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AI Data Centers and the Concentration of Wealth

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This essay was written with Nathan E. Sanders, and originally appeared in The Guardian.

Opposition to AI data centers has emerged as a primary theme in US politics, one that—surprisingly—doesn’t fall along party lines. We applaud people coming together for constructive debate on any issue, and agree that communities need to evaluate whether any economic benefits these data centers bring is worth their costs. Still, we worry that a focus on data centers obscures the larger impacts of AI on people’s lives: the concentration of power of AI companies, and their widespread political and financial influence.

Local data center opposition is grounded in legitimate concerns about misallocation of land resources when housing is at a premium, pressures on already higher energy prices, and localized environmental impact. Unlike other resource-consuming and polluting industrial facilities, data centers produce very few jobs. The fact that US opposition to data centers seems to be most fierce among lower-income communities reflects righteous indignation with an inequitable bargain, where tech companies and developers profit from exploiting local resources but offer little in return. On a global scale, their carbon footprint could grow unsustainably if usage accelerates. And all this is in aid of a technology that many fear will propagate misinformation, take their jobs, or even cause existential risks for humanity.

For some, data center opposition may feel like the only tangible mechanism for registering their concern, disapproval, or even anger about AI. The problem is that this may be exactly what the AI companies are banking on. They can overcome the protest when it matters to them, and live with a significant fraction of proposals being defeated. More importantly, focusing political opponents on the data center issue obscures the bigger prize they’re after.

While there is a staggering three-quarters of a trillion dollars being spent on data center infrastructure by US companies this year alone, this investment should be taken in perspective. The market for enterprise software, for example, is about twice this size. And it’s small compared with what these companies actually want.

AI companies have their eyes set on capturing all the value created by entire industries. The technology has arguably already conquered customer service and consumer sales. But on the horizon are bigger targets, such as enterprise software development, creative design, management and even legal services. In AI companies and their allies’ vision of the future, AI replaces teachers and doctors. The companies would rather spend time fighting resistance to how fast they are building computing infrastructure than dealing with issues of how their products should be used in those fields, or how those fields should be protected from their products.

And while data center opposition campaigns have been successful in building widespread appeal, their effectiveness in the US is mixed. They seem to be most successful when organizing against speculative, early-stage data center proposals that have a relatively low likelihood to ever see fruition. Meanwhile, advanced-stage, well-capitalized data center projects have proven to have the resources to overcome local opposition. An OpenAI- and Oracle-backed facility in Saline township, Michigan, is breaking ground on construction even after local officials voted to reject it. The developers sued the town of 3,000 and forced a settlement that involved their project going forward. Meanwhile, the Trump administration, a vigorous ally of corporate AI, has signaled its willingness to advance AI infrastructure development by overriding state objections and even using federal lands.

Also consider that rampant data center development may be a momentary spike rather than a longstanding concern. Demand for the centralized computing that data centers provide may well decline over time. The leading Chinese labs, such as Z.ai, are innovating in technical mechanisms to make frontier-class models smaller and cheaper to run. AI power users have become adept at miniaturizing open weight models, ones published free for anyone to download and use, to run locally on their own computers. Apple and Google both support infrastructure stacks for running AI models directly on mobile phones. It could be that the current mania for data centers will look like the fiber optic cable bubble from the early 2000s, as demand shifts to smaller models and AI usage on people’s own devices.

For those concerned primarily with affordability and environmental protection, singling out data center construction is misplaced. Energy rates and inflation today seem to be most visibly affected by the US-Iran war. The US is disinvesting in long-term energy security by ceding the renewable energy industry to China and actively cancelling climate commitments. Consider that 10% of global carbon emissions stem from heating buildings, which dwarfs energy use by AI and could be cut fivefold by using heat pumps powered by renewable energy. With respect to housing affordability, federal housing subsidies have changed little over three decades, in inflation-adjusted terms, even as housing costs have spiked and homeowners have enjoyed robust tax incentives.

As for AI itself, the concentration of power and wealth in these tech companies is the greatest existential risk facing society today. This means we must limit corporate power, especially corporations’ ability to exploit the public and manipulate our political system.

Opposing data centers should be just a starting point. We can advocate for states to regulate AI, to reject irresponsible uses of the technology, and shape corporate behavior. We can fight for AI computation to be taxed, so that the public can capture some of the profit of AI use while also forcing AI companies to internalize more of the energy and environmental consequences associated with its use. And we all can join the global movement for Public AI, an alternative ecosystem for AI that is developed under public control with an incentive structure to create public benefit rather than private profit.

The US midterm elections present ample opportunity for those seeking to control the AI political agenda. In the recent New York congressional Democratic primary, PACs linked to the dueling AI companies Anthropic and OpenAI spent millions of dollars lobbying for or against “AI safety“, the idea that we must urgently monitor and prevent people from using AI to cause catastrophic harms. We’re already seeing a similar dynamic play out in races in Massachusetts and other states.

Why would Anthropic and OpenAI—bitter industry rivals but fundamentally on the same side politically—support opposing viewpoints? Because they both ultimately profit from the mystique: the idea that their products are so powerful that controlling those products is the world’s most important challenge. Here’s the typical read on the dynamic. To one side (backed by OpenAI affiliates), “safety” comes from the appearance of US industry dominating AI innovation, under the slow-moving control of federal lawmakers (and without pesky state regulators in the way). To the other side (backed by Anthropic), “safety” means a heavier regulatory framework that plays to Anthropic’s posturing as the ethics- and compliance-focused AI vendor. In both cases, it’s more marketing than principled concern about safety.

Political organizers should call out and reject the AI companies’ framing of the debate, and reorient campaign agendas around populist resistance to corporate concentration of wealth and power. When AI companies pump millions into legislative races, the result should not be hyperbolic discussion of AI superintelligence. And when a plot of land in a small town is pitched as a data center site, the debate should be about more than the local costs and benefits. It should include out-of-control money in politics, and Citizens United-proof solutions to limit corporate influence like public financing and state regulation.

We all have a vested interest in what’s on the policy agenda, and what the outcomes are. Today, the greatest risk AI poses to society is the exacerbation of inequality and the concentration of wealth. The real problem is trillion-dollar AI companies and their trillionaire oligarchs cozying up to political power in Washington and governments worldwide, and using their money to enact their agenda over the popular will of the people. This is the issue we’d like to see put front and center, and it requires solutions much more extensive than slowing data center development.

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petrilli
11 minutes ago
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Seattle, WA
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Samsung chip division's single-year profits beat its past 40 years of profits, combined, due to increased memory and storage prices — Samsung passes Nvidia to become most profitable company in the world, notches 19x quarterly increase in profit

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Samsung announced stellar results last night, noting a 19x quarterly increase in operating profit, allowing the firm to pass Nvidia as the most profitable in the world. Kim Yong-Kwan, president and head of corporate management, strategy, and operations for Samsung Electronics' Device Solutions (DS) division, said that the semiconductor unit's 2026 operating profit will exceed everything it has earned across roughly 40 years in the chip business at a company town hall last Friday, according to a report published Monday by Korea JoongAng Daily.

Brokerage consensus puts Samsung's full-year 2026 operating profit near 300 trillion won ($196 billion), and its second-quarter figure at about 84.6 trillion won ($55.1 billion). Samsung easily beat the consensus with $58.5 billion when it posted preliminary results on July 7, overtaking Nvidia's most recent quarterly operating profit of $53.54 billion and becoming the most profitable technology company in the world for the period, on the back of AI-driven memory demand.

Samsung's DS division booked 53.7 trillion won ($35.1 billion) of the company's 57.2 trillion won in total operating profit during the first quarter of 2026, roughly 94% of the total, which is why the division's projection sits so close to Samsung's full-year consensus.

"This year's profit will exceed the cumulative profit generated over the past 40 years since we entered the semiconductor business," Kim Yong-Kwan told staff, scoping the claim to the chip business rather than the wider conglomerate.

Samsung entered the semi space by acquiring Korea Semiconductor in 1974 and shipped its first 64Kb DRAM in the mid-1980s. SamMobile estimates the division's cumulative operating profit from 1985 to 2025 at under 300 trillion won. Samsung's smartphone, display, and appliance businesses have earned far more than that over the same period, so the record applies to memory and logic chips, not to Samsung overall.

Contract prices for DRAM and NAND have risen steeply through 2026 as AI server demand outran supply, pushing memory makers toward 40% to 50% operating margins on NAND in the first half of the year. Prices for 12 GB LPDDR5X modules have reached about $145, and Samsung is negotiating further commodity DRAM increases for the third quarter. The DS division's earnings move with those contract prices, and Samsung has told customers to expect tight supply through at least 2027.

Samsung is releasing preliminary second-quarter figures on July 7, so these record projections are still estimates. The reported profit will also absorb a profit-sharing agreement that pays chip workers 10.5% of DS operating profit as stock, worth as much as $26.6 billion this year. SK hynix is due to report its own second-quarter results on July 29, and analysts expect the two companies to post combined operating profits near 150 trillion won for the quarter.



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petrilli
5 days ago
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Absolutely normal things.
Seattle, WA
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DARPA plans 30-year endurance nuclear waste batteries to power next-gen drones, says report — project SYMPHONEE aims to harvest Strontium-90 to power persistent military drones

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Batteries that can last decades between recharges or renewals are the stuff of tech enthusiast dreams. However, DARPA’s ‘Rads to Watts’ program could bring forth unrivaled portable power, lasting decades, via the development of a new class of radiovoltaic devices. Morgan State University recently won a $3.37M DARPA contract to advance this tech, and a report by Defense One suggests upcoming nuclear waste-powered batteries could last as long as 30 years and power next-gen drones.

Morgan State now has a considerable sum to keep its researchers employed on a project dubbed SYMPHONEE (Strontium-Yttrium Multi-junction PIN-based High-Density Output Nano-system for Extreme Environments). Radioisotope power sources have been used for quite some time in low-power draw applications such as smoke detectors and space systems for decades. However, the new initiative, led by Morgan State and with team members such as Northrop Grumman, PNNL, Project Omega, ARA, and Widetronix, aims to take the tech into the next generation. More specifically, under the auspices of (and with funds from) the 'Rads to Watts' program, they are aiming to build next‑generation radiovoltaic micro‑power systems for extreme environments.

The proposed next-gen power cells make use of radioisotopes extracted from nuclear waste, especially Strontium‑90. Research partner Project Omega has already made some devices and will build the DARPA prototype. We noticed that it has published a promotional video that highlights sea drones with a 10-year battery life, for example. Coordinated by Morgan State researchers, PNNL labs will handle nuclear materials/testing, Northrop Grumman and ARA will provide AI-driven modeling, with Widetronix designing nuclear micro‑generator radiovoltaic converter architectures.

“Our team is pushing the boundaries of radiovoltaic technology, developing high-power, long-life systems that were not previously achievable,” said Professor Michael Spencer, the technical lead for the project. “By integrating advanced materials, device engineering, and nuclear science, we are laying the foundation for a new generation of persistent power systems for extreme environments.”

radiovoltaic battery advances
Project Omega
radiovoltaic battery advances
Project Omega

With this research, development, and fabrication powerhouse assembled, it is hoped a step change will be achieved to boost radiovoltaic micro‑power system power density. The goal is to be able to power persistent autonomous operations in remote or difficult-to-access environments like space, underwater, and contested regions – for decades. A Northrop Grumman rep emphasized the potential of a ‘persistent power source’ becoming available for “next-generation defense systems.” Project Omega is also interested in developing “persistent underwater security systems” – sea drones.

It is also somewhat positive to imagine that substances long considered to be highly undesirable waste products could end up being strategic assets.



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petrilli
7 days ago
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Good thing there's no way that flying radioactive waste around could possibly end badly.
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Free The Icons

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With last year’s release of MacOS 26 (Tahoe), Apple made a mess of app icons. In the first betas of MacOS 27 (Golden Gate), however, there are signs of a turnaround. We’re urging Apple to continue making improvements, by restoring the ability for MacOS app icons to have distinct shapes.

Apple’s Liquid Glass App Icons

In Tahoe, Apple modified the icons for dozens of their first-party apps to give them a “Liquid Glass” appearance. The changes were a substantial regression, leading to blurry, dumbed-down icons.

Two Automator icons, one pre-Tahoe with a detailed robot and one on Tahoe, with a hard-to-distiguish robot face.

With the recently unveiled Golden Gate, Apple has again updated their MacOS app icons. This time, however, the changes are genuine improvements. Here’s the refined Automator icon, for example:

The newer icon is sharper, with superfluous Liquid Glass removed. Dozens of Apple’s apps have seen similar updates. The result is that Golden Gate’s icons are superior to Tahoe’s, as this comparison from Basic Apple Guy shows. Seeing these improvements led me to think about another fix Apple should make in MacOS.

The Problem of Tahoe’s Dictated Squircles

With the Tahoe release, Apple didn’t just mess with their own icons. They also dictated the shape of every third-party app icon, forcing them to adopt the same prescribed squircle. Any icon that failed to do so found itself shrunk down and imprisoned in an ugly gray background, in order to fit Apple’s desired aesthetic.

Audio Hijack outside of, and inside, icon jail
Audio Hijack’s icon as it used to appear, and in Tahoe icon jail

To avoid this icon jail, developers were forced to redesign their icons to match Apple’s preferred form. After decades of beautiful, memorable Mac icons in varying shapes, Tahoe flattened personality to obtain bland uniformity. The platform is worse for it.

Past icons weren’t just more expressive. They were also more usable. Having distinct shapes provided a useful way to tell icons apart. Tahoe eliminates that cue by forcing everything into the same squircle, leaving color as the primary way to tell icons apart at a glance.

That falls down if you’ve got color vision deficiency, or even just multiple icons with similar color schemes.1 I’m looking at you, Slack and Photos. I have to look closely, because it’s so difficult to tell you apart now.

It Doesn’t Have to Be Like This

Apple’s prohibition on shapes is a step backward for both usability and creativity in app icons. Icons are now harder to distinguish because they’re no longer allowed to be distinctive. But there’s no technical reason for it. Apple could, and should, once again allow icons to take on a wide variety of shapes.

It’s clear that some people within Apple recognize that the transition to Liquid Glass introduced mistakes. They also appear to have the authority to fix those mistakes. Refinements to Apple’s own icons in Golden Gate are a welcome course correction, as is the much-celebrated Liquid Glass opacity slider. It’s time to correct the mistake of banning icon shapes as well.2

Apple should stop forcing every icon into the same squircle. Let’s return to a world of gorgeous app icons like these:

A collection of gorgeous old school icons

Free the icons.


Footnotes:

  1. With color now so critical to tell icons apart, it should be no surprise that the new “Clear” and “Tinted” icon styles added in Tahoe are seeing so little uptake. As Adam Engst noted, “[I]t’s nearly impossible to identify a particular app when they’re all clear or tinted squircles, as you can see below. My brain just shuts down when it sees them.”

    A sea of identical-looking icons on Tahoe, all tinted blue

    I’m not sure this “Tinted” style would be a good idea even if these icons had distinct shapes, but I know it’s a very bad one given their uniformity. ↩︎

  2. For folks within Apple, this was feedback filed as FB23388490 (“Third-Party App Icons Should Not Be Restricted to Apple’s Dictated Squircle Shape”). I imagine it is a duplicate many times over. ↩︎

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petrilli
14 days ago
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Seattle, WA
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Meta Is Testing Facial Recognition for Police and Military

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We know that ICE wants to deploy eyeglasses with facial recognition that can identify people in real time.

Turns out Meta is prototyping the feature with a Pentagon supplier. (Alternate news story.)

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petrilli
15 days ago
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As if you needed more reason to avoid Meta and work for their destruction.
Seattle, WA
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Lilbits: 8TB SD cards are coming soon (likely for a small fortune)

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It’s been more than two years since SanDisk announced plans to launch 4TB SD cards based on the SDUC standard. They haven’t actually arrived yet, so take this next part with a grain of salt, but during the Computex show in Taiwan earlier this month, SanDisk indicated that those 4TB SDUC cards really are coming […]

The post Lilbits: 8TB SD cards are coming soon (likely for a small fortune) appeared first on Liliputing.

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petrilli
32 days ago
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Available for a modest $1B.
Seattle, WA
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