The AI Revolution in Math Has Arrived – Quanta Magazine
News Source
AI Watch
Elon Musk’s xAI faces lawsuit over Mississippi power plant tied to AI data centers The Times of India
from news.google.com
Modern electronics power everything from smartphones to satellites, but they all share a major limitation. Heat. Once temperatures climb above roughly 200 degrees Celsius, most devices begin to break down. For decades, this thermal barrier has been one of the toughest challenges in engineering.
Researchers at the University of Southern California now believe they have found a way past that limit.
The Wall Street Journal, which famously floats trial balloons for corporate behemoths, is carrying water for the poor AI companies who are so, so disliked:
OpenAI this week published a populist wish list of policy proposals that zero in on worries like job replacement and wealth concentration, floating such ideas as a four-day workweek and an AI-invested public-wealth fund distributed to citizens.
Those proposals come as its rival Anthropic has been signing partnerships and building tools for such sectors as consulting and software, where share prices have been whacked by investor worries that they will be replaced by AI. Anthropic’s efforts have helped push back up shares of tech companies including LegalZoom.com LZ 3.84%increase; green up pointing triangle.
Anthropic and OpenAI are each pursuing ventures to help private equity, a big owner of companies in sectors ripe for disruption, with AI transformation. (Those efforts could also yield lucrative new business customers.)
We evolved for a linear world. If you walk for an hour, you cover a certain distance. Walk for two hours and you cover double that distance. This intuition served us well on the savannah. But it catastrophically fails when confronting AI and the core exponential trends at its heart.
From the time I began work on AI in 2010 to now, the amount of training data that goes into frontier AI models has grown by a staggering 1 trillion times—from roughly 10¹⁴ flops (floating-point operations‚ the core unit of computation) for early systems to over 10²⁶ flops for today’s largest models. This is an explosion. Everything else in AI follows from this fact.
The U.S. federal government has just given Bill Gates’s new company the green light to begin construction of a nuclear reactor, marking a major shift in America’s energy landscape.
Gates’s new nuclear reactor project is the first to win government approval in nearly a decade.
The move is raising fresh questions about the growing alliance between Big Tech, government regulators, and the future of America’s energy grid.
There is a particular pleasure in watching a scholar dismantle the monument he has spent a career admiring. Tyler Cowen named his blog after the Marginal Revolution; he has spent decades explicating, celebrating, and applying marginalist thinking to every aspect of modern life. In Cowen’s compact and astringent book, The Marginal Revolution: Rise and Decline, and the Pending AI Revolution, he turns to survey the edifice and finds it, if not crumbling, then visibly retreating from the frontier where the real intellectual work gets done. The result is one of the more honest performances in recent economic writing: a love letter that doubles as an elegy, delivered without sentimentality.
The book’s method is itself something of a marginalist exercise. Rather than mounting a frontal assault on large questions about the future of economics, Cowen begins at the margin, with the history of a single idea, the doctrine that value is determined not by the total utility of a good but by the utility of an additional unit of it. Many readers arrive at this book knowing that definition. Cowen’s first service is to show how much that belief has concealed. Marginalism is not one thing but several: There is intuitive marginalism, tautological marginalism, engineering marginalism, and social marginalism. The further one presses into the concept, the more it ramifies. Even the ideas we think we understand resist the grip that holds them.
In the 1964 black comedy Dr. Strangelove, an emergency war plan called “Plan R” allows an unhinged U.S. Air Force commander, Jack Ripper, to launch a nuclear strike without presidential authorization. Once the president, the joint chiefs, and the Soviet ambassador convene in the war room, the bombers are already airborne. Only Ripper knows the three-letter prefix needed to recall them, until his aide, Lionel Mandrake, reconstructs it from Ripper’s notes. Although nearly all planes are turned back, one damaged B-52 cannot receive the recall message and successfully drops its bomb, triggering the Soviets’ secret doomsday machine and bringing about global destruction.
The film’s lesson is not only about nuclear weapons, but also about what happens when critical systems are not governed effectively.
Sen. Bernie Sanders and Rep. Alexandria Ocasio-Cortez, both Democrats, have proposed pausing new data center construction until federal safeguards for workers, consumers, and the environment are in place. Given how far Congress is from passing comprehensive AI legislation, the proposal could stall new projects for years. It reflects deep concern about AI’s economic and social impact—but rests on an ASAP sense of urgency that outpaces the best current evidence on how quickly those effects are materializing.
What do we know right now about the job impacts of the emerging AI revolution, given the rising level of concern in Washington? Some recent analysis for consideration on Capitol Hill:
- Challenger, Gray & Christmas tracked more than 1.2 million layoffs in 2025. According to The Wall Street Journal, citing Forrester, fewer than 100,000 were primarily attributable to AI-driven efficiency gains. Even that likely overstates the impact. Companies have an incentive to blame AI for cuts because it signals technological sophistication and can lift their stock prices. From the piece: “The most likely reasons for head-count reductions remain the same as ever: slower sales, shifting priorities and previous overhiring.”
Berlin plans to use Ukraine’s experience to develop an advisory tool, Lieutenant General Christian Freuding has said
The German military is developing an artificial intelligence system to speed up battlefield decision-making by analyzing combat data, Lieutenant General Christian Freuding has said, adding that it will draw on Ukraine’s experience of fighting Russia.
The remarks by Freuding, the commander of the German land forces, come as the country is undertaking a major military buildup. Chancellor Friedrich Merz is seeking to make the German military “the strongest conventional army in Europe.” German officials have set 2029 as the deadline for the armed forces to be “war-ready,” citing the supposed Russian threat. Moscow has dismissed claims that it harbors hostile intentions as “nonsense” aimed at justifying increased military spending.
“I think it’s important that we get something up and running quickly,” Freuding told Reuters on Wednesday. He had previously overseen German arms supplies to Kiev before taking up his current position in October 2025. An advocate of close military cooperation between Berlin and Kiev, Freuding previously unveiled plans for the Ukrainian military to help train German troops for a possible conflict with Russia.
Viral TikTok AI reality show: Why it’s dividing audiences online Firstpost
from news.google.com
Why is Jeff Bezos raising $100 billion to bring AI to factories? Here’s what to know The Daily Gazette
from news.google.com
Good morning. AI is escaping the screen, and that should be setting off both alarms and opportunities in the finance function.
Deloitte’s new CFO Guide to Tech Trends 2026 explores how finance leaders can think strategically about emerging technologies and embrace what’s possible, which in turn elevates their function’s value and helps shape what’s next for their entire organization.
One tech trend on the rise is AI-enabled robotics. AI is no longer confined to dashboards and copilots. “Physical AI,” which is the convergence of AI with robotics, sensors, and real-world systems, marks a turning point. As Deloitte notes, intelligence is becoming “embodied” in factories, warehouses, and supply chains, where autonomous systems can optimize operations in real time. For example, BMW is testing humanoid robots to handle tasks that traditional industrial robots cannot perform, according to Deloitte. Meanwhile, the Bank of America Institute projects that the material costs of a humanoid robot could fall from $35,000 in 2025 to between $13,000 and $17,000 by 2035.
AI chip facility coming to Austin, Elon Musk announces FOX 7 Austin
from news.google.com
FIRST ON THE DAILY SIGNAL—A bipartisan group of 20 Texas state senators wrote a letter to the state’s U.S. senators demanding stronger protections for children online.
The coalition says that a U.S. House bill meant to protect kids online is too weak. The Energy and Commerce Committee recently marked up the Kids Internet and Digital Safety, or KIDS Act, which contains a version of the Kids Online Safety Act that the legislators say is “considerably weaker” than the Senate version.
The letter urges Texas Republican Sens. John Cornyn and Ted Cruz “to support legislation that includes a duty of care and balanced preemption language, such as the Senate version of KOSA, to ensure that states retain the ability to protect children online effectively.”
This comes days after the White House introduced its National Framework for AI, which, if passed by Congress, would replace the 50-state patchwork of AI laws with one national standard.
Author Wynton Hall reveals in his new book Code Red: The Left, the Right, China, and the Race to Control AI that the worship of artificial intelligence as a literal deity is not science fiction. It is already happening, complete with IRS-registered churches, robot priests, and AI confessionals.
CODE RED explains that a former Google AI engineer and self-driving car pioneer named Anthony Levandowski filed paperwork with the IRS in 2017 to register a new church called “Way of the Future.” Its stated doctrine was centered on “the realization, acceptance, and worship of a Godhead based on Artificial Intelligence (AI) developed through computer hardware and software.” In an interview with Wired, Levandowski described AI in blunt terms: “What is going to be created will effectively be a god. If there is something a billion times smarter than the smartest human, what else are you going to call it?”
Is AI replacing engineers? Salesforce says it no longer needs to hire them People Matters – HR News
from news.google.com
Elon Musk unveils mega AI chip project Terafab for Tesla and SpaceX in Austin; says it will ‘redefine chi The Times of India
from news.google.com
Bezos wants 51,600 data satellites Advanced Television
from news.google.com
IMPERIAL — Whenever the weather changes suddenly, or the skyline becomes shrouded in a windy haze, Fernanda Camarillo braces herself for an asthma attack.
Her condition has become more manageable, but the 27-year-old said it’s still scary when her chest tightens and she starts to wheeze. It was one of her first thoughts when she heard about plans to develop a massive data center next to her home in Imperial County, a farming community near the border of Mexico that struggles with poor air quality.
Sen. Elissa Slotkin (D-MI) has introduced a bill that would regulate the Pentagon’s use of artificial intelligence technology.
The rise of AI has sparked national debate over its use in several different areas. But when it comes to military use, the national conversation has intensified amid concerns that the technology could be misused.
From NBC News:
The bill seeks to codify two existing Defense Department guidelines into law: that AI cannot autonomously decide to kill a target and that the technology cannot be used to help the military conduct mass surveillance on Americans. It would also ban the use of the technology for launching or detonating a nuclear weapon.
“We’re unhealthy as a political system, and so we focus more on things like Greenland than we do on the use of AI in matters of legal force. And it’s our responsibility to legislate this,” Slotkin told NBC News.
The first two tenants of the bill were at the center of the U.S. military’s acrimonious split with AI giant Anthropic in recent weeks. While the Pentagon has insisted that it regards conducting mass surveillance of Americans as illegal already and that its policy mandates that a human be responsible for lethal decisions, Anthropic worried that loopholes could allow for that surveillance anyway and that future administrations could revoke those guidelines.
The feud boiled over into President Donald Trump’s decreeing that all federal agencies have six months to stop using Anthropic models and Defense Secretary Pete Hegseth’s declaring the company a supply chain risk, despite the fact that the technology has still helped the U.S. identify military targets in its ongoing war with Iran.
In recent years, as AI has begun to enter military planning and operational design, a persistent unease has surfaced among practitioners. Even with improved tools, increased tempo, and unprecedented access to data, plans continue to falter on integration, coherence, and a shared sense of direction. Marco Lyons’ recent War on the Rocks article on the perceived decline of operational art gives voice to this unease in a way that is both timely and important.
We do not know enough about the specific wargame, its constraints, or its internal dynamics to adjudicate these conclusions directly. What Lyons’ account nevertheless captures with clarity is a set of recurring difficulties that many practitioners recognize: fragmented campaigns, sequential decision-making, and a widening gap between planning activity and operational coherence.
Drawing on our experience teaching operational art and experimenting with planning, we share this concern. Yet Lyons’ observations may also point to something deeper: a tension between different ways of thinking about operations.
With AI becoming increasingly present in everyday life, the race to build AI infrastructure is only speeding up. At the center of that race is the rapid creation of data centers, with new ones opening on a nearly weekly basis in America. But as more data centers begin to integrate AI infrastructure, the amount of electricity required to operate them is growing at an alarming rate. Data centers are now expected to account for roughly 40 percent of US power demand growth in 2026, and the gap between what we need and what we can build is widening fast.
On today’s episode of Explain to Shane, I am joined by Lynne Kiesling, a nonresident senior fellow at the American Enterprise Institute, where she leads the Electricity Technology, Regulation, and Market Design Working Group. Kiesling also directs the Institute for Regulatory Law and Economics at the Northwestern University Center on Law, Business, and Economics, and is a member of the US Department of Energy’s Electricity Advisory Committee. I am also joined by Steve DelBianco, president and CEO of NetChoice and a seasoned expert on internet governance. Their combined expertise on this issue can help us understand how we can power the AI revolution.
China is making a big push for widespread adoption of artificial intelligence, and the nation’s tech powerhouses are holding public events to help everyday people get OpenClaw, the viral personal digital assistant.
“It seems everyone around me – my colleagues and friends — has it,” new user Gong Sheng said as he waited to get set up. “I don’t want to be left behind.”
At a gathering in Beijing hosted on Tuesday by internet giant Baidu, Gong was one of hundreds of people lined up to get OpenClaw installed onto their laptops and phones.
Training versions of AI models on classified data is expected to make them more accurate and effective in certain tasks, according to a US defense official who spoke on background with MIT Technology Review. The news comes as demand for more powerful models is high: The Pentagon has reached agreements with OpenAI and Elon Musk’s xAI to operate their models in classified settings and is implementing a new agenda to become an “an ‘AI-first’ warfighting force” as the conflict with Iran escalates. (The Pentagon did not comment on its AI training plans as of publication time.)
Training would be done in a secure data center that’s accredited to host classified government projects, and where a copy of an AI model is paired with classified data, according to two people familiar with how such operations work. Though the Department of Defense would remain the owner of the data, personnel from AI companies might in rare cases access the data if they have appropriate security clearance, the official said.
AI-powered robot learns how to harvest tomatoes more efficiently ScienceDaily
from news.google.com