn’t go anywhere close to Dobby’s grave” and that now, “a lot of people were very happy about that, and the project is now going [ahead] and Dobby’s happy”.

However, they ended up going “quite close” to real Bronze Age remains, though and “avoided Dobby’s grave”.

by Sam Warner, NME |  Read more:

Image: Wirestock Creators/Shutterstock

[ed. Hardly a day goes by that I don't read something that seems straight out of The Onion.]

The Extras Are Tired

Less than a decade ago, when I was working on technology stories, my colleagues and I ran into an issue that I’m pretty sure had not occurred to the people who founded this magazine in 1857: how to style the word influencer, which was an occupation and cultural force, but one just emerging. We weren’t sure that all of our readers would know what one was, and we also didn’t know how exactly we would define the word ourselves. I spent the fall of 2018 sending a lot of emails about whether we needed to encase the word in scare quotes.

Quaint! Many—but not all that many—years later, influencer is very much a real job, no explanation required. As of 2023, 27 million Americans were paid to make online content in one form or another, at least according to one marketing consultant company. Enthusiasm from influencers can turn a random business into a sensation, while their ire can do the opposite. Donald Trump’s White House is full of influencers, but Joe Biden’s courted them too, in apparent recognition of their power. This week, Arizona State University announced that it would begin offering a bachelor’s degree in content creation—influencing by another name—through its journalism school.

In some ways, the influencer industry is more legitimate than it’s ever been. But it has always been precarious, and more than a decade into its existence, it is neither novel enough to be exciting nor established enough to have a real professional code. In an oversaturated market, rage bait is the last sure way to get attention, despite the way it alienates people over the long term. AI is swiftly becoming the dominant way many people get personal-seeming advice about how to live their life, which makes the usefulness of aspirational online content even less apparent than it ever was. And so, although influencers—especially lifestyle influencers—have never been universally respected, they lately seem to be openly reviled.

Naturally, much of the influencer backlash lives online. A few months ago, someone asked on Reddit, “What’s an industry that provides zero value to society but makes billions of dollars?” Among the 5,300-plus responses: Ticketmaster, sports-betting companies, multilevel marketing schemes, private prisons, and—several times over—influencers. A hilarious number of people have found internet fame by making content about how much they hate other people who are internet-famous for making content. (“Everyone Is Finally Turning on TONE DEAF Influencers” is the title of one recent video, made by an Australian YouTuber with nearly 300,000 subscribers and a clothing line.)

But the juiciest fights play out in the physical world, which is where influencers very literally bump up against the people who can’t stand them. A few years ago, a coffee shop in Brooklyn banned photography after too many influencers clogged the café with tripods and handheld lights; earlier this month, Indonesia indicated that it would crack down on people creating content for pay while on tourist visas.

Last week, the scene of the debate was a gift shop in Nantucket, an island that has recently been overrun by vacationing influencers, just like Bali, Iceland, and Santorini before it. The store’s operators, evidently fed up with the stream of people filming inside, had a sign made that read No Influencers, hung it up in the store, and posted a picture of it on Instagram. There, it drew the attention of thousands of people, including Paige Paul, who has about 2 million followers across platforms, is married to a famous tennis player, and has been spending time on the island since she was a child. Paul, previously known as Paige Lorenze, declared the sign a misogynistic slight against an industry that is overwhelmingly female. The store’s owner, John Sylvia, said it was meant as a joke for locals, but the sentiment clearly came from an earnest annoyance: “A lot of people are tired of feeling like extras in someone else’s video,” he told New York magazine.

The fight felt freighted. Influencers today are a bit like plastic surgeons, or plumbers: On a societal level, many people sure seem to like what they do—they just don’t necessarily want to be right next to them while they’re doing it.

But influencers are unique in how they seem to be everywhere, particularly in places where people are trying to do things other than be on their phone to watch influencers. Of course we love the game and hate the player: It’s much easier to be annoyed by individuals than by concepts, especially when those individuals are, often, pretty annoying.

You’d need to be pretty clueless to not feel a little weird about the online attention economy and all it entails—the vanity; the grift; the slop; the desperation; the calculated intimacy; the endless consumption; the creeping sense that everything and everyone is actually just there to make you feel kind of bad about yourself and then sell you something. Social media can, of course, unite like-minded people, but it can also reward the kind of tribalist reactionaryism that can conflate disliking some women with disliking all women, or make an anti-consumerist folk hero out of a store that sells $2,750 baskets. The industry that Paul and her cohort belong to is unquestionably grim—but the industry isn’t walking around town with a selfie stick. There’s a reason that the sign doesn’t say no influencing, but rather no influencers.

by Ellen Cushing, The Atlantic |  Read more:

Image: Atlantic/Getty

[ed. I'm a great fan of guitar instruction videos because they teach you something. I guess you could call that a form of influencing. Some instructors have a wide audience and are influencial because of their teaching technique.The opposite (and there are many examples) are so-called "reaction videos" where someone listens to a song and simply records their "reactions". Who cares. Talk about bottom of the barrel. Same goes for opinion influencers, foodies and tons of other niches (Mukbang videos?). If all they have to offer is distraction or entertainment they're a waste of time.]

How to Get Chatbots to Give Accurate Financial Advice

Finding good financial advice can be stressful – and expensive. That’s one reason why chatbots have become an increasingly popular and free alternative.

But using artificial intelligence to answer your pressing money questions also carries hidden dangers. I’m a finance professor who has been closely watching the spread of AI into personal finance, and I recently warned that AI is riskiest when it sounds most confident. I advised readers to bring in a human professional for high-stakes financial decisions. [...]

For people who can’t afford ongoing advice, AI is genuinely useful for budgeting, paying down debt and low-cost investing.

The skill lies in using AI well. Here are some simple guidelines to get accurate and actionable answers when you engage with a chatbot: [...]

Five habits that make AI safer

Once the list of questions is set, here are some precautions to take once you engage with a chatbot.

Make it ask you questions first. Open with, “Before you advise me, ask me the questions a good financial planner would ask.” Generic answers come from under-specified questions, and you learn which details will actually produce a more useful outcome.

Ask it to argue against itself. After any recommendation, reply: “Give me the strongest case against this, and the situations where it would be wrong for me.” If it can’t engage in response, that’s a sign the bot is entering a more dangerous mode. This one precaution does more than any other to signal for you to be careful.

Make it show its assumptions. If the bot projects that your savings will grow to an impressive number, ask what assumption it made and what would change it. You’ll learn that it assumes steady returns every year, no missed contributions and no fees. That means the projection is just information, not a promise.

Verify the facts. Contribution limits, tax brackets and deadlines all change, and this is exactly where AI can be subtly out of date. Check the IRS or the Social Security Administration directly. If one number drives your decision, don’t take it on a chatbot’s word.

Never share identifying details. Don’t offer account information, Social Security numbers or logins. Describe your situation in general terms. Good advice doesn’t require handing over data that can be used against you.

by Pawan Jain, The Conversation |  Read more:

Image: Badhan Ganesh on Unsplash, CC BY

What Do Consultants Get Paid For?

A consultant I had lunch with recently is redesigning the loyalty program of a large airline. His team finished the analysis in two weeks. Months later the program still does not exist. This is because the purpose of the assignment is not to solve an analytical case study, but to figure out which redesign the parties will accept, and to get the people with authority to commit to implementing it.

I was not surprised to hear the story. In our just-published book Messy Jobs: The Work That AI Cannot Reach, Jin Li, Yanhui Wu, and I argue that a job is not a collection of independent tasks but a bundle of tasks and a position inside an organization. While many of the constituent tasks are clean, the job is messy because they must be combined under incomplete knowledge, conflicting objectives among the different parties and binding constraints on who has the authority to make decisions.

Hence we argue that automating the clean parts does not necessarily eliminate the job, because the remaining activities, tightly bundled with the rest, can remain the constraint. We argue that the bundle is strongest where separating the analytical/cognitive parts that can be automated would destroy local knowledge, trust, accountability or continuity.

Two objections

Critics of our argument raise two concerns. The first one has to do with advances in AI capabilities: models do some tasks extremely well and others badly. As they gain memory, use tools and acquire multimodal perception, critics would say, AI will get better at many other tasks like persuading, anticipating the objections raised in a meeting and adapting the tone. Hence even the interpersonal part by itself may not be a sanctuary for long. Just wait a bit for AI to get better, say the critics: Messy Jobs (in their view) describes the transition rather than the long run.

The second objection to our thesis is more radical. Maybe as long as we have humans in the loop, we need organizations. But if organizations really are a mess, slow, political, resistant to change, with a large role for humans precisely because someone has to hold meetings, build coalitions and learn the internal politics, why not get rid of the entire organization? What is the point of preserving the existing obsolete structures?

We believe that both objections fail, because some of the mess is substantive and necessary.

Where the “implementation” months go

To an outsider, my friend’s consulting project looks purely analytical. The team receives all the data, including all passenger records, redemption rates, customer-retention data, and so on. The team works out the key economic and financial trade-offs of the possible redesigns to figure out which redesign maximizes profits.

If doing this, given all the available data and the current AI tools, took two weeks, why has the project taken many months?

First, inside the airline, different parts of the business worry about different things. For instance, the salespeople have relationships with the hotel chains and do not want to disturb them, while the operations team worries about the staff at the airport counters who will have to deal with angry passengers who have grown used to certain privileges.

Second, there are the outside parties, from hotel chains to credit-card companies to the retailers that accept miles. Anything that improves the airline’s economics may reduce the value of the program to the hotels or to the card issuers. Each has a view on how card spending should count relative to flying, or how hotel nights should count relative to flying. There are winners and losers everywhere, and a reform that benefits the airline as a whole can hurt a particular business unit or a particular partner.

So the consultants spend weeks doing an enormous amount of work that looks peripheral to the problem. They repeatedly meet the head of the loyalty program, then the CFO, then the CEO. They also meet the commercial partners, and that means meeting the head of loyalty, then the finance team, then the chief executive. They revise the proposal. They redo the presentation.

And all of these people speak different languages. Organizations have different internal codes because they care about different things and deal with different problems. What the consultants are doing is a mix of analysis, translation and intermediation. The assignment of the consultants is to design a program that is an agreement that the relevant parties will authorize and implement.

Once the analysis is cheap, what remains is to learn what each party will actually accept, and to obtain commitments from those who are authorized to make them.

The real knowledge problem

An advocate of highly capable AI systems (“AGI-pilled”) would probably say this is a problem ready for AI. Have an agent redesign the program, have it meet the other constituencies, have it come back with a solution.

But what happens in those meetings deserves a closer look. There are four frictions in the room that make the meetings necessary.

by Luis Garicano, Silicon Continent | Read more:
Image: via

Frank Zappa: The MTV Interview

[ed. Man, I still miss the guy. I wish we had politicians this intelligent, direct and honest. Actually, not just politicians, everybody. Had a good laugh around 12:20, after he got done talking about John and Yoko stealing one of his songs.]

Feds Implement Temporary Water Sharing Agreement in Western States

Arizona, California and Nevada will be required to curb their use of the water from the Colorado River by about 20 percent over the next two years — and could ultimately face even larger cuts — according to three officials familiar with negotiations over a long-awaited federal plan to rescue the depleted river.

The plan, part of which the Bureau of Reclamation is expected to describe in an Environmental Impact Statement on Friday, comes at a time of escalating crisis for the Colorado, a crucial water source for seven states, 30 Native tribes and a swath of northwestern Mexico. But experts say it will not be sufficient to resolve a political standoff among the river’s many users or prevent the beleaguered waterway from teetering toward collapse.

The cuts proposed for the next two years resemble what the three states offered in a proposal this spring, and represent the first phase of a broader 10-year framework for operating the river’s dams and reservoirs, according to the officials, who spoke on the condition of anonymity to discuss ongoing negotiations.

That framework is expected to call for operating plans to be developed every two years and outline a wide range of possible measures those plans could include — including reducing the amount of water released to the Lower Basin by as much as 40 percent.

The framework is not expected to consider mandatory cuts to water use from the four states in the upper part of the basin: Colorado, New Mexico, Utah and Wyoming. Arizona, California and Nevada make up the Lower Basin. [...]

The current operating rules, which expire at the end of September, have not prevented chronic overuse of the river amid a decades-long drought worsened by climate change.

After a historically meager winter snowfall and a scorching spring, the amount of water flowing into the river this year is less than a quarter of average annual demand, and levels in its major reservoirs have dropped to record lows. Scientists warn that one or two more dry years could crash the entire system, disrupting hydropower production, drinking water supplies and irrigation for some 5 million acres of farmland. [...]

The likely operating plan for 2027 and 2028, based on a May proposal from the Lower Basin states, is projected to save about 3.2 million acre feet of water — enough to fill roughly 1.5 million Olympic swimming pools. The plan will require significant “belt tightening,” particularly in Arizona, according to Sarah Porter, director of the Kyl Center for Water Policy at Arizona State University, but states have indicated they can tolerate the reductions.

Yet those measures are only half of what studies suggest is needed to bring water demand in line with the dwindling supply, Porter cautioned, increasing the likelihood of even steeper cuts down the road. [...]

The 330-mile system of canals and aqueducts, which supplies water to the most populated parts of Arizona, is poised to see the biggest cut in its history under the bureau’s operating plan for the next two years. If the agency chooses to implement some of the deeper reductions considered in the 10-year framework, CAP’s entire water allocation could be wiped out. [...]

Fraught negotiations

Experts say the rising tensions on the river result from a chaotic combination of bad weather, poor planning, intransigent state officials and federal missteps under the Trump and Biden administrations.

At the heart of the conflict is an impasse between the Upper and Lower Basin states over who should shoulder the burden of necessary cuts.

In the Upper Basin, home to the snowcapped mountains and winding tributaries that feed the river, there are few reservoirs to provide long-term water storage, leaving users reliant on natural flows. That means the Upper Basin takes an automatic cut during dry years, officials argue. They say responsibility for restoring water to Lakes Powell and Mead should fall on the Lower Basin states that use them.

Yet about three-quarters of the people who depend on the Colorado live in the Lower Basin. The region is also home to major cities and sprawling farms that provide most of the nation’s winter vegetable supply. Officials from these states say they have already curbed their water consumption by millions of acre feet in recent years. Overuse of the river is universal, they argue, and so too is responsibility for saving it.

The situation is complicated by the arcane legal framework governing the river, which prioritizes users chronologically. Without agreements among the states, major cuts would fall entirely on junior users, including huge cities such as Phoenix and Tucson, before more senior rights-holders such as the farmers in California’s Imperial Valley see any reductions.
Last summer, it looked like states might agree on a new method of apportioning the river based on actual flow, rather than historical averages and legal agreements. But those negotiations broke down over familiar disagreements about who should be subjected to mandatory cuts. [...]

A vanishing river

Brad Udall, a climate scientist at Colorado State University’s Colorado Water Center, describes the tensions over the river as a “big collision of 19th-century water law, 20th-century infrastructure and 21st-century climate change and population growth.”

The Colorado has almost never contained enough water to satisfy everyone who has legal rights to it, Udall said, and human-caused warming has made the situation even worse. Since 2000, high temperatures and shifting rainfall patterns linked to climate change have diminished the amount of water flowing through the river by about 20 percent, compared to the 20th-century average.

The deficits have forced repeated negotiations over how to manage shortages. Past deals have helped curb consumption somewhat, but they were never stringent enough to reverse the inexorable decline of reservoirs that are intended to provide a buffer during bad years.

Lake Mead, the site of the Hoover Dam, is mere inches from its lowest level on record. A few hundred miles upstream, Lake Powell is approaching the point at which water can no longer flow through the turbines of the Glen Canyon Dam. That raises the risk of a phenomenon called cavitation, in which air bubbles form then implode in fast-moving water, releasing energy that can damage the dam itself.

“The reservoirs are depleted so low they’re really at the end of their capability,” Castle said. “We’re in such a precarious situation.”

by Sarah Caplan, Washington Post |  Read more:

Image: Caroline Brehman/Reuters
[ed. The U.S. Bureau of Reclamation on Friday unveiled the framework that will guide operations on the Colorado River through 2036. See also: Lake Powell's Dying Days (CCG):]

***

The L.A. Times’ Ian James reported that Trump’s Interior Department would accept a proposal submitted by California, Arizona and Nevada — the Lower Basin states — to slash their water use by 12%, 31% and 28%, respectively, through 2028. They’ll receive $350 million from Biden’s Inflation Reduction Act to support water conservation.

The Upper Basin states — Colorado, Utah, New Mexico and Wyoming — will get $100 million in conservation funding. But unlike their downstream neighbors, they won’t face mandatory water cuts. However much water they end up saving, that will be good enough. [...]

If Powell’s water levels sink much lower, water won’t be able to pass through the dam’s hydropower turbines, which generate cheap electricity for communities across the West. That wouldn’t be a “dead pool” situation; water could still flow downstream to the Grand Canyon and Lake Mead through bypass tubes lower in the dam. But the bypass tubes are surprisingly frail and could break with sustained use.

Translation: We are frighteningly close to “de facto dead pool.” That’s why the Trump administration is ordering everyone to use less water.

Well, not everyone. California, Arizona and Nevada are willing to cut back dramatically, and federal officials seem happy to make them do it. The Upper Basin states — the ones upstream of Lake Powell — say they shouldn’t have to commit to mandatory reductions, in part because they already consume a lot less.

In a New York Times opinion piece earlier this year, I argued that the Upper Basin states need to do more. Podmore agreed.

“It’s a tricky situation, because the Lower Basin has always used more water, and that’s a convenient argument for the Upper Basin,” he said. “But also, there’s more people in the Lower Basin. And the most productive agricultural land that’s irrigated with Colorado River water is located in the Lower Basin.”

“Even with the cuts that the Lower Basin has offered, we still have a long way to go to balance the water budget,” he added. “Everyone needs to pitch in.”

[ed. But not everyone is agreeing to pitch in: California’s Biggest AI Data Center Is Suing for Colorado River Water (Yahoo News):]

***

The developer behind California's biggest planned AI data center publicly swore it would never touch Colorado River water. It would run on recycled wastewater — clean, virtuous, zero environmental impact. That pledge held right up until the cities of Imperial and El Centro said no thanks. Now Imperial Valley Computer Manufacturing (IVCM) has sued the Imperial Irrigation District (IID) for access to the very river it promised to leave alone. The facility would sit in a desert valley where 180,000 people share exactly one freshwater source.

The Farm-to-Cloud Gambit

IVCM's legal strategy treats 160 acres of fallowed farmland as a water entitlement for a nearly million-square-foot AI campus.

The developer's playbook relies on a tactic called "buy and dry" — purchasing irrigated farmland, retiring it from production, then claiming its water allocation for industrial use.

China Now Uses 80% Artificial Sand

The world is running out of sand.

About 50 billion tons of sand and gravel are extracted annually, most of which is used for construction activities. This is a problem for two reasons. First of all, it’s not sustainable. Secondly, if we continue to extract sand at this rate, it will end up causing irreversible damage to the environment.

 

For instance, loss of sand from oceans, rivers, and beaches can lead to excessive flooding and degradation of marine ecosystems. It threatens coastal communities, and infrastructure. Plus, sand mining near aquifers can lower water tables, affecting water availability for humans, land animals, and agriculture.

And no, you can’t just use sand from the desert. Desert sands are typically rounded and smooth, which makes them less effective for construction purposes. For concrete, the rougher texture of river or beach sand is essential as it helps bind the materials together. Desert sand, with its finer and more uniform grains, lacks the necessary angularity to bond effectively with cement.

“The issue of sand comes as a surprise to many, but it shouldn’t. We cannot extract 50 billion tonnes per year of any material without leading to massive impacts on the planet and thus on people’s lives.” Pascal Peduzzi, a researcher at the United Nations Environment Programme (UNEP), told BBC.

A 2024 study suggests China may have found a solution to the sand mining problem. The Chinese have been using artificial sand made by crushing rocks and leftover materials from mining for many of their construction projects. This simple technique has allowed them to drastically reduce their dependence on natural sand without slowing down their massive construction projects. [...]

The study authors developed a monitoring system that allowed them to examine the sand use pattern in China from 1995 to 2020. Their analysis revealed many surprising facts. For example, the Chinese have been producing artificial sand since the early 2000s, but it became popular in 2010.

2010 was also the year when the supply of natural sand in China reached its highest level. However, the next year’s supply of manufactured sand overtook that of natural sand, becoming the primary sand type used for construction activities.

In the following years, production of artificial sand continued to increase by 13 percent annually. In 2020, the use of natural sand reduced to the extent that it accounted for only 21 percent of the total sand supply, witnessing an 80 percent decline compared to 2010.

“China’s overall sand supply surged by approximately 400% over the study period, yet the proportion of natural sand dropped from ≈80% to ≈21% due to the increasing use of manufactured sand,” the study authors note.

“The percentage of manufactured sand in the Chinese market could now be close to 90 percent. The shift from natural sand to manufactured sand is a miracle for a country that has completed such massive infrastructure construction,” Song Shaomin, a professor at Beijing University of Civil Engineering and Architecture, told SCMP.

by Rupendra Brahambhatt, ZME Science |  Read more:

Image: Nathan Cowley/Pexels

Will Larry Ellison Be the Face of the A.I. Bubble?

[ed. Don't miss this one. It's got everything (and could easily be a Pulitzer contender).]

On Jan. 21, 2025 — the first full day of the second Trump administration — Larry Ellison woke up in his 33-bedroom, 34-bathroom oceanfront mansion in Florida, got into his Gulfstream jet and headed up to Washington. Ellison, who was 80 and worth in the neighborhood of $200 billion, had an appointment at the White House. He didn’t bother to take a driver’s license — he needed to call someone on the president’s staff to vouch for him at the gate — but there he was, at 2 p.m., standing beside Donald Trump in the Roosevelt Room as the president announced “the largest A.I. infrastructure project by far in history” and told the world that his friend Larry Ellison was just the man to get it done. “He’s sort of C.E.O. of everything,” Trump said. “He’s an amazing man and an amazing businessperson.”

Ellison began by thanking Trump. “We certainly couldn’t do this without you,” he said. “It would simply be impossible.” He then proceeded to sketch out the ambitious plan. Ellison’s database software and cloud computing company, Oracle, and its partners — most prominently OpenAI — were going to invest as much as $500 billion over the next four years into a group of sprawling data centers, 500,000 square feet each, that would produce 10 gigawatts of computing power, using enough energy to power as many as 10 million homes. It was called Project Stargate, after the 1994 sci-fi movie in which Kurt Russell steps through a wormhole and finds himself inside a pyramid on an alien planet. This Stargate would be a portal leading humanity from the postindustrial era to the artificial-intelligence age. [...]

For Ellison, it was the capstone of a mad two-year scramble to transform Oracle into an A.I. juggernaut. The effort began in late 2022 when the launch of ChatGPT stunned the world and set in motion a race to master and control the most transformative new technology since the birth of the internet. Ellison, a founding father of Silicon Valley and the last of his generation still in the game, was desperate to avoid getting left behind. He’d moved quickly and aggressively — some might even say recklessly — to turn Oracle into a “hyperscaler,” one of the handful of companies providing the critical infrastructure that would power the A.I. boom. [...]

ChatGPT landed very differently in Washington than it did in Silicon Valley, setting off a scramble of its own inside the Biden administration to regulate the development of A.I. To oversee his A.I. policy, Biden turned to a veteran Democratic policy adviser, Bruce Reed, who believed that the administration needed to be proactive. A year after ChatGPT’s debut, in late 2023, Biden signed a comprehensive executive order on A.I., seeking to define the government’s role in the future of this new technology.

For the Biden administration, artificial intelligence was by no means just a domestic economic issue. Countries around the world were all racing to develop their own A.I. infrastructure and technology, and global power and influence would flow to whoever got there first. From this perspective, A.I. data centers were less businesses than geopolitical assets.

The administration was especially concerned about the A.I. ambitions of China and the Persian Gulf, given the powerful role artificial intelligence was likely to play in reshaping the information ecosystem. [...]

The administration’s concerns and Ellison’s ambitions were on a collision course. China and the Gulf were both critical to Ellison’s A.I. plans. Oracle already had a lot of contracts around the Gulf, and it also had a strong business relationship with one of China’s most important A.I. companies, ByteDance. Oracle was the U.S. cloud provider for the U.S. division of ByteDance’s TikTok, storing and securing the data of the app’s 100 million American users. But with ByteDance itself now pivoting into generative A.I., they had the opportunity to do more business together. In the summer of 2024, Oracle started working on a $6.5 billion deal to build a large data center complex in Malaysia, from which it could convey computing power to ByteDance and other foreign companies through opaque leasing deals.

It would be perfectly legal — but under the Biden administration maybe not for long. By that point, national security officials were growing increasingly concerned about China and the Gulf’s A.I. ambitions and were discussing ways to gain more control over them. The administration was especially worried about the role Oracle might play in fueling these ambitions. They knew that Ellison was trying to scale up the company’s A.I. infrastructure quickly and that it was badly in need of cash, which meant that it might be more tempted to make deals that the administration didn’t think were in America’s best interests. [...]

In early 2024, the administration started working with Congress on a bipartisan bill — the Protecting Americans’ Data From Foreign Adversary Controlled Applications Act — that would force ByteDance to divest its U.S. TikTok operations. Biden signed the bill into law in April 2024, setting a deadline of Jan. 19, 2025, for a sale. If ByteDance failed to meet the deadline, the app would be shut down in the United States.

At the same time, the administration was preparing to shore up its efforts to restrict China’s access to American computing power and to exert more control over the Gulf’s. In late 2024, it circulated the draft of a plan to require hyperscalers to go through a licensing process to operate overseas and to keep 50 percent of their computing power in America.

All of the hyperscalers were looking to build overseas, but Oracle had the most to lose: Its global plans were the most ambitious, at least relative to its size. The company publicly and aggressively opposed the Biden plan. Its top policy executive in Washington, Ken Glueck, called it “one of the most destructive” moves ever taken against the tech industry, arguing that the best way to solidify America’s lead in the artificial intelligence race was for U.S. companies to build and control as much of the world’s A.I. infrastructure as possible.

Biden signed off on the new policy in the final days of his presidency. It was scheduled to go into effect in May 2025. If enacted, it could force Oracle to scale back its ambitions in Malaysia and the Gulf. Ellison’s plan to transform Oracle was in trouble. But a new president was on his way to Washington.

‘The Tsunami’

Relief came almost immediately. Hours after his inauguration in January 2025, Trump sat down at the Resolute Desk and began signing executive orders aimed at dismantling Biden’s A.I. policies. He also signed an order directing his attorney general to hold off on enforcing the congressionally mandated TikTok ban for 75 days. And then, of course, came the Project Stargate announcement with Ellison and Altman.

Trump turned to a very different group of people to shape his new administration’s approach to artificial intelligence. He named as his A.I. and cryptocurrency czar David Sacks, a Silicon Valley venture capitalist who had raised many millions for the Trump campaign and, according to a New York Times investigation, was personally invested in at least 449 companies with ties to artificial intelligence. Sacks, who has denied any conflict of interest, believed that when it came to A.I., the government’s job was to get out of the way.

The National Security Council’s technology and national security division had played a key role in shaping America’s A.I. policy in the Biden years. Trump initially appointed David Feith — who had serious concerns about China’s ability to remotely access computing power through Malaysia and other Southeast Asian nations — to run it. But in April, he fired Feith and a few other China hawks and then eliminated the entire directorate. [...]

Trump saw another benefit to withdrawing the Biden plan: The Gulf states were adamantly opposed to it. They needed U.S. computing power to build out their own A.I. infrastructures and had something to offer in return. Their sovereign wealth funds were sitting on trillions of dollars that they were ready to invest in all sorts of American companies, including some connected to the Trump family.

Two weeks before the Biden policy was scheduled to go into effect, Zach Witkoff — son of the Trump adviser Steven Witkoff and chief executive of the Trump family’s cryptocurrency firm World Liberty Financial — made an announcement at a conference in Dubai: The Emiratis would use $2 billion of the firm’s brand-new stablecoin for an investment in Binance, a crypto exchange. Less than two weeks later — 48 hours before the Biden restrictions would kick in — Trump rescinded the policy.

That same day, Trump landed in Saudi Arabia, the first stop on a three-day tour of the Gulf. He was joined in the United Arab Emirates by Altman to announce Stargate U.A.E., a multibillion-dollar initiative to build one of the world’s largest data centers outside Abu Dhabi. Oracle would be a partner, too.

With the Biden plan dead, Oracle was free to operate its data center complex in Malaysia as it saw fit. By the end of June, the facility was on track to become the second-biggest in the world. Oracle doesn’t release the names of its customers there, but by studying its output, an independent A.I. research firm, SemiAnalysis, determined that the facility was feeding most of its computing power to ByteDance. An analyst at the tech-focused think tank ChinaTalk, Aqib F. Zakaria, ran his own numbers and arrived at a startling conclusion: Oracle was providing a staggering 22.6 percent of China’s known A.I. computing power.

by Jonathan Mahler, Jim Rutenberg and Kirsten Grind, NY Times |  Read more:

Images: Louie Psihoyos; Scott Ball
[ed. Not to be redundant but this came out shortly after I'd posted about Oracle (and Larry Ellison) below in The Hater's Guide to Oracle (Part 2). It contains a treasure trove of new information and a road map to how business and politics intersect in Washington and around the world these days. Well worth a read.]

The Hater’s Guide To Oracle (Part 2)

Oracle has one of the strongest mythologies in the tech industry. Ask a regular person and they’ll tell you that it’s “incredibly profitable” and “growing fast,” that it’s “unstoppable,” and that Larry Ellison has the mandate of heaven with regard to the continual sales of software and hardware related to databases and AI.

And those people are completely and utterly wrong.

The original title of this article was “Is Oracle Dying?” because I assume, when I took a deeper look, that there’d be some sort of debate, some sort of bull case for a decades-old quasi-hyperscaler run by one of the more nakedly-evil CEOs in the history of tech. I assumed — incorrectly, I might add — that Oracle as a business was doing fine other than the ridiculous commitments it made to support the whims of Sam Altman and OpenAI via deals that I believed (and still believe) will kill Oracle.

Except it turns out that Oracle has already been on a death spiral for the best part of a decade (if not longer) and has only survived this long by screwing its customers, taking on masses of debt, and — most importantly — more than $85 billion in acquisitions over the last 23 years. Pretty much every major product line outside of databases is a hodge-podge of other people’s innovation stapled together with a legendary contempt for the customer. These acquisitions (and continual price increases) are the only thing keeping the reaper from Oracle’s door other than margin-destroying GPUs. [...]

After April 2009’s $5.7 billion acquisition of Sun Microsystems, Oracle’s revenues barely kept pace with inflation until December 2021’s $28.3 billion acquisition of Cerner allowed it to create Oracle Health, adding about $6 billion in annual revenue that had 40% lower margins (about 21.7%) than Oracle’s other businesses, though Oracle immediately started closing offices and brutal layoffs to try and bring them up.

And as I mentioned above, Oracle’s other plan was to sink a little over $99 billion in capital expenditures since the middle of calendar year 2020 into AI GPUs. [...]

Oracle is a decades-long mission to keep reapplying lipstick to a pig. Billions of dollars of acquisitions have, for the most part, only succeeded in keeping the company’s revenue growth from going negative, and as noted by forensic accountant Howard M. Schilit, this is one of the most well-documented cases of accounting shenanigans being used to cover up that a business is in decline.

Today’s newsletter is a sequel to the Hater’s Guide To Oracle, where I told the sordid tale of how Larry Ellison grew a massive, lucrative business out of a database business that one reporter once told me was a “law firm with a database company attached,” an Enterprise Resource Planning (ERP) product that competes with SAP to create the most-annoying way to run a large company, and a business built around licensing Java that exists mostly to email people and say “you need to pay us for Java or we’ll sue you.”

Then, as I’ve mentioned, there’s Oracle’s cloud infrastructure business, a decade-old also-ran that was meant to compete with Microsoft Azure and Amazon Web Services, but only managed to catch up following the advent of AI GPUs and a movement where all it took to party was buying billions of GPUs and saying “gosh darn, we love AI.”

I originally started drafting this as a much tamer piece where I’d ask whether Oracle was dying, but as my editor and I started digging into the research, it became obvious that not only is Oracle dying, it’s been dying for years, kept alive through decades of acquisitions and a desperate and dangerous commitment to generative AI.

And AI, I believe, will be what eventually kills Oracle dead. [...]

With revenue plateauing and customers in revolt, Oracle’s future already looked murky, but with the power of AI — and $95 billion in FY2027 capex — it’s becoming increasingly clear that this may be Larry Ellison’s last dance with Silicon Valley.

by Ed Zitron, Where's Your Ed At |  Read more:

Image: Larry Ellison, Bloomberg/Getty

[ed. Larry Ellison. One of the most hated personalities in tech (and unfortunately, owner of my beloved island of Lanai, in Hawaii). Update: What a coincidence. There's quite a story in the NY Times that just came out about Ellison being the face of the AI bubble. See also: The Hater's Guide to Oracle (Zitron); Ellison Empire Beseiged On All Fronts (NC); and, this excellent series The Oracle Files by Drey Dossier on YouTube. (For example, this one: How Larry Ellison and Gulf Money Just Bought Your News):]

***

Warner Brothers Discovery shareholders are getting screwed on this new Paramount deal. Okay. And I would like to get into exactly how before they vote on Thursday, the largest media merger in American history is going to a shareholder vote. A merger worth in the ballpark of $111 billion in case you were wondering.

Which means that Warner Brothers, you know, the big conglomerate that owns CNN and HBO, is potentially getting folded into another conglomerate Paramount Pictures, which is the company that owns CBS, MTV, Showtime, and Nickelodeon. And the shareholder vote is April 23rd, this up coming Thursday.

And last Thursday afternoon, which is one week before the vote, Warner Brothers Discovery filed a 14 page correction to the document that shareholders are voting o n.

Now, this is kind of a big deal because this is a 14page addendum to the biggest media merger in American history. And this was filed on Thursday of last week, 4 days ago at this point. 

Now, public companies don't usually rewrite their own proxy statements a week before a shareholder vote, unless of course someone is forcing them to, which usually means that someone being one of their shareholders is suing them in order to do so. So, I checked to see if there were any lawsuits floating around out there, and what do you know? There is one. A shareholder named Donna Nikosia, apologies if I butchered that last name, filed a lawsuit on April 2nd saying that the original document left out a lot of information that shareholders needed in order to make an informed vote. 

And following Donna's lawsuit were 15 other shareholders who had sent letters more or less saying the same thing. And can we all just take a moment here and say thank you to Donna for filing what we all probably knew to be true in the back seconds of our heads that there is information being left out that you need in order to make an informed decision this upcoming Thursday. Now up top I just want to say that I am not a Warner Brothers Discovery shareholder. I have never owned a share of Warner Brothers Discovery or Paramount Pictures. I am just thanking Donna as a media consumer.

All right, and somebody who works within the media ecosystem because I like to keep my media independent and this deserves a lot more scrutiny than it's getting. So WBD, Warner Brothers Discovery, told the court that this lawsuit had no merit and then two weeks later slightly added the information.

Anyways, so this move in business, I've learned, is how you smother out a lawsuit without ever having to say that we are wrong. Now, we're going to get into what was in this correction in a second here because oh boy, were they leaving information out? [...]

You know, I read that 14 page new filing this weekend and there are two companies in it that WBD is still trying very hard not to have to say out loud and is trying even harder, it seems, to smother this from any of the news outlets taking this to the other shareholders. And I think I figured out which ones they're talking about. 

[ed. And this: Why Iran's Blockade is an Oracle Story:]

Most people know Larry Ellison as the Oracle billionaire, which true, you also probably know that he is the largest private donor to the Israeli military in American history.

He's given over $26 million to the friends of the IDF since 2014, including a single $16.5 million donation in 2017. That is the largest gift in the organization's history. And that is the part we have discussed at length. But here is the part that a lot of people don't know. Ellison is not just the largest funer of the Israeli military. 

His company is the operational backbone of it. According to Open Intel, Oracle holds a 26-year contract to build and operate the IT infrastructure for the IDF's intelligence campus in Negv. For clarity, that is the facility that houses unit 8200, Israel's signals intelligence and cyber warfare division and one of the largest listening bases in the world. That is a 26-year relationship extending into the 2040s between a private American company and the intelligence apparatus of a foreign military. 

And that's just the intelligence side because Oracle also runs the Israeli Air Force entire logistics system, the supply chain that tracks his spare parts for F-35s and F-16s, aviation fuel and mutations inventory. Oracle hosts an AI battlefield management system called Fireweaver that coordinates sensors and weapons on the battlefield in real time, which means that Oracle software is making targeting decisions in the kill chain for Israeli Defense Forces.

Chinese All-Terrain Robots

 

[ed. Holy crap. Unitree's "Super Athlete". It'll take your gear up or down a mountain with ease and do a little pirouette at the end.]

You Live In This Dump?

[ed. See also: 4 Prompts That Can Tell You What Chatbots Really Know About You (NYT).

Hundreds of millions of people worldwide who have embraced chatbots for web search, work and health care are still trying to understand the privacy implications of conversing with A.I companions. While it’s obvious to users that the chatbots keep a record of whatever they explicitly say to them in their questions and requests, what’s less clear are the inferences drawn about their behavior from those conversations...

To understand what the chatbots have figured out about you, try these prompts.

by Brian X. Chen,  New York Times/Archive Today |  Read more:

Image: Reddit

[ed. It's like Google Maps for humans.]

What Will More Intelligence Actually Do For Us?

In lots of sci-fi books, as soon as artificial superintelligence arrives, it bootstraps itself to even more godlike intelligence in an explosive “singularity” that rapidly transforms the entire physical universe. Lots of people, especially “AI safety” and “effective altruist” types, expected things to play out basically the same way in reality. But looking around, not much has changed since we entered the intelligence explosion. There’s a huge data center boom, and most people use AI on a daily basis, but we still live basically the same lives — driving to work or taking the train, sitting in front of a computer, scrolling on our phones, collecting a paycheck. People are staying in their jobs longer, but employment hasn’t been disrupted in a significant way:

A lot of people I know are surprised by this. Ruxandra Teslo writes:

Walking around the world today one might notice that it is weirdly unchanged…To many, this is surprising. Just the other day I was at a conference where someone remarked that if he could have seen today’s AI capabilities a few years ago, he would have been astonished — and would have assumed the world by now would look far more transformed, with much higher GDP growth.

Teslo blames bottlenecks — governance and other “frictions” — for the slow economic impact. But some others are advancing a more radical hypothesis — that intelligence itself is subject to diminishing returns.

One of these is Francois Chollet, an AI researcher who specializes in measuring AI’s capabilities. In a highly controversial series of tweets back in March, he conjectured that intelligence might be subject to diminishing returns:

One of the biggest misconceptions people have about intelligence is seeing it as some kind of unbounded scalar stat, like height. "Future AI will have 10,000 IQ", that sort of thing. Intelligence is a conversion ratio, with an optimality bound. Increasing intelligence is not so much like "making the tower taller", it's more like "making the ball rounder". At some point it's already pretty damn spherical and any improvement is marginal.

Now of course smart humans aren't quite at the optimal bound yet on an individual level, and machines will have many advantages besides intelligence -- mostly the removal of biological bottlenecks: greater processing speed, unlimited working memory, unlimited memory with perfect recall... but these are mostly things humans can also access through externalized cognitive tools.

In fact, this is a possibility I myself had raised in a post a year earlier:

It seems possible that humans are simply incredibly specialized in a few types of cognitive tasks — extracting patterns from sparse data, synthesizing various patterns into “intuition” and “judgement”, and communicating those patterns in language — and that we’ve basically approached the theoretical maximum in those narrow areas…That would explain why AI has gotten much better at things like math and coding and forecasting over the last year, but why the basic chatbot interface doesn’t seem much more “intelligent”. It would also explain why when you talk to Terence Tao about math, it’s like talking to a superhuman, but when you talk to him about where to get lunch or which movies are the best, he’ll just sound like a fairly smart normal dude. AI will eventually get better than Tao at math…but it may never get much better than the most thoughtful, eloquent humans at deciding where to get lunch or recommending movies. It may simply not be mathematically possible to get much better than we already are at that sort of thing.

Why would intelligence top out like this? Well, if we think of intelligence as the ability to extract information from data, then even an infinitely advanced model endowed with infinite compute will be limited by the fact that there’s a limited amount of information that can be extracted from the data.

For one thing, data itself is in limited supply. You can’t transform the world unless you can (in some generalized sense) understand it, and you can’t understand the world unless you can measure it, and our ability to measure the world is inherently limited and finite. [...]

So although we don’t know yet, it’s possible that humans were already hitting the point of diminishing returns with regards to individual cognitive capacity, and that superintelligent machines will never be as far beyond us as we are beyond dogs. But even if that’s true, I can think of at least three reasons why machine superintelligence could still deliver huge productivity gains. [...]

Distributed tacit knowledge

The German company Zeiss makes the best glass on the planet. If one of the mirrors that Zeiss makes for ASML’s EUV chipmaking machines were the size of Germany, the biggest bump on that mirror would be just one millimeter high. Only a few other companies — and maybe no other company on Earth — can match that. Zeiss’ mirrors also have a number of other amazing properties, like not distorting much due to temperature changes.

How does Zeiss make glass this good? No one knows — not even the people at Zeiss. If the technology were capable of being written down on a blueprint, China would have hacked Zeiss and stolen it, the way Huawei hacked Cisco and Nortel. If the technology were capable of being explained by a former Zeiss employee, or even several former Zeiss employees, China would have paid those people many millions of dollars to spill the beans.

Zeiss’ technology basically can’t be stolen, because it’s tacit and distributed. It consists of a vast number of little tricks and techniques that a huge number of individual employees use on a daily basis. These people don’t always even realize all those little things they’re doing that make the glass come out so good. And each employee knows a different set of tricks and techniques. The knowledge exists at the level of the organization itself, and is thus very hard to steal or recreate.

This is true of lots of corporate technology. A big part of the reason China can cut off the supply of rare earths to the rest of the world any time it wants to is that other countries aren’t very good at refining rare earths. Rare earths are difficult to separate from each other in solutions; it takes a ton of little chemistry tricks to do it cheaply at scale. Chinese refiners have spent four decades building up those little tricks and techniques; American or Japanese refiners won’t simply be able to replicate their efficiency overnight, and so it’ll continue to cost much more to produce rare earths outside China.

Except in the age of AI, this might change. Suppose American rare earth refiners give their employees a bunch of equipment to record everything they do — smart glasses, gloves, and so on — in addition to sensors distributed throughout their plants. AI will be able to synthesize all that information and very rapidly suggest small ways to improve the production process. Many of those little experiments will fail; others will succeed and will quickly be adopted, allowing another round of experimentation and improvement to begin very quickly. Crucially, AI’s ability to do this doesn’t depend on its raw intelligence — only on its ability to handle huge amounts of data very quickly.

In other words, in the age of AI, distributed tacit knowledge might not be nearly as big of a barrier to technological diffusion. This could improve economy-wide productivity, as lagging firms catch up to leading firms much more quickly. A more equal distribution of productivity would also make the economy more competitive, creating more surplus for consumers (though possibly reducing the incentive for firms to innovate, by making technology less excludable).

AI’s ability to quickly produce distributed tacit process knowledge might also supercharge productivity growth at the frontier. Imagine if any company could optimize any production process five times faster than today. The whole economy would speed up, as components got cheaper, turnaround times and product cycles got shorter, and scale-up got much faster.

And as with the previous example, improving the production of distributed tacit knowledge wouldn’t depend on AI’s raw intelligence. It would spring from AI’s ability to act like a computer — to interface directly with sensors, to handle lots of data, to perceive tiny details, and to do everything very very quickly.

by Noah Smith, Noahpinion |  Read more:

Image: Zeiss
[ed. Another thing I've wondered about: historians make a living unearthing little known facts and connecting dots from sources that are deeply buried in paper and microfiche respositories (and early data storage technologies - like 8 and 5 1/4 inch floppy disks). Millions of memos and correspondences that were once widely distributed and now sitting in dusty boxes or warehouses, archived somewhere. Items that could help significantly in understaning more about human judgement and decision-making. How much of this has been scraped for training? Very little, I'd presume.] 

Impulse Cooking Revolution

via: Impulse Labs
[ed. Not a recommendation, but I've been hearing more about these lately (for example, see this Wirecutter review):]

These models use the type of battery found in some electric cars; it stores power, which allows the appliance to run on a regular 120-volt outlet instead of the 240-volt version required for most electric stoves. Installing an appliance that runs on 240 volts can be expensive, tricky, and time-consuming, especially in older buildings with multiple apartments.

On the Impulse Cooktop, that battery can also produce a whopping boost of heat by channeling 10,000 watts to a single element — that’s 3,000 more watts than the next most powerful induction cooktop that I've come across in my research.  [...]

I also tested that battery-boost, and I can tell you one thing for sure: This baby does indeed get very hot, and very fast. On medium-high heat, a few tablespoons of oil in the bottom of a pan began smoking in two seconds.

And I'm rounding up.

In my previous tests of high-end induction cooktops, bringing 4 quarts of water to a full, roiling boil took eight to 10 minutes. On the Impulse Cooktop’s battery-powered boost setting, it took just under three minutes. That’s so astoundingly fast, I went around the office showing the timer to my colleagues.

***

[ed. It aint cheap:]

At $7,000 for a 30-inch model (and $7,600 for the 36-inch version), the Impulse Cooktop costs as much as the most expensive luxury models available, which are made by far more established companies. (You can, of course, get a great cooking experience from induction cooktops that cost a lot less.)

But for now, the Impulse Cooktop is in a category of its own. Even if it weren’t lightning fast and extremely powerful, the intuitive design makes cooking over induction so pleasurable that it’s even fun, especially the ability to control the heat down to the degree.