In September, OpenAI announced that its new artificial intelligence technology needed less than a week to solve the Navier-Stokes problem, a mathematical puzzle that bedeviled the world’s smartest humans for decades. In the weeks that followed, the company released a deluge of additional findings that stunned leading mathematicians and raised new questions about the future of an academic field that has long been viewed as the pinnacle of human achievement.

But the implications of A.I.’s newfound mathematical skills extend well beyond academic research. Using similar techniques, Silicon Valley is now building A.I. systems that aim to eliminate the dangerous flaws, or “bugs,” in the world’s computer software. Just as an A.I. system can prove a math problem, it can prove that a software application is bug-free — at least in theory.

This sweeping effort to guarantee the integrity of computer software, which scientists call “software verification,” is vitally important as the internet faces its biggest cybersecurity threat in decades. Now that the leading A.I. systems can hack into computer software, by identifying and exploiting its flaws with stunning speed, the world needs a new breed of A.I. that can remove these flaws.

&Truth, a new start-up based in Palo Alto, Calif., is among the many companies working to build this kind of technology. Much like the Silicon Valley start-ups Axiom and Logical Intelligence and leading A.I. labs like Anthropic and OpenAI, &Truth hopes to verify the world’s software using a specialized computer programming language called Lean, the same tool that allows A.I. technologies to solve million-dollar math problems.

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“Using the same techniques that allowed A.I. technologies to crack a million-dollar math problem, researchers are building new systems that aim to solve the world’s cybersecurity crisis.” https://t.co/dpHfCT2BOL

— Christina Ayiotis, Esq., CRM, CIPP/E, AIGP (@christinayiotis) October 30, 2026

American spy agencies had gathered striking intelligence.

A top executive at a Singapore-based data center company was under scrutiny for possibly steering advanced Nvidia A.I. chips to China. And now American officials had concluded that she was a Chinese intelligence asset, funneling information to Beijing.

But what came next was even more alarming. Surveillance of the executive, Alice Huang or Huang Le, a Chinese citizen, revealed that she had developed a close relationship with Jensen Huang, Nvidia’s chief executive.

For years, Washington has worked to deny China the technology needed to match or surpass the United States in the intense global competition for superiority in artificial intelligence. The discovery that Beijing was getting reports from someone with direct access to Mr. Huang, one of the most powerful figures in the A.I. revolution as well as an influential ally of President Trump’s, set off alarms at the White House.

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Wow.https://t.co/ovzrTKn4CR https://t.co/VlJTst2k4X

— Ryan Mac 🙃 (@RMac18) October 29, 2026

As A.I. systems have grown increasingly powerful over the past several years, decoding the inner workings of these technologies has only become harder. In 2014, Google’s Inception technology spanned several million “neurons,” the fundamental mathematical calculations that drive an A.I. system. The latest systems span trillions.

The trouble is that no one seems to know what each neuron is doing. When an A.I. system learns a particular concept — like recognizing a car or a cat or a suit tie — it spreads these ideas across multiple neurons in ways that even experts cannot understand. Researchers call this “superposition.” And if they can’t disentangle this phenomenon, the implications could be profound.

In coming years, many businesses, governments and individuals may be reluctant to turn to A.I. technologies because they don’t have a detailed understanding of how these systems work. If they can’t pinpoint why a system made a particular choice, they may not trust it. And if they do put their trust in A.I., they could open themselves up to liability when the technology makes serious mistakes, particularly when A.I. systems are used in sensitive areas, like diagnosing diseases at hospitals or helping the police identify perpetrators in photographs.

When Mr. Cammarata started an interpretability project at OpenAI three years ago, he estimated that less than 2 percent of the neurons inside an A.I. system could be properly understood. Now that he has a new way of looking at the problem — which involves a phenomenon he calls “recursive generalization” — he thinks that he can understand the behavior of more than 90 percent of neurons.

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New York Times @nytimes: Did the Hardest A.I. Problem Just Get Much Easier? – The New York Times. #MachineLearning #AI #aiact https://t.co/nN5DZlk7HL

— Nordic AI Institute (@nordicinst) October 27, 2026

When Anthropic goes public as soon as next month, its initial offering will be more than just a coming-out party for the artificial intelligence company. It will also be a litmus test for the economy, with trillions of dollars at stake.

Anthropic, which makes the Claude chatbot, is a tent pole of the A.I. industry. Valued in the private markets at nearly $1 trillion and backed by more than $130 billion in funding, it could raise $100 billion in its offering and promptly become one of the world’s biggest public companies. But the stakes are even higher than that.

Anthropic and OpenAI, its chief rival, sit atop a pyramid of business partners and suppliers — infrastructure providers, chipmakers, energy companies and A.I. start-ups — that have all spent heavily over the past four years because they believe demand for A.I. products will keep growing.

Anthropic’s listing will provide the first in-depth look at the health of a key business underlying the A.I. boom — and will be a test of its durability. Is there unending appetite for A.I. services to justify the spending on chips, data centers and other infrastructure? Or will Anthropic’s performance show that there are limits?

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What’s Riding on Anthropic’s Market Debut? Nearly Everything.https://t.co/8kyw2Ujt0M

— Darius Radzius (@DariusRadzius) October 26, 2026

Christian charities and campaigners have condemned the Government’s approval of the Jackdaw gas field in the North Sea. Tearfund and the Scottish Catholic International Aid Fund (SCIAF) have called for the decision to be reversed.

They emphasised the consequences for communities already suffering from climate change, and urged government ministers to refuse permission for the much larger Rosebank oilfield.

The Government announced on Wednesday that the Energy Secretary, Miatta Fahnbulleh, had agreed that the regulator could grant consent for gas to be produced at the Jackdaw field. The Labour Party promised in its election manifesto not to issue any licences to explore new oilfields and gas fields, but Jackdaw already held a licence.

Ms Fahnbulleh said on Wednesday: “This decision will support the country’s energy security with home-grown gas this winter and help minimise the UK’s use of imported higher-emission fuels as we continue our transition to renewables and nuclear. The decision is compatible with our legally binding climate commitments, and we remain resolute in ending new licences for oil and gas and achieving net zero by 2050.”

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Christian charities and campaigners have condemned the Government’s approval of the Jackdaw gas field 🌊 in the North Sea #ChurchTimes #ChurchNews https://t.co/mcw9bY1Jnn

— Church Times (@ChurchTimes) October 23, 2026

Frequent AI use, defined as daily or weekly use, is not yet the norm across the U.S. workforce, though its adoption has increased sharply in the past three years. In the AJQS data collected January-March 2026, 28% of employees reported using AI at least weekly, while 54% said they had not used AI in their role. Differences in use reflect, in part, the nature of people’s jobs: Not all roles involve regular access to digital devices or have obvious opportunities for employees to use AI directly.

Roughly half of employees in the professional and business services, financial activities and information/media industries regularly use AI. Meanwhile, healthcare support, manufacturing production and retail sales employees have low levels of usage, with 70% to more than 80% never using AI in their role.

Regular AI use is more common among employees with higher levels of education and those in management positions. College graduates are more than twice as likely as those without a college degree to say they use AI on a daily or weekly basis (40% vs. 17%, respectively). In addition, 37% of managers versus 25% of individual contributors are regular AI users.

Younger workers, who have grown up with the latest technologies, are not among the most frequent users of AI at work (about one in five use it weekly or more). Yet among AI users, employees aged 18 to 24 are the most likely to say AI has led their employer to ask them to take on more responsibility, at 38%, compared with 31% or less in every other age group.

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🗞️ IN THE NEWS 🗞️ American employees who use #AI at work mostly report gains in speed and creativity, but new @Gallup research finds that the benefits are not evenly shared across the workforce. More details in this @Inc article: https://t.co/RwHotsFpGO #artificialintelligence

— Inc. Arabia (@inc_arabia) October 20, 2026

Two spectres talk financial markets. One is the fear that surging bond yields will make the rich world’s shaky public finances unsustainable, triggering a nasty fiscal crisis. The other is the worry that the revenues from artificial intelligence needed to keep the data-centre boom going will fail to arrive. As we report, that would devastate credit markets and cause a big fall in stocks, too.

The good news is that only an Ichabod Crane would think that both these scenarios could strike at once. Instead, investors must decide which story is scarier. For now, The Economist is more worried about sovereign debt.

For most of the year, concerns about governments have dominated. Between the end of February and the start of October, the yield on 30-year US Treasuries rose by a full percentage point. The Iran war has sent inflation up and forced central banks to raise interest rates. Strong economic growth and the rush to build data centres have caused a scramble for capital in which governments have had to compete with the private sector. In Japan, Britain and especially France, investors have fretted about the ability of governments to service their debts.

In recent weeks, though, the prospect of an end to the AI boom has scared the markets more. The five-year bonds of CoreWeave, a “neocloud” that rents out data centres, trade at a 15% yield, up from 10% in July. The company’s share price has fallen by about a third in the past month. The slowing revenue growth of Anthropic, an AI-model provider, has investors worried that the cash CoreWeave and its peers need may not arrive, or at least not quickly enough to pay their creditors. Interlinked financing means that pain could spread quickly, through both the ai supply chain and the private-credit and insurance firms that hold a lot of data-centre debt.

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For most of the year, worries about governments’ sovereign debt have dominated. Yet in recent weeks the prospect of an end to the AI boom has scared the markets more. Only in a big crash akin to the global financial crisis of 2007-09 would the two collide https://t.co/80gVNhvOZ9

— The Economist (@TheEconomist) October 22, 2026

The actress Christina Applegate, who received a multiple sclerosis diagnosis in 2021, said on Tuesday that she had been unexpectedly plunged back into uncertainty after a doctor told her she didn’t have multiple sclerosis after all.

“This may come as great news, but to me it comes as like I’m back at square one,” Ms. Applegate said on “MeSsy,” a podcast she hosts with the actress Jamie-Lynn Sigler. She broke into tears as she described the doctor’s words: “She came into my room and she said, ‘Congratulations, you don’t have M.S.’”

“Well, I was not happy at all,” she said, explaining that her symptoms did not go away when the diagnosis did. “Everybody else was so happy.”

“You don’t get misdiagnosed and then all of a sudden I’m better,” she added.

The about-face, Ms. Applegate said, doesn’t mean she’s not sick anymore. It means she’s still sick but doesn’t know why — a common experience for people with complex chronic illnesses, and one Ms. Applegate already went through for years before receiving her M.S. diagnosis.

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Misdiagnosed: Christina Applegate said she learned she was misdiagnosed with multiple sclerosis five years ago. She tells how she’s “back at square one." https://t.co/kNKf8xbrBd

— NBC4 Washington (@nbcwashington) October 20, 2026

The benefits and risk cloak more central driving factors among AI titans: the will to power, the desire for wealth, the hunger to be in charge. The sheer technological sweetness, too—the hard problem followed by the elegant answer. Scientists involved in technological breakthroughs always have a sweet spot.

But about four years ago, when reports of AI’s advancement began to break through to people paying attention, there was no declared objective: “We’ll split the atom, win the war, put man on the moon.” There was no clear product or labor-saving device. AI simply promised to change everything. It would create intelligence itself, an artificial but superior version of human intelligence. Then we’d figure out what to do with it, and what it will do to us. It will transform the human condition. For better or worse? Let’s strap in and find out.

Our society, our country, never decided to “do” AI. History will be perplexed by this. Something so big, so epochal, and people had no say? There was no vote, no debate. Some people started to do it and raise capital, and we shrugged. “It’s the next step.” As Sam Altman said early on, electricity, computers, the internet—now this. Americans always take the next step.

The creators and owners of AI might be pressed to answer the question: Exactly what purpose were you pursuing, and how, with a sense of the downsides, did you expect us to like it?

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From @WSJopinion: History Raises Its Eyebrows at the Week in AI by @Peggynoonannyc https://t.co/diQJHPj1c5

— The Wall Street Journal (@WSJ) October 18, 2026

The robot takeover looks a lot different from what we see in Hollywood thrillers.

Even as artificial intelligence-powered humanoid robots dance, box and beat human running-speed records, the physical bots showing up in our daily lives in Los Angeles are less Terminator and more R2-D2.

On a Wednesday afternoon at Ralphs on Pico Boulevard, a skinny, six-foot-tall tower of sensors rolled through the aisles. It made low beeping noises, its lights flickering purple and green. A small screen on the top of the tower had two blinking eyes and a small line of text. “Hi, I’m Tally!”

“Robot! Robot!” a young boy yelled. Some adults looked confused; others laughed.

Ricardo Valadez, a 62-year-old real estate agent from Mid-City and Ralphs regular, said he felt like the robot was stalking him around the store but was reassured by an employee that it just checks the shelves to see what is missing or out of place.

“I was kind of like, ‘What the hell is that?'” Valadez said. “I don’t know why; I felt that it was following me.”

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Page One, @latimesThe “AI Employee of the Month” 🤖 https://t.co/mSrxwtqQFz

— Carl Quintanilla (@carlquintanilla) October 16, 2026

Nearly five years into its fight for national survival, Ukraine has entered a moment of intense vulnerability, under growing pressure not only from Russia but also now from the United States.

A double blow came overnight on Wednesday.

Ukraine said that its military, with no warning, had lost some critical access to a military version of Starlink, a pillar of its battlefield communications. Kyiv relies on the satellite internet network, known as Starshield, which is paid for by the Pentagon. That led Ukrainian officials and analysts to surmise that the restrictions had come from Washington, as President Trump is locked in his latest feud with Ukraine’s leadership.

At the same time, Russia unleashed dozens of ballistic missiles in a broad attack on Ukraine’s energy infrastructure early Wednesday, cutting power to 600,000 people in the capital, Kyiv. It was a dark omen for a rapidly approaching winter in which Russia is gearing up to try to push Ukraine to the breaking point as Kyiv runs low on lifesaving air defenses.

It was unclear how long the Starshield restrictions would remain in place. Still, the Trump administration’s treatment of Ukraine has caused outrage in a country already reeling from a string of challenges.

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Ukraine’s Vulnerability Grows as Starlink is Restricted and Russia EscalatesKyiv has found itself increasingly vulnerable. A huge attack cut power to 600,000 people there, and a Pentagon-funded satellite program appeared to be curbed without warning. https://t.co/igpM7s86S9

— Sjoerd Nolf (@SjoerdNolf) October 14, 2026

Top executives at Anthropic, OpenAI and other AI companies are privately gaming out scenarios for a public and political revolt after a catastrophic AI event. These officials anticipate a large-scale event, most likely a cyberattack, that shuts down access to financial services, internet connectivity, or even power and water.

The first example of significant real-world harm caused by unsafe AI would turn an already wary public further against the technology and its leaders, including Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman, as well as President Trump for his reluctance to regulate it.

While scenario planning is common within many companies and national security settings — the Pentagon has been running war games for decades — the difference is that many top AI researchers and executives believe a major incident is inevitable.

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⚠️ 🤖AI companies plot "the day after"Top executives at Anthropic, OpenAI and other AI companies are privately gaming out scenarios for a public and political revolt after a catastrophic AI event. Why it matters: These officials anticipate a large-scale event, most likely a cyberattack, that shuts down access to financial services, internet connectivity, or even power and water. The first example of significant real-world harm caused by unsafe AI would turn an already wary public further against the technology and its leaders, including Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman, as well as President Trump for his reluctance to regulate it. Threat level: While scenario planning is common within many companies and national security settings — the Pentagon has been running war games for decades — the difference is that many top AI researchers and executives believe a major incident is inevitable. "OpenAI conducts preparedness exercises where teams discuss and work through a range of potential scenarios," a company spokesperson said. "These scenarios are not treated as inevitable, but are meant to help us prepare for a variety of circumstances." Anthropic declined to comment. Zoom in: The blame game will start whether a rogue-agent swarm breaks containment from an internal testing environment or a bad actor finds unexpected ways to use available models. A recent campaign targeting South Korean financial organizations — including reported breaches at two banks — shows the damage one person can do. A hacker from China allegedly used AI tools from China-developed models, including DeepSeek, to steal data from tens of thousands of bank customers. The attacker used Claude Code to ask for help finding places to sell the stolen data, according to cybersecurity firm CrowdStrike. Top AI planners assume Democrats, ascendant after the midterms, will move fast to shut down AI but will face significant challenges. An aging Congress, out of touch with the AI revolution, could find itself out of its depth. The global economy is now heavily intertwined with an AI infrastructure buildout. Slowing it down could hit an already fragile economy hard. Too many open-weight models can already be freely downloaded and used to cause harm, a problem most cybersecurity pros see as solvable only by using AI to fight rogue AI. Between the lines: The planning involves red-teaming for worst-case scenarios. It focuses mainly on racing to educate members of Congress. Company executives know regulation has no chance of passing right now, but still want to shape the legislation and policies U.S. leaders will turn to after a first catastrophic event. What we’re watching: Many AI industry insiders told Axios they believe a major event will occur in the next six to 12 months. Even with Democrats in control of the House and Senate, the companies see fractured politics as the norm, including within the Democratic Party. Some of the most heavy-handed Democratic proposals include banning superintelligence or pausing advanced AI development. Others have bipartisan support and even some industry buy-in, including a required kill switch on advanced AI. But experts have questioned the viability of trying to turn off all AI systems. The bottom line: In a real crisis, Washington can set partisan differences aside. One Democratic aide pointed to cooperation during COVID and the 2008 financial crisis. AXIOS

— Ares, Information Service (@Aresinfoservice) October 10, 2026

Stephen Huff was about to get married when he had a scan to investigate why he had been feeling short of breath. He was a fit 29-year-old who had played professional baseball and never smoked, so he wasn’t expecting the diagnosis: stage 4 lung cancer. “I had multiple spots all in my lungs, my neck, my spine, my liver, my brain – just everywhere,” he says. “I put on a brave front, but deep down I was terrified. I didn’t know if I’d be here in six months.”

Luckily for Huff, his mother, a cancer researcher, encouraged him to get a new kind of test that is quietly revolutionizing treatment. Rather than focusing on the place in the body where the cancer originated – for example, the lungs, bowel or skin – the new approach focuses on genes. The aim is to pinpoint the exact mutation driving the tumor, so it can be switched off with targeted drugs that act like guided missiles.

Through this fresh approach, Huff “hit the lottery” – as his oncologist told him – because it meant he could be treated with a recently approved drug that specifically targeted the genetic alteration driving his cancer. Within weeks, Huff began to feel better. “My first scan showed that basically every tumour site had either shrunk or gone away completely,” he says.

Now, thanks to this precision oncology method, more and more people like Huff are surviving cancers that were once considered a death sentence, like lung, pancreatic and brain cancer. “Being able to identify exactly what makes a cancer tick is having an incredible impact,” says David Thomas, a pioneer of precision oncology at the University of New South Wales in Sydney. But surprisingly, it has received little fanfare outside of the medical community so far.

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A revolutionary way of targeting tumors could beat even the worst cancersWe have long treated cancer based on its location in the body. But a whole new approach that analyses tumors differently is now helping people survive forms of cancer that were once considered a death sentencehttps://t.co/eLjdh5vd1zhttps://t.co/GekaZnFhSP

— David Ullrich (@DavidUllrich202) October 13, 2026

For years, AI scientists have been warning that the technologies they are developing are technologies they don’t know how to control. Those concerns were largely ignored in America’s Congress. In 2024 members of California’s delegation in Congress took the extraordinary step of asking Governor Gavin Newsom to veto a then-pending state AI safety bill. The risks, they said, were “hypothetical”. The Terminator, they reminded the governor, was science fiction.

But the invasion of Hugging Face, an AI-development platform, by an OpenAI model earlier this summer has begun to change Washington—and terrify the public. “The truth is,” Representative Ro Khanna tweeted, “for too long, too many of us did not give enough weight to the warnings of AI safety activists…I was one of those many, and I was wrong.” Mr Khanna has now joined an array of members from both parties to propose the FRONTIER Act, an ambitious regulation of the most powerful models, tied to pre-empting state regulation. Senator Bernie Sanders has proposed even more aggressive limits on AI development.

These proposals are good starts. But they are both too much and too little. It is too early to silence state regulators, and not enough to focus on the risks caused by the most powerful models alone. Instead, we need an approach that advances AI safety generally while avoiding the developments AI scientists are most fearful of.

Four changes by Congress would do that and provide time to work through the immensely complicated questions that will follow.

First, it should expressly allow competitors to agree to slow development while safety technology is improved. 

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Lawrence Lessig and Yoshua Bengio suggest how to reduce serious risks without abandoning American technological leadership https://t.co/ZA1TP9vVT7

— The Economist (@TheEconomist) October 13, 2026

Most adults worldwide use social media, and among younger adults, nearly everyone does. Across 97 countries surveyed by Gallup so far in 2026, a median of 81% of adults say they have used some type of social media in the past seven days, rising to 95% among those aged 15 to 29.

Findings from the latest State of the World’s Emotional Health report challenge some assumptions about what that widespread use means for wellbeing. The analysis reveals a modest, complicated relationship that varies by time spent using social media, age and where people live.

With social media so embedded in daily life, the findings are particularly relevant at a time when the world’s emotional health is under considerable strain. Worry, stress, sadness, anger and physical pain all remain well above the levels Gallup measured two decades ago. What is less understood is how much social media is associated with this rise in negative emotions.

For this study, Gallup classifies adults as low use (no use or less than 30 minutes a day), moderate use (30 minutes to less than two hours) or high use (two hours or more). After accounting for factors that can influence wellbeing metrics such as these, moderate use is associated with fewer negative emotions than high use and more positive experiences and higher life evaluations than low use. As with many things in life, moderation appears to yield more optimal wellbeing outcomes.

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As part of the World Health Summit, Gallup has released new data from 97 countries on social media use and wellbeing.Globally, there is no substantial relationship between time spent using social media and wellbeing.This finding is remarkably robust. It is true for youth populations (N=26,700 youth 15-29) and for all ages pooled (94,460 adults 15+). It is true with or without extensive controls for internet use, employment status, physical health, age, gender, country effects, education, income, social support. It is true for linear and quadratic use effects. It is true for heavy use, defined several ways. In fact, in some models no use or light use predicts the worst outcomes, but the effects are always very small.However, associations vary widely across countries. In most countries, there is no effect. In Africa, associations between social media use and wellbeing are insignificant or even positive! In USA, CAN, AUS, ISR, & parts of Europe, social media use predicts negative wellbeing.Effects of social media among the youth are among the worst in the USA, raising interesting questions about differences in content and underlying mental health across youth populations.

— Jonathan T. Rothwell (@jtrothwell) October 12, 2026

xercise may be a more powerful tool for pain relief than many people realize, according to a large analysis spanning hundreds of thousands of participants.

Pain often makes movement feel like the wrong choice. Yet a large new analysis suggests that exercise can reduce pain across conditions ranging from osteoarthritis and migraine to neurological disorders, inflammatory diseases, and cancer-related pain.

Researchers at Adelaide University analyzed 157 systematic reviews covering 2,736 randomized controlled trials and 221,279 participants. Across that evidence, exercise was associated with reductions in both acute and chronic pain, making the study the most comprehensive synthesis to date of exercise as a pain treatment.

The results challenge the assumption that harder or longer workouts are necessary for pain relief. Lower intensity and shorter duration programs produced greater reductions in pain, while meaningful benefits were also seen in programs totaling less than two hours of exercise per week.

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Exercise Can Improve PainA pooled meta-analyses (n=197,392) shows that exercise reduced pain versus control immediately after the intervention (SMD −0.59; 95% CI −0.65 to −0.53; P<0.001). The benefit held across musculoskeletal, inflammatory, neurologic and cancer pain, and for every modality tested.https://t.co/rJKmocxTZl

— Dr. John Cush (@RheumNow) October 8, 2026

O God, our heavenly Father, who didst raise up thy faithful servant Robert Grosseteste to be a bishop and pastor in thy church and to feed thy flock: Give abundantly to all pastors the gifts of thy Holy Ghost, that they may minister in thy household as true servants of Christ and stewards of thy divine mysteries; through the same Jesus Christ our Lord, who liveth and reigneth with thee and the Holy Ghost, one God, for ever and ever. Amen.

Robert Grosseteste (1168-1253), Bishop of Lincoln, proposed that God created light in a central point with matter attached. As this light expanded in all directions like a bubble, the attached matter stretched causing it to take form. It’s eerily similar to Big Bang cosmology. https://t.co/SwXImtDUZC

— Dominion Mandate Scientist (@Romans8Shaman) August 15, 2026

As the United States and China vie for A.I. dominance, the Trump administration has made it more difficult for companies to hire foreign researchers, while China has made recruiting the world’s best scientists a national priority.

Over the past two years, China has flung open its doors to international researchers, introducing a visa for scientists and offering lucrative research grants.

Despite those efforts, foreigners are not coming.

Worse still for China’s ambitions, the number of Chinese scientists working in the United States has risen rather than declined, according to a new study about global A.I. research.

For every 30 Chinese researchers in the United States working on artificial intelligence in 2025, only one in China made the opposite journey, according to the study, conducted by the Carnegie Endowment for International Peace, a think tank.

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In Race With U.S., China Struggles to Recruit Foreign A.I. Researchers https://t.co/GRZEJwCxsX "Worse still for China’s ambitions, the number of Chinese scientists working in the United States has risen rather than declined, according to a new study about global A.I. research."

— Bill Bishop (@niubi) October 6, 2026

I was due to be a Gen X-er. By waiting a week past my due date, I not only lost my father his 1980 tax deduction but also became a Millennial. Not that being born in the first few days of a sociologically designated generation (or claiming a cool label like “Cusper” or “Xennial”) is really that much of a distinction. But I have come to realize that entering one’s generational cohort at the beginning of an arbitrary twenty-year span means not being quite so wholly subsumed in the zeitgeist as are one’s slightly younger peers.  

Add to that a family whose scant middle-class means and slight Luddite tendencies meant that we were never technological early adopters. Multiply that by a choice to homeschool when such an election still produced a marked cultural wince. Subtract any culturally defiant choices such as those of my friends who did not even own a television. It totals a childhood not outside the mainstream culture—certainly not paddling against it—but holding water as the cultural drift moved us all along.  

From the vantage point of midlife, I am deeply grateful for an upbringing that walked through the ’80s and ’90s with a good deal of cultural foot-dragging, but I have also come to believe that this sort of cautious, reluctant, belated travel through innovation is beneficial to everyone in every generation at every time. Most of us cannot drop off the grid, but almost all of us can wait a little longer before buying into new technologies for our homes and families. These small “not yet” choices help to form us and our children into more intentional and humane people, better able to use technology than to be used by it, and to assess the loss that accompanies technological advance as well as the obvious gains.  

I can remember the time before my family bought our first microwave. Or television with a remote control. Or cordless phone. Or VCR. Or computer. Moreover, in most cases, I also recall a vague, childish knowledge of the grownup discussions going on for months before such innovations were ceremoniously purchased and ensconced in our home. In the haziness of memory at least, I am aware of a prevailing ethos that we didn’t really need that new technology, not in any pressing way.  

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A California pastor named Justin Lester has built a digital twin of himself using nearly 2 million words from his sermons, books, and other messages. The artificial intelligence–generated clone offers counsel around the clock to hundreds of people in Vallejo, a city in the Bay Area. The New York Times, which reported on Lester, said the AI twin talks in the pastor’s cadence. It has comforted a woman the night before heart surgery, advised a person who felt despair over a lost job, and generated a letter for a homesick child at camp.

Lester is not alone in searching for ways to incorporate generative AI into Christianity. The creators of one AI-infused app, called Bible Chat, have created another sort of digital chaplaincy that allows users to confess their secrets and sins to a chatbot, and ask it for insight about how to interpret the bible. Bible Chat has been downloaded more than 30 million times. Other “faith tech” tools are also on the rise.

I’m sure most of us already sense something is off here, and plenty has been written about the obvious concerns with the technology: Can a chatbot pray for you? (No.) Can it know you? (No.) Can it be trusted to tell you the truth when the truth costs something? (No.) I won’t use this article to rehearse those arguments. Instead, I will focus on our existing problems, as Protestants, with spiritual authority and how AI technology that provides spiritual guidance threatens to make it a lot worse.

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(CT) ‘The New York Times, which reported on Lester, said the AI twin talks in the pastor’s cadence. It has comforted a woman the night before heart surgery, advised a person who felt despair over a lost job, and generated a letter for a homesick child at camp’ https://t.co/eimklPp9eQ #faith #parishministry #ordainedlife #technology #ai #21stc

— Kendall Harmon (@KendallHarmon6) October 5, 2026

This summer, a cybersecurity company called Tenzai entered a three-month-long hacking contest, racing to find vulnerabilities in computer networks operated by governments agencies, banks, hotels, airlines and other businesses.

The contest, called HackerOne, has become a real-world proving ground for the latest artificial intelligence technologies, including Claude from Anthropic and GPT from OpenAI. Over the past year, these technologies have improved to the point where they can pinpoint holes in computer networks with stunning speed, fundamentally changing the nature of cybersecurity.

But in winning this extended contest — a result announced on Thursday morning — Tenzai did not use technology from Anthropic or OpenAI. It used A.I. systems built by the Chinese start-up Z.ai.

The feat demonstrated the enormous power of Chinese A.I. technologies that are freely available on the internet.

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A hacking competition shows the power of China’s approach to AI https://t.co/de62ucivxL

— The Straits Times (@straits_times) October 1, 2026

America’s landscape is undergoing one of the largest transformations in decades. The country houses nearly 100 hyperscale data centers, which consume at least 100 megawatts of power at peak operation — enough to power about 80,000 homes.

There are another 120 under construction, according to Cleanview, a market intelligence company tracking data center development. Four hundred and sixty more are planned. Roughly 40 percent of today’s hyperscale data centers were built on previously developed land. The rest took over farmland, shrubland and forest.

Data centers have existed for years but have never been quite this large. “Traditionally it’s just one building situated in an urban area,” Adams said. Now, hyperscalers start with one building and then expand to “two, three, four, five, six buildings.” Meta is constructing a data center campus called Hyperion on a tract of land in rural Louisiana that will dwarf Manhattan’s Central Park. The project is huge but may soon be overtaken. If all the data centers currently planned are built on schedule, according to Cleanview’s data, by 2030 the Hyperion campus will rank only at No. 5 in the U.S. by square footage.

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America’s landscape is undergoing one of the largest transformations in decades.

To meet the insatiable demand for computer processing to power AI, tech companies and their developers nationwide are building ever-larger data centers. https://t.co/dGFucHTl8D

— The Washington Post (@washingtonpost) September 28, 2026

Some computations are so hardcore that it takes a facility of extraordinary power to even think about running them.

These are the supercomputers – massive facilities humming with the corpulence of their GPUs and CPUs, crunching applications that would take a desktop computer hundreds to thousands of years.

A commercially accessible quantum computer has just accomplished a feat that suggests this newer technology could one day leave supercomputers in the dust.

In just 19 seconds, IBM’s Nighthawk r2 processor generated a million samples – a task estimated to take a supercomputer around 110 years.

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A Quantum Computer Just Did in 19 Seconds What Could Take a Supercomputer 110 Years https://t.co/sdqaoE9yKO

— Randy Kemp (@randylewiskemp) September 29, 2026

A.I. has made the gap between policymaking and technology one of the widest ever, according to more than 20 interviews with lawmakers, technologists and policy experts. Many governments are torn between wanting to harness A.I. and fearing its risks. And they are further mired by national politics, limited technological know-how, geopolitical divisions and reluctance to fall behind in a race that could shape economic power and national security for decades to come.

Many countries are waiting for the two leading A.I. nations — the United States and China — to take a cue from their A.I. policies. Yet in the United States, the Trump administration has been divided over A.I. safety, with President Trump saying regulation would hurt innovation and cede ground to China. China itself has imposed some rules on A.I., especially to censor chatbot content, but also raced ahead with development.

“There’s this assumption that there are adults in the room on this issue, but there are no adults in this room,” said Sean Ó Heigeartaigh, director of the AI: Futures and Responsibility Program at the University of Cambridge, who is a member of a European Union advisory board on A.I. “That is what makes all of this so completely terrifying.”

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A database of predicted structures for nearly every known protein on Earth is being upgraded to better represent some of the least-known and deadliest species: viruses.

Researchers added more than 8,000 virus protein dimers — pairs of interacting molecules — to the AlphaFold Protein Structure Database on 24 September. The resource contains predictions of the 3D structure of proteins, which are generated using the AlphaFold2 artificial-intelligence tool and made publicly available. The added proteins come from 23 virus families, all with human-infecting members, and are part of the launch of a ‘pandemic preparedness portal’ within the widely used and freely available AlphaFold database.

Earlier this year, researchers added predicted structures for 1.7 million pairs of interacting proteins from 20 widely studied organisms, including humans, mice and tuberculosis-causing bacteria. This marked the first time that protein complexes — such as enzymes comprising two identical protein strands — had been included in the AlphaFold database, which is maintained by the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI) in Hinxton, UK.

“Many viral proteins do not act individually, they act in concert with partners,” says Joe Grove, a molecular virologist at the University of Glasgow, UK, who was part of the effort to add viral complexes to the database.

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A database of predicted structures for nearly every known protein on Earth is being upgraded to better represent some of the least known and deadliest species: viruses.

Researchers added more than 8,000 virus protein dimers — pairs of interacting molecules — to the AlphaFold… pic.twitter.com/jarQwaigzD

— Flavian (@bullish1312) September 25, 2026

Robots — the sector Mr. Xi first championed in his 2014 speech — have been a particular success. China has more than 2 million robots in its factories, more than in the rest of the world combined. Some Chinese researchers have argued that robots may be more promising for achieving general-purpose intelligence than large language models — Silicon Valley’s chosen method — because they can learn from interactions with the physical world.

Those rapid gains have fueled anxiety in Washington, where fears of being overtaken by China have become the main argument against reining in A.I. A congressional advisory group warned that China’s quick adoption of A.I. in robots and other practical applications would generate huge amounts of new data that could then be used to further improve its models. In July, the U.S. government proposed restricting imports of humanoid robots, a move Beijing denounced as discriminatory.

For people like Mr. Liang, the robotics company founder in Shenzhen, the signs of China’s progress are already all around.

He still admires American entrepreneurs, but he no longer looks only to them for inspiration. He wears smart glasses from Huawei. He has hired interns from American universities who are eager to learn from China’s robotics expertise.

“Before, we all used American technology as the benchmark, and we’d joke about ‘C-to-C’: ‘copy to China,’” Mr. Liang said. “I think it’s the mission of this generation of Chinese entrepreneurs to let the world know that some Chinese companies are different.”

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How China’s Leader Plans to Win the Future With A.I.

A decade ago, Xi Jinping asked if China could master A.I. His push is remaking the economy, challenging the United States and keeping society under control. @vwang3 https://t.co/1NxAUK6oSR via @NYTimes

— Ashis Basu 🇨🇦 ashis.bluesky.social (@BasuAshis) September 23, 2026

Financing the AI buildout projects that AI investment in data center buildings, power systems, networking infrastructure, and specialized chips and other equipment will total an enormous $10.3 trillion from 2025 to 2032, or an average of 3.63% of U.S. gross domestic product per year.

“The projected buildout would be larger relative to the economy than the major U.S. canal, railroad, electrification, highway, and telecommunications investment booms,” writes the author, Stijn Van Nieuwerburgh of Columbia University.

The paper warns that the risks embodied in the AI investment race are migrating from transparent on-balance sheet financing by major corporations to opaque off-balance sheet financing through joint ventures, private credit, securitization, special-purpose vehicles, lease commitments, loan guarantees, and other structures.

These off-balance sheet arrangements then depend on AI companies’ cash flows and collateral values, which are subject to “uncertain AI demand, rapid technological change, timely access to power and hardware, and the continued credit quality of a small number of [data center] tenants,” Nieuwerburgh writes.

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Financing the AI buildout will total $10.3 trillion from 2025-2032, or an average of 3.63% of US GDP each year: study. That "would be larger relative to the economy than the major US canal, railroad, electrification, highway, & telecom investment booms" https://t.co/RCT3oaG4VS

— Lisa Abramowicz (@lisaabramowicz1) September 24, 2026

A little over a year ago, Joseph Coates was told there was only one thing left to decide. Did he want to die at home, or in the hospital?

Coates, then 37 and living in Renton, Wash., was barely conscious. For months, he had been battling a rare blood disorder called POEMS syndrome, which had left him with numb hands and feet, an enlarged heart and failing kidneys. Every few days, doctors needed to drain liters of fluid from his abdomen. He became too sick to receive a stem cell transplant — one of the only treatments that could have put him into remission.

“I gave up,” he said. “I just thought the end was inevitable.”

But Coates’s girlfriend, Tara Theobald, wasn’t ready to quit. So she sent an email begging for help to a doctor in Philadelphia named David Fajgenbaum, whom the couple met a year earlier at a rare disease summit.

By the next morning, Dr. Fajgenbaum had replied, suggesting an unconventional combination of chemotherapy, immunotherapy and steroids previously untested as a treatment for Coates’s disorder.

Within a week, Coates was responding to treatment. In four months, he was healthy enough for a stem cell transplant. Today, he’s in remission.

The lifesaving drug regimen wasn’t thought up by the doctor, or any person. It had been spit out by an artificial intelligence model.

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A 37-year-old man with a rare blood disease was being sent to hospice.

An AI model searched thousands of existing drugs and ranked a combination no one had tried for his condition.

He responded within a week. He is in remission.

The drugs were already on the shelf. The AI… pic.twitter.com/sFKRgqtz2g

— Cicero Institute (@InstituteCicero) September 23, 2026

As many atheist philosophers (such as the eminent John Gray) have noted, the New Atheists’ philosophical arguments were never very good. Moreover, their arguments seemed strangely anachronistic following many of the great scientific discoveries of the 20th century.

Consider first modern cosmology. Cosmologists have discovered that the universe, contrary to the expectations of those who long portrayed it as eternal, probably had a beginning. Multiple lines of evidence from observational astronomy support this conclusion. Developments in theoretical physics (such as the Borde-Guth-Vilenkin theorem, which states that any universe that is expanding – as ours is – cannot be infinite in the past), also back it up.

Nobel laureate Arno Penzias, who helped make a key discovery supporting the Big Bang theory, noted the obvious connection between its affirmation of a cosmic beginning and the concept of divine creation. “The best data we have are exactly what I would have predicted, had I nothing to go on but the five books of Moses…[and] the Bible as a whole,” he wrote in 1978.

Atheist physicists Lawrence Krauss and Stephen Hawking claimed to explain the beginning of the universe from “nothing”, but their “nothing” turned out to be a set of mathematical laws that allegedly pre-existed (or existed independently of) the material universe. But maths has no causal power. Mathematical equations are inherently conceptual. Thus, the attempt to circumvent the problem of the beginning with what was called “quantum cosmology” led inexorably back to the need for a pre-existing mind.

Second, physicists have discovered that we live in a kind of “Goldilocks universe”. In other words, the fundamental laws and parameters of physics are finely tuned against all odds to make a life-friendly universe.

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Who wrote the digital code?

"Discoveries in molecular biology have revealed digital code in even the simplest living cells. Francis Crick and James Watson elucidated the structure of the DNA molecule in 1953. Crick then developed his famed “sequence hypothesis”. He proposed that… pic.twitter.com/itAlWDyGN2

— Nancy Pearcey (@NancyRPearcey) September 23, 2026

Finally, we will ask what went wrong.

The postmortem will be this. Many people panicked about the possibility of strong AI models killing us all. That fear was not based on peer-reviewed scientific research showing a high chance of doom, nor was doom indicated in any market prices of the time, including measures of risk. It was a story, just like this is a story, and it was spread on social media. The key point of the doom story was that, if America keeps the No. 1 spot in AI models, the models will be so strong they will do us all in, or lead to unimaginable catastrophes. We were too afraid to have America keep the lead, forgetting that if truly destructive AI is our fate, the doomer scenario can come from Chinese AI as well.

Today, we cannot say for sure that the AI doom scenario is false. But is it a story we wish to live by? Is belief in it a good way to protect and extend life, liberty, and the pursuit of happiness? Will it help us much, or for long, if it is Chinese AI that turns on us and does us in?

In my view, successful societies accept challenges and meet them. Solving problems, bit by bit, is the best way to ensure that we have the capabilities to meet big and truly existential risks, should those risks come along. Debating the chances of our doom, ex ante, on a highly speculative basis, is unlikely to provide the same kind of expertise and talent cultivation. It is instead more likely to demoralize and immobilize us.

So which America are we going to choose?

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Tyler Cowen: A Doomsday Scenario for American AI https://t.co/3qm0eVwQ3I

— Mark Semonian (@msemonian) September 21, 2026