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Trump blew billions on Iran instead of keeping you insured
President Donald Trump blew more money in five months of war with Iran than it would have cost us to keep millions of Americans insured for the year.
Movies that made $2 billion at the box office
James Cameron and the Marvel Cinematic Universe are the two consistent factors when it comes to earning billions at the box office.
The Science Behind the AI Panic Is Shakier Than You Think
A column by Sascha Lobo Is AI making us dumb? So asked DER SPIEGEL on its cover a while ago. After a few weeks of recovery and a therapeutic intervention with the help of my AI, I feel able to respond. That’s a bit unfair, of course; the article itself is more nuanced than the loud cover, the image of a schoolkid with dull prompt questions, or the subtitle: “AI is conquering the schools, and educators fear a disaster.” The short answer to “Is AI making us dumb?” is: no. The long answer is more interesting, and even carries a preliminary glimmer of the spectacular. Unfortunately, it requires a detour into the sphere of artificial intelligence, into the mogul-field terrain of technology assessment, the attention economy, and the destructive virus of cultural pessimism. Along with narrowing the scope to AI’s effects on education and work rather than on intelligence. Because the honest version of the question would be: Does AI help us learn and work, or not? Generative AI, which set off the still-ongoing hype with ChatGPT, has only existed in relevant distribution since late 2022, early 2023. For a technology-driven transformation of people and society, that is extremely short. For that reason alone, research is still in its infancy. And technology assessment is not a fast discipline anyway. Prominent voices from Elizabeth Eisenstein to RAND to Tom Wheeler say we still cannot conclusively judge the consequences of the printing press. Its invention is a mere 580 years back, and some scholars would rather not circulate assessments that might have to be retracted in two or three hundred years. We’re Going Through Growing Pains A phenomenon that already caused upheaval in social media research makes serious assessment of AI’s consequences even harder: the “moving target” problem of LLM-ology, as the linguist Sean Trott called it in 2025. AI develops so quickly and so unpredictably that researchers often end up studying snapshots of the past. There are concepts, from morphological analysis to anticipatory governance, for keeping research, planning, and regulation halfway meaningful anyway. But even with those, universally valid statements are rare. DER SPIEGEL - The German View is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. Subscribe We should therefore treat findings about the interplay between humans and AI as far more procedural and situational. Unfortunately, this challenge comes at the worst possible time. We are going through growing pains: AI’s everyday impact has grown very large very fast, and with it the longing for guidance. Annoyingly, the body of solid knowledge has not exploded along with it. Experts cannot be moved to broad consensus on even banal statements about AI. Sascha Lobo, born in 1975, is an author and strategy consultant focusing on the internet and digital technologies. Together with Jule Lobo, he explores the debates of the day in the podcast “Feel the News – Was Deutschland bewegt” (”What Moves Germany”). Nvidia CEO Jensen Huang says software developers are dying out. Bill Gates considers coders one of only three professions that will survive the AI tsunami. Top tech economists find virtually irrefutable arguments both for and against an AI bubble. The same naturally applies to the structurally youth-hostile debate over whether AI is good or bad for young people. The gap between the demand for insight and the supply of solid knowledge creates an orientation vacuum. This vacuum of AI cluelessness is filled, as the attention economy described by Georg Franck in 1998 would have it, with half-knowledge (funnily enough, often AI-generated), marketing, and self-marketing. After all, infinite money is at stake, along with academia’s best current shot at global fame. But this iridescent froth of interpretation operates more by the algorithmic principles of the digital public sphere than by seriously earned insight. That is why dramatized, fear-feeding claims about AI are so promising. It tempts parts of academia into distorted drivel, and parts of the media then sensationalize the published drivel once more. Was the Research Aimed at a Desired Result? How badly this can influence academia and public perception is demonstrated by one of the most-discussed studies on AI’s effects: “Your Brain on ChatGPT.” The MIT study by Nataliya Kosmyna also gets plenty of space in the SPIEGEL cover story. What was measured and interpreted: lower brain activity in people who write with AI assistance, compared to people who only google or write without any tools. As is common with preprints, the study has not yet been peer-reviewed, and it contains substantial weaknesses that experts have sharply criticized. The first round had 54 participants in three groups, the second only 18, who reportedly also came from MIT’s own orbit. There was no preregistration (committing in advance to what you want to find out with which data). In their analysis, Stanković et al. even discovered an opposite effect that the study does not further explain. Some measurement data has not (yet) been published. And the EEG analysis method used is considered too imprecise to support such far-reaching conclusions. The biggest criticism, though, is the suspicion of an activism-driven study. In an interview with Time, lead author Kosmyna said she published the study immediately, rather than after full peer review, because she feared politicians might otherwise decide to put ChatGPT in kindergartens. She considers that absolutely harmful. It is legitimate to hold such a view. It just seems unscientific to approach a study with it, and then to design the setup so that the chance of a fitting desired result remains as high as possible. Ideologies Collide It is not easy to separate genuine AI insights from studies that trivialize and weaken well-founded AI criticism. The same goes for the opposing, AI-enthusiastic narratives, because the pro-AI side works against it with billions in resources. Ideologies collide, fed by egos, PR strategies, moral posturing, and once-in-a-lifetime opportunities. Doomsday marketing makes the search even harder: AI companies can profit from warnings about the dangers of AI, whether through the notoriety of apocalypse narratives or because, in some target groups, danger translates into power. Some seemingly negative findings are therefore quite welcome in the AI industry. If you try to get at the findings presumably less influenced by interest groups, the picture in education seems relatively clear: AI can improve educational outcomes when the right AI is used the right way, namely pedagogically. Simply dumping an AI chatbot into a classroom, by contrast, accomplishes little. Huge surprise. But something else is also obvious: whether they are allowed to or not, kids use AI for school, which is why the controlled integration of AI tools into education is, in the medium term, entirely without alternative. In the world of work, the landscape of findings is more complex and requires more differentiation. A series of serious studies points to an AI effect that suits neither the alarmists, regulation fetishists, and AI opponents, nor the trillion-dollar corporations with their armada of paid scientists, PR professionals, and ecosystems: working with AI helps the inexperienced (at least for now) considerably more than it helps the pros, in certain fields of work, and provided they know how to use it correctly. Missing Domain Knowledge Among the experienced, the professionals, and the high flyers, by contrast, despite frequent time savings, partially negative effects and new problems are emerging. Take the jagged frontier problem: AI solves task A brilliantly and fails completely at task B, even though both look similar even to professionals. Or the verification-cost problem, in which AI’s greater productivity gets eaten up by the enormous effort of checking its output. Or the illusion of competence, because AI makes new domains seem easily penetrable, until you painfully discover that deep domain knowledge is missing. Taken as a whole, the effects of working with AI do lean positive. But the promise that AI works as a turbocharger for everyone and boosts practically everything simply refuses to materialize. The AI magic the world has been feeling since ChatGPT arrived in late 2022 has so far barely shown up in most companies’ numbers. The consulting firm McKinsey has coined a term for this, the “gen AI paradox,” and believes that work processes and corporate structures would have to be rebuilt quite fundamentally to realize AI’s benefits at scale. Reuters just reported that only 3.3 percent of Microsoft’s customers have subscribed to the AI package Copilot. That may be down to the product; in other areas we continue to see soaring successes and new AI triumphs. But after the first quarter of 2026, disillusionment is the word for all too many AI projects at traditional companies: because the promised revolution of AI agents has so far failed to arrive or been postponed, and because of the leveling effect that many of the studies cited here suggest. Against Inequality The societal effects, on the other hand, appear rather encouraging. Many previous technologies operated on the Matthew principle, named for the Gospel verse about giving to those who already have: they tended to reward the more competent and more privileged. AI, however, seems more often to have an equalizing effect once a threshold of access and education is crossed. Some anecdotal insights point in this direction, for example, how an unemployed man in Leipzig successfully defended himself in court in 2025 against fraud accusations from Germany’s federal employment agency — without a lawyer, armed only with ChatGPT. The AI made mistakes and cited invented court rulings, but in the end the man walked away unpunished. And a key capability of artificial intelligence is its capacity to learn: set up correctly and fed with data, it can keep getting better. It is a question of time, or more precisely of AI innovations and training data, until even free AI chatbots write better legal briefs than law graduates with perfect exam scores. Whether that will make anyone dumb is something the world’s press will surely inform us of in due time. Subscribe Leave a comment
Hiltzik: Trump replaces science with stupidity
Partisan political filters and the search for "DEI" have resulted in billions of dollars in canceled scientific research grants
Heat stress is rising globally, raising health concerns for billions: Study
Climate change is causing frequent, well-studied, extreme heat events. Less well understood is the additional heat stress experienced by billions of people as a result of those extreme heat events. However, a new study published in Nature Climate Change aims to change that. The study analyzed more than 70 years of climate data stored in […]
Inside the federal keyword lists that canceled billions in research funding
In court documents, the National Institutes of Health, the National Science Foundation and others shared which words they used to target grants.
‘Going it alone does not work’: America’s first one-party war
As President Donald Trump pleads for tens of billions of dollars to pay for the nation’s war with Iran, Democrats in Congress have offered an unequivocal — and historically unusual — message.
Week in Politics: Iran War; Trump attends solemn ritual; nuclear deal with Saudi Arabia
The Trump administration is seeking tens of billions of dollars in supplemental appropriations for the Iran War, a war which the president and allies have repeatedly claimed is already won.
Matt Mindrum: Don’t put a moratorium on Indianapolis’ growth
Marion County's data center moratorium sends a message that Indianapolis is becoming less open to business. It risks turning away billions in investment from some of the world’s fastest-growing industries.
The tech-broification of American science has officially begun
Trump’s ‘Golden Age’ of American science starts with dismantling it, while funneling billions into AI.
White House offers its science blueprint: More AI, less life sciences
The Trump administration released its blueprint for U.S. science, calling for shifting hundreds of billions of research dollars from universities to industry.
Wilmington announces business and economic development chief
The city of Wilmington announced on Thursday the hiring of Louis Starks as its new business and economic development manager. According to a news release, the role focuses on strengthening Wilmington's business ecosystem, supporting entrepreneurship and advancing strategic economic growth. "In this role, Starks will collaborate with residents, local businesses, community groups, educational institutions and regional partners to promote investment, workforce development, and innovation for businesses of all sizes," the release stated. "He will also help connect small businesses with City procurement opportunities, cultivate public-private partnerships, and lead initiatives that promote long-term economic vitality." Starks has more than 20 years of experience in economic development, urban planning, housing finance, workforce development and public policy, according to the release. Most recently, he served as manager of business development for Oakland County, Michigan, "where he led teams focused on business retention and expansion and financial services for one of the nation's most economically diverse regions. During his tenure, his teams supported billions of dollars in business investment initiatives while helping create thousands of jobs," the release stated. He holds a law degree and master's degree in urban and regional planning from the University of Iowa, as well as a bachelor's degree from Duke University. He is also a Certified Economic Development Professional. Starks is expected to begin his Wilmington position on July 27. “Louis has built his career around helping individuals, organizations and communities reach their full potential,” stated city manager Becky Hawke in the release. “Whether supporting entrepreneurs, managing complex redevelopment projects, or bringing together public and private partners, he has consistently focused on creating opportunity and delivering results. He understands that a strong economy creates opportunities for everyone. By supporting local businesses and fostering innovation, his work will help ensure the benefits of Wilmington’s growth are felt throughout the community, creating jobs, strengthening neighborhoods, and improving quality of life for residents.”
Trump to steer billions from universities to AI and individual scientists
White House says overhaul will back AI and researchers to restore the US scientific edge as Beijing closes the innovation gap.
House takes first step to unlock Iran war funding — but fate in Senate uncertain, with measure tied to ‘SAVE America Act’
The House of Representatives on Wednesday took the first step toward funding President Donald Trump’s war with Iran, as well as approving tens of billions in additional Pentagon money and aid for US farmers.
White House wants to shift billions of dollars of research funding away from ‘slow consensus peer review’ and into individual scientists and AI
Moving funding to individual scientists and AI could undermine US scientific credibility at home and abroad.
Exclusive | White House to Redirect Billions in Research Funds Toward AI, Away From Colleges
The overhaul will reshape $200 billion in spending a year and favors individual scientists to outpace China.
Michigan extends key tax breaks for billions of dollars of real estate development in Detroit
Real estate developers are breathing a sigh of relief now that state lawmakers have agreed to an extension of two key property tax abatements used for projects around Michigan.
Most Americans support conservation – here’s how the Great Lakes Restoration Initiative got politicians from both parties on board too
An analysis of one major effort shows how to get Democrats and Republicans to agree to spend billions of dollars on a decades-long environmental restoration project.
Boeing on track for 2028 Air Force One delivery, costs rise
Boeing said on Sunday it remains on track to deliver two new Air Force One jets in 2028, but meeting that target will require additional spending on a program already years behind schedule and billions of dollars over budget.
'It's absolutely exciting!': Astronomers discover an atmosphere around an Earth-like planet in the habitable zone for first time ever
Astronomers have detected helium escaping from the super-Earth LHS 1140 b, providing the strongest evidence yet that a rocky planet in another star's habitable zone has retained an atmosphere for billions of years.
Google and Apple are clashing with the EU over the future of AI assistants
Google and Apple have a big leg up in the AI race: their control of billions of smartphones around the world.
Science by merit, not political favor
The right to be judged by a jury of your peers is a bedrock of American democracy. This principle applies not only to the judicial system but also to how the federal government evaluates and awards billions of dollars in grants to natural…
Kalshi says it's not a sportsbook even as World Cup bets surge
The betting site Kalshi emerged as a dominant sports betting platform during the World Cup. But the company avoids billions of dollars in taxes by insisting it is not a sports gambling operator.
Trump earned billions last year. Some Pennsylvania swing voters say they don't care
Key voters in Pennsylvania are split on whether President Trump earning a big windfall last year is a big deal or not. Their reaction reveals a level of cynicism about many in the political class.
Over 100 Democrats vote to block billions of dollars in military aid to Israel, reflecting growing schism in party
More than 100 Democrats voted to block billions of dollars in military aid to Israel — an ultimately unsuccessful effort that highlighted the growing division in their party on the issue.
Greenland institute halts new collaborations with the US
The Trump administration has cut billions of dollars in public research funding and fired government scientists.
China’s Chip Champion to Raise Billions in Race for A.I. Control
CXMT, a linchpin in China’s drive to develop homegrown artificial intelligence technology, is aiming to raise nearly $10 billion in a blockbuster public offering in Shanghai.
Tech Investors and Longevity Influencers Back Neko Health’s Mega Round
The health tech start-up co-founded by Spotify’s Daniel Ek is worth billions more after a new $700 million funding round.
Big Banks Smash Earnings Records, but ‘Tectonic’ Risks Loom
The largest banks in the United States collectively raked in tens of billions of profits in the second quarter, despite the war in Iran and persistent inflation.
The Quintessential Trump-era Politician
In 2020, I wrote an article about collaboration and collaborators. The title was History Will Judge the Complicit, and it started with the story of two famous East Germans, Markus Wolf and Wolfgang Leonhard, who both landed in East Berlin just after the end of the war. Although they came from very similar backgrounds, the former stuck with the regime, eventually becoming its spy boss; the latter, horrified by the brutal reality of Soviet-style communism, escaped. By way of juxtaposition, I also wrote about Lyndsey Graham and Mitt Romney. These two men also made very different decisions when confronted by Donald Trump’s assault on the ideals that they had both grown up believing: A glance at their biographies would not have led many to predict what happened next. On paper, Graham would have seemed, in 2016, like the man with deeper ties to the military, to the rule of law, and to an old-fashioned idea of American patriotism and American responsibility in the world. Romney, by contrast, with his shifts between the center and the right, with his multiple careers in business and politics, would have seemed less deeply attached to those same old-fashioned patriotic ideals. Most of us register soldiers as loyal patriots, and management consultants as self-interested. We assume people from small towns in South Carolina are more likely to resist political pressure than people who have lived in many places. Intuitively, we think that loyalty to a particular place implies loyalty to a set of values. But in this case the clichés were wrong. It was Graham who made excuses for Trump’s abuse of power. It was Graham—a JAG Corps lawyer—who downplayed the evidence that the president had attempted to manipulate foreign courts and blackmail a foreign leader into launching a phony investigation into a political rival. It was Graham who abandoned his own stated support for bipartisanship and instead pushed for a hyperpartisan Senate Judiciary Committee investigation into former Vice President Joe Biden’s son. It was Graham who played golf with Trump, who made excuses for him on television, who supported the president even as he slowly destroyed the American alliances—with Europeans, with the Kurds—that Graham had defended all his life. By contrast, it was Romney who, in February, became the only Republican senator to break ranks with his colleagues, voting to impeach the president. “Corrupting an election to keep oneself in office,” he said, is “perhaps the most abusive and destructive violation of one’s oath of office that I can imagine.” In the wake of Graham’s unexpected death on Saturday, I wrote about him again. He was, in many ways, the quintessential politician of Trump’s Washington, a man who shifted 180 degrees. Graham had been a fervent American patriot, proud reserve officer and military lawyer; he became one of the most important defenders of a president who believes soldiers are “suckers and losers” and shows no respect for law of any kind. As his politics changed, his language grew coarser and his behavior grew worse: He urged Israel to “level the place” in Gaza, and insulted the Danish prime minister in Munich, prompting a colleague, Senator Elissa Slotkin, to issue an apology. Here’s an excerpt from the article, which you can read in The Atlantic (gift link here) Like his close friend John McCain, Graham believed that America should stand at the center of a broad democratic alliance. The few times I met him were in that context, at the Munich Security Conference or at other European-American gatherings, which he once attended with great regularity. He also took seriously the practice of American democracy at home. In a 2014 conversation with The Atlantic, he described himself as a pragmatic politician who eschewed populist slogans. “I know Washington is broken, but what’s broken about it is everybody yelling and nobody trying to fix it,” he said. “I’m trying.” When Donald Trump first appeared in U.S. politics, Graham recognized him immediately for what he was: the spokesman for an alien ideology, one radically different from the idealistic patriotism that Graham had practiced and preached since childhood. Trump privately mocked the military that Graham loved as nothing but “suckers and losers.” He put falsehoods, cynicism, and personal greed at the center of his politics, while expressing disdain for transparency, accountability, and democracy itself. In 2015, Graham described Trump as a “race-baiting, xenophobic, religious bigot” who should “go to hell.” Also as a “nutjob.” When Trump won, Graham understood, as did so many others, that he would have to make some important choices. For a while, he went silent. In the spring of 2016, I saw him at one of those conferences in Europe. He seemed too depressed to speak. But then, like many other Republicans—and, more important, like many other people who have lived under political occupation or experienced radical regime change—he made the decision to abandon his previous ideals, to bury the patriotism that was once so important to him, and to become, instead, a loud, opportunistic collaborator. As I wrote in 2020, it’s very hard to look in to anyone’s heart and to understand their motivations from the outside. But it does seem that Graham had a deep need to be relevant, to be in the game, to be a player, at any cost. And that, rather than any particular achievement, is what he will be remembered for. Continuing to monitor conflicts of interest, ostentatious emoluments, outright corruption and policy changes that will facilitate outright corruption. (Read my original article, Kleptocracy Inc and check out the SNF Agora Institute chart) June 27 Trump diverted funds from more than 900 projects nationwide—including safety upgrades at national parks—to finance beautification projects around Washington, including $700,000 used to fix a White House walkway. June 28 After a years-long Department of Justice investigation into Abbott Laboratories over its management of a baby formula facility where potentially deadly bacteria turned up enough evidence to criminally charge the firm, top department officials instead opted for a financial penalty—illustrating the department’s move away from strict corporate enforcement under the Trump administration. June 29 Defense Secretary Pete Hegseth stacked the Defense Policy Board—which is charged with providing independent national security recommendations to the Office of the Secretary of Defense—with Trump allies, including tech billionaire Marc Andreessen, who has invested in defense contractors like OpenAI and SpaceX, after purging the panel last year. Trump purchased between $1 million and $5 million worth of stock in Axon—which makes about 90% of US tasers—two weeks before ICE solicited bids for a $220 million taser contract. The White House unveiled limited-edition US passports for America’s 250th birthday, featuring a portrait of Trump overlaid on the Declaration of Independence. June 30 Trump made around $1.2 billion from his various crypto companies last year, including more than $500 million from World Liberty Financial and $600 million from sales of his meme coin. Trump is considering issuing 250 pardons to commemorate America’s 250th birthday. These are expected to be largely doled out through the Office of the Pardon Attorney’s informal network of intermediaries. White-collar defense attorneys say they can typically win pardons for clients for $2 million. Last year, Trump administration officials awarded a no-bid contract worth up to $500 million to Clark Construction for the White House ballroom—negotiations in which the president was directly involved. July 1 The Amazon MGM Studios documentary about Melania Trump earned the First Lady more than $10 million. Trump made hundreds of individual stock purchases worth as much as $12.8 million the day before his announcement pausing “Liberation Day” tariffs for 90 days sent the S&P 500 soaring nearly 10%—one of the largest single-day gains ever. Mar-a-Lago and Trump National Doral saw record surges in revenue during Trump’s first year in office, earning $77.5 million and $121.9 million respectively, compared to average annual revenues of $25 million and $75 million during Trump’s first term. Entities across the Persian Gulf paid more than $300 million to Trump’s businesses last year, including $263 million from the sale of half his stake in World Liberty Financial to a firm backed by Sheikh Tahnoon bin Zayed Al Nahyan, a top UAE royal and brother of the country’s president. Kash Patel failed to properly disclose his stock purchase of a Department of Justice contractor, MicroStrategy, worth up to $250,000 last year, despite laws requiring disclosure within 45 days of the trade. July 2 Trump has been directing administration officials to steer more government contracts—so far worth more than $2.4 billion—to Jeff Bezos’s Blue Origin aerospace firm, after Amazon gave $1 million to Trump’s inaugural fund, donated to the White House ballroom project, and reached a $40 million deal to license a Melania Trump documentary. Alongside the billions he made from cryptocurrency last year, Trump earned millions of dollars from real estate licensing fees, including $21 million from organizations in the UAE and $9.2 million in Saudi Arabia, along with smaller sums from merchandise sales, including $4.7 million from Trump Watches and $35,920 from 45 Guitar, a guitar brand endorsed by the president. House Democrats accused consultants tied to the Trump administration of financial fraud, alleging they gave prospective donors to America250—the bipartisan committee created by Congress to celebrate the nation’s semiquincentennial—the banking and routing numbers for Freedom 250, the White House’s fund for events like the UFC cage fight. Democrats also allege that Freedom 250’s CEO traveled to the World Economic Forum in Davos to solicit donations from foreign government officials and business leaders. The Trump administration’s proposed rollback of gun regulations would lift the prohibition on mailing handguns to individuals, a significant win for GrabAGun—the direct-to-consumer firearm retailer on whose board Donald Trump Jr. sits and in which he holds a 1.1% ownership stake. GrabAGun currently must rely on a middleman to transfer firearms to customers. Trump’s financial disclosure revealed that he made more than 21,000 securities trades during his first year back in office, growing his investment account to at least $858 million across stakes in around 1,600 companies, compared to the 13 total trades Joe Biden made during his entire presidency. July 4 Nearly 1 million people who bought the president’s meme coin—Trump Coin—collectively lost $3.8 billion on the token, while he walked away with $636 million. July 6 Shares of Dell closed up 4.4% after Trump recommended people buy the firm’s computers during a speech announcing the launch of Trump investment accounts for children, boosting the more than $1 million worth of shares the president owns in the company. July 9 Federal Reserve Chair Kevin Warsh named crypto investor and Trump ally Marc Andreessen to a task force aimed at modernizing the Federal Reserve, including rethinking its approach to inflation—a key factor keeping interest rates elevated. Palm Beach International Airport has officially changed its name to Trump International Airport—a move that will require Florida to pay royalties to the president’s family for licensing his name. I was there a few months ago, during a trip to Barcelona. The sculptures were a revelation, I’d never seen so many together before. Each one has its own personality. Enjoy the good weather, if you are lucky enough to have it. History Will Judge the Complicit The Quintessential Politician Autocracy Inc Open Letters, from Anne Applebaum is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
‘Outrage’: Community and research allies blast Trump plan to politicize U.S. grants
The Office of Management and Budget has proposed a sprawling overhaul of a rule establishing the framework for federal financial assistance that would set up Trump and future presidents to politicize federal grantmaking, shifting grantmaking power to administration appointees and seizing broad latitude for the executive branch in the financial aid process. Wide-ranging opponents of the Trump administration proposal say it would tee up federal agencies to dismiss community needs and congressional intent on a partisan basis as they decide discretionary federal awards – with billions of dollars at stake.
‘Marie Antoinette would feel very comfortable’: How U.S. airlines built their business around big spenders
Delta, United and American are pouring billions into first-class lounges, caviar service and lie-flat seats as premium cabins become their most profitable real estate—while economy travelers face rising fares and add-on fees.
Thousands of acres, billions in investment: What's next for RiverPlex MegaPark?
The RiverPlex MegaPark is still years away from reaching its full potential, but the foundation is being laid for what could become one of the Gulf Coast’s largest industrial hubs, according to Ascension Economic Development Corporation President and CEO Kate MacArthur. With roughly $10 billion in announced investment already committed and thousands of acres still […]
Nintendo President Promises To Tackle Pokémon Card Scalpers After Billions Printed Fail To Satisfy Market
During a meeting with shareholders, Shuntaro Furukawa said that the intense world of Pokémon Card flipping is on their radar and mentions requiring government ID isn't off the table
Mark Zuckerberg takes business calls on a jet ski wearing his $800 Meta glasses—and insists ‘the other person could not tell’
Zuckerberg is convinced smart glasses will replace the smartphone—and he's spending billions to prove it, even as Reality Labs posts a $19.2 billion loss.
MAGA Base Stays Quiet After Trump Reports Billions in Personal Gains
A new mandatory disclosure revealed that the president has earned $2.2 billion during the first year back in the White House.
Trump administration’s $46 billion 'smart wall' races ahead
The wall is under heavy scrutiny for the billions of dollars being dedicated to it when border crossings are at their lowest in decades.
Trump administration’s $46 billion 'smart wall' races ahead
The wall is under heavy scrutiny for the billions of dollars being dedicated to it when border crossings are at their lowest in decades.
Philippines' 80-year bet on America
Eight decades after the US recognized Philippine independence, Manila remains closely tied to Washington through treaties, military cooperation and billions in trade. DW went to Manila and Washington to ask what this partnership delivers — and who pays the price.
Big Tech is spending billions to not employ people
Amazon disclosed $2.7 billion in estimated severance costs in its latest annual report, while Intel and Oracle also reported spending $1.8 billion.
Trump made hundreds of millions from cryptocurrency ventures in first year back in office
President Donald Trump collected billions of dollars through an array of cryptocurrency holdings, royalty payments and property investments last year, according to his latest annual financial disclosure released on Tuesday.
Iowa small businesses encouraged to compete for federal defense contracts
Iowa small business owners are being encouraged to compete for billions of dollars in government contracts as the federal government looks to expand its defense industrial base.
Iowa small businesses encouraged to compete for federal defense contracts
Iowa small business owners are being encouraged to compete for billions of dollars in government contracts as the federal government looks to expand its defense industrial base.
Small Businesses Could Lose Access To Billions In Contracts As New HubZONE Deadline Kicks In
Certain areas across the U.S. that were previously designated as HUBzones will see that status expire on July 1.
Scam Victims Report Billions Lost and Harm to Mental Health
Scam victims in the U.S. lost an estimated $68 billion in 2025, suffering widespread financial and emotional harm.
Germany news: Heat soars as political reforms split opinion
As Europe's heatwave rages, Germany continues to swelter with new records expected Saturday. Elsewhere, politicians bicker over reforms and industry blames train operator DB for billions in losses. DW has the latest.
Mark Cuban urged AI firms to spend billions on cities hit by job losses
He said this is the "cost of doing business" for the companies that are losing a PR battle with the masses.
Making Our Own Luck
We are cross-posting a piece that former NIH official Kris Willis wrote for Macroscience. Kris is now the President and Founder of the Woodley Park Institute, for which I’m a board member. Picking winners or hedging bets? Federal science agencies have long wrestled with the question of how to ensure their billions of dollars of grants and contracts result in maximum benefits for Americans. On the surface, it might seem that a goal-oriented, interventionist style of management would be the best policy: prioritize our most pressing problems and distribute funding accordingly.This top-down strategy creates a unique hazard, though: bad choices can send resources in the wrong direction, resulting in slow progress that impedes the delivery of tangible benefits to citizens. Moreover, if decision makers pursue an applied advance when the underlying scientific principles remain poorly understood, they risk costly failures and a loss of support for the research enterprise at large. Examples include Nixon’s 1971 War on Cancer, undertaken on the premise that a cure could be achieved in less than a decade, the drive to build an operational commercial fusion plant by the mid-1990s, and the National Plan to Address Alzheimer’s Disease, which failed to produce the effective treatments and prevention strategies promised by 2025. The contrasting laissez-faire approach is to hedge your bets. If the path to an advance is impossible to predict, then the wisest choice might be to distribute funding to as widely as possible. The main risk of this strategy is that spreading funding thinly may limit the resources available to the most promising research, resulting in the same negative outcomes as the interventionist approach: limited support for the most promising topics, slow progress, and delayed returns. In reality, at science agencies like the National Science Foundation and National Institutes of Health, program managers navigate between these two extremes, setting some funds aside to target high-priority areas and using the rest to cover the widest possible range of meritorious proposals. This middle path seems like the most rational way to proceed, but it still requires making choices. How much should be set aside for high priority topics? What should those topics be? How should we define merit? Expert opinion can provide a helpful guide, but leading experts can have remarkably different opinions about what matters and what should be prioritized. Moreover, experts and administrators alike can be risk averse, giving an edge to high-profile, well-established concepts. What’s really needed is a data-driven framework to help guide decision-making, one that doesn’t simply repackage prestige or incumbency. Recognizing breakthroughs years in advance Many breakthroughs fail to attract funding or recognition at the earliest stages of development. Katalin Karikó, for example, spent years struggling to win grants for work on mRNA that would eventually win her and Drew Weissman a Nobel Prize. Similar stories can be told about Jim Allison’s groundbreaking studies leading to the development of cancer immunotherapy, Stan Pruisner’s demonstration that prions can self-replicate without DNA, or Robin Warren and Barry Marshall’s proof that Helicobacter pylori, not stress, causes ulcers. Yet at some point, the scientific community recognizes and responds to transformative breakthroughs like these. How does that change happen? And what if science funders could identify the areas that are on the cusp of a breakthrough? Those questions led my collaborators and me to study how scientists responded to past breakthroughs. Based on patterns in that data, we developed a means of predicting future breakthroughs, using biomedicine as a proof of concept. It’s worth taking a moment to describe how our approach works. Briefly, our prediction process begins by grouping the 18 million or so peer-reviewed papers in PubMed, the authoritative database of biomedical research, into roughly 50,000 unique topics. A small subset of these topics are so widely acclaimed as breakthroughs that they have been recognized with a major prize like a Nobel or a Lasker Award. We theorized that studying the development of these outliers over time, especially before they gained acclaim, was the key to identifying future instances of them. After defining topics, we chose 21 representative breakthroughs and asked what they looked like before they won prestigious prizes. To answer that question, we re-ran our topic-mapping algorithm repeatedly, winding back the clock one year each time, stringing together the years to follow the progress of each field as it grew and advanced. We found that in each case, the years leading up to a discovery followed a pattern: a burst of papers on a new, rapidly evolving topic, many of which quickly became influential. These characteristics—the percent of papers that are new, the percentage of papers that are brought in from other topics, and the influence of each individual paper—can all be measured separately for any given topic. Together, they act as a predictive signal that is detectable an average of five years before a transformative discovery is made, and up to thirty years before the discovery receives a major prize. Scanning the current research landscape for topics that display this signal allows us to predict what work will likely produce a future breakthrough. Each year we analyzed includes four or five signals, a number that appears to have remained constant across a twenty year time frame. In their classic work on the sociology of science, Bruno Latour and Steve Woolgar established that the desire to participate in a major discovery is an important motivator for scientists as they consider whether they should take up (or abandon) a research problem. Although further work is needed, the simplest explanation for our results is that this behavior is widespread enough to detect at scale. A foundational advance, or something like it, draws the attention of scientists and causes them to change the direction of their research. They vote with their feet, staking their own reputation and careers by publishing on and citing the new idea. That upswell of interest is the foundation of our breakthrough signal. What kind of research does our model identify as a breakthrough? After building a model based on the patterns in our 21 preselected breakthroughs, we tested it by identifying all early signals of discovery from 1994 through 1997. Of the 18 signals we found in that time period, 17 can be traced forward in time to a breakthrough. Examples include super-resolution fluorescence microscopy (see the image above), the directed evolution of proteins and enzymes (Chemistry Nobel, 2018), and sequencing the human genome (National Medal of Science, 2008). The discovery of the role of leptin signaling in obesity is a particularly interesting case study. Around 1950, scientists noticed the existence of a type of lab mouse that suffered from a unique inherited form of obesity. When given the freedom to choose their own diet, these mice ate more than normal and preferred food that was high in fat. Researchers had few clues as to why the animals overate; early experiments pointed to the existence of a soluble ob factor found circulating in the bloodstream that regulated appetite, but its identity was unknown. In 1994, Jeffrey Friedman and colleagues identified and sequenced the ob gene, noting that the protein it encoded appeared to fit the profile of a circulating factor. A year later, a trio of high-profile publications demonstrated that ob was a hormone that regulated body weight and fat deposition by regulating appetite. One of these was co-authored by Friedman, who christened it leptin from the ancient Greek word for thin. Using our model, the data from 1996 make it clear this advance would become a breakthrough. Scientists had flocked to study the biology of the new hormone, generating the flurry of new papers and citations required to produce a signal. One of these demonstrated that serum leptin concentrations reflected the amount of adipose tissue in the human body, providing clinical validation of the earlier mouse studies. Before the identification of leptin, scientists were unable to point to a specific molecule that controlled appetite and adiposity, so that it was impossible to rule out non-physiological causes of obesity; its characterization fundamentally changed our concept of weight gain. In 2010, Friedman and fellow pioneer Douglas Coleman were awarded a Lasker for the discovery. Our work also identifies breakthroughs in clinical practice and behavioral and social sciences, even though these areas are less likely to draw the attention of major prize committees. One example that falls into this category is the introduction of endovascular aneurysm repair, a minimally invasive surgical procedure for the treatment of abdominal aortic aneurysm, a leading cause of death among Americans over the age of 65. Relative to the previous standard of care, it reduces in-hospital mortality by almost four-fold. In 2017, Timothy Chuter received the American College of Surgeons’ prestigious Jacobsen Innovation award for his multiple refinements to the technique. Another under-recognized breakthrough identified by our model is the development of standardized survey instruments to assess the quality of life for HIV+ patients. The antiretroviral cocktails introduced in the mid-1990s reduced AIDS mortality, but treatment came with serious side effects. The new evaluations showed that patients whose disease progressed had worse physical functioning than Americans with other chronic diseases, while those who were asymptomatic maintained a health-related quality of life on par with the overall US population. This evidence made it possible for patients and activists to argue that even in the absence of a total cure, and in spite of the side effects, alleviation of symptoms was a worthwhile priority for clinicians. My colleagues and I have failed to identify any significant recognition for the physicians and health policy experts who pioneered this advance, although in 2016, researchers called for the World Health Organization to set targets for good health-related quality of life as part of its framework to end the AIDS pandemic. From forecasting to funding How should science funders use our predictions? Any serious discussion of what we should do with this new capability needs to begin with an understanding of its limitations. We can’t (and shouldn’t) invest all of our resources in the small number of topics predicted to produce breakthroughs. Innovative new fields are born from existing ones; they rarely arise de novo. If funders don’t maintain a diverse portfolio, the breakthroughs of tomorrow will have no antecedents. Think of this as eating the seed corn, or killing the goose that lays the golden egg. There are also multiple goals of funding beyond basic scientific discovery, including translating discoveries into clinical practice, developing new technologies, supporting economic development, and training new scientists. The investments needed to accomplish these goals are likely different from those required to support emerging breakthroughs. Finally, we must be aware that we may not capture every instance of a breakthrough. The concept is fuzzy, and not every significant discovery is recognized with a major award. Further, breakthroughs are rare, meaning that our dataset is, by necessity, small. This makes formal estimates of accuracy challenging. Although our overall success rate appears to be high, any one signal may turn out to be a false positive. We found one apparent example: the development of the third generation COX-2 inhibitors, Vioxx and Celebrex, which were much celebrated in the early 2000s as effective but non-addictive pain relievers, meets all the algorithmic criteria of a breakthrough. Five years after it received FDA approval, researchers demonstrated that Vioxx was associated with serious cardiovascular complications, and the manufacturer voluntarily pulled the drug from the market. Celebrex remains available, although like other NSAIDs, it carries an FDA warning for increased cardiovascular risk. Decision makers who were overly focused on the breakthrough potential of this research might have wasted substantial resources nurturing an area that ultimately proved to be a failure—but so would those who relied on expert opinion at the time. That said, the potential benefits of funding the next mRNA vaccine or cancer immunotherapy years earlier than we might have are large. When we can’t assume the outcome of an action, it’s worth conducting an experiment. Can targeted support for areas that are poised to produce a breakthrough increase the return on scientific investment without cannibalizing future advances? With the necessary administrative infrastructure in place, conducting this experiment would be straightforward. First, identify all the breakthrough signals between 2018 and 2023, select half at random, and commit to a decade of investment. For biomedicine, a six year window should yield about 30 topics with the potential to produce a breakthrough. Providing strong support to half of these might be accomplished for $300 million a year. That’s roughly half of the recent annual budget of the NIH Common Fund or around 20% of the fiscal year 2025 budget for ARPA-H. After five years, then again at ten, compare to see which group — the one that was actively managed, or the control — produced more breakthroughs, and on what timescale. Although we used biomedicine as an example, the same experiment could just as well be run for physics, materials science, or any other discipline. Any attempt to undertake such an experiment should keep three points top of mind. First, we can predict the topic of future breakthroughs, but the people and vision for how to move the work forward are still important. In practice, this means success requires active program managers with the expertise to develop the science and the authority to do so, including by recruiting investigators. Second, we would be wise to learn from the failures of past attempts to fund transformative research. High among these are funding modestly repackaged work, confusing the genuinely novel with the merely unfamiliar, and relying too much on incumbent investigators. All of these risks can be mitigated by thoroughly and intelligently integrating high quality data into portfolio management. Finally, we need to have patience. Even with strong funding support, producing a breakthrough takes time. If supporting breakthroughs is the best way to nurture the birth of new fields, we also need to accurately describe and properly manage the other two stages, so that we invest wisely throughout the productive lifetime of ideas and divest once they reach the point of diminishing returns. We would benefit from more study of all of these phases, especially the transition from one to another. More research could answer questions like: When does a breakthrough become an established field? How do the availability of funding, the size and characteristics of the available workforce, and the accumulation of evidence that disagrees with prevailing models affect a field’s decline? Exactly how do old ideas give birth to new ones, and can we speed up the process? The more we understand about the dynamics of scientific progress, the better we can maximize the odds that our curiosity leads to results. I’d call that finding a way to make our own luck.
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Merchants of Doubt and the attacks on Extreme Event Attribution science
Last week, I attended a meeting at Columbia University on attribution science and climate law, hosted by the Sabin Center. It was a fantastic event, bringing together scientists and legal experts working at the intersection of extreme event attribution and climate law. Subscribe For those unfamiliar with it, extreme event attribution attempts to quantify the contribution of climate change to an extreme event. For example, several groups analyzed the impact of climate change on Hurricane Harvey’s enormous rainfall totals over Houston, Texas and they found that climate change increased rainfall by 15 to 38%. One thing that came up again and again was how terrified fossil-fuel interests are of extreme event attribution science. They are acutely aware that this research could land them in court. And losing those cases would leave them legally liable for billions of dollars in climate damages. Because the legal stakes are so high, the blowback has turned ugly. I spoke with several scientists at the meeting who are facing ongoing harassment over their work. This blowback is a coordinated campaign to make the entire field look suspect. The goal is to create the impression that attribution science is too uncertain, too political, or too conflicted to be useful in court or in public policy. The strategy is not based on actual science or evidence of misconduct, but on the generation of doubt. The new Merchants of Doubt We’ve seen this before. In fact, not that long ago: We only have to go back a year to the Department of Energy (DOE) Climate Working Group (CWG) report to see an example of using doubt as the tool to push back against well-established science. This strategy is laid out in an email from a member of the CWG, Dr. Roy Spencer, that was released during litigation over the Climate Working Group process. The key quote is: About all I can hope is that what we write will provide sufficient “reasonable scientific doubt” regarding the science claims in the 2009 TSD [technical support document], based upon almost 2 decades of new science, to call into question the original reasoning for the EPA Administrator’s decision that CO2 presents a threat to human health and welfare. This statement is strong evidence that at least some members of the committee were working to support a particular policy outcome: revoking the Endangerment Finding. The email also explains how they planned to do it: by attempting to generate “reasonable doubt”. This is going to be hard, Spencer implies. Despite falsely claiming that “2 decades of new science” weakens the case, Spencer explicitly acknowledges that the actual peer-reviewed science of climate change overwhelmingly rejects his position: But if the science argument is decided upon by a vote, or by the number of published citations, we lose the science argument. We can go back even further: This CWG email shares unmistakable DNA with the infamous 1969 tobacco memo that declared: “Doubt is our product, since it is the best means of competing with the ‘body of fact’ that exists in the mind of the general public. It is also the means of establishing a controversy.” The tobacco memo also acknowledges the limit of this strategy: Like the CWG, they knew the science was not on their side. Share The new new Merchants of Doubt The people attacking the IPCC chapter on extreme event attribution are the newest iteration of the Merchants of Doubt. Their goal, like all Merchants before them, is to introduce doubt into the process. Because the report is not even out yet, they cannot attack its conclusions. So they are attacking the authors instead. Here is a press release from the House Science, Space, and Technology Committee: In the letter, the Chairmen express concerns about potential conflicts of interest involving members of the Attribution Committee, stating that “publicly available information suggests a troubling pattern” in which committee members are affiliated with nonprofits that support climate accountability lawsuits, “raising the appearance of impropriety and member bias.” To be clear, this is just innuendo. There is no actual evidence of bias. And given the robust process that these reports go through, including multiple lines of peer review, it seems very unlikely that significant bias can survive into the report. When the report comes out, critics will have the opportunity to make legitimate criticisms of the report — if any exist. If none do, however, they’ll still make criticisms, but they’ll be bogus, simply designed to generate doubt. We’ll see. A note to the press: Fix your frame To any journalists reading this: The public debate over extreme event attribution science is not going away. The science is simply too dangerous to fossil-fuel interests for them to stop fighting it. You very well might be assigned to write an article about this area of research in the future. When you do, do not automatically adopt the framing that climate misinformers want you to use. They want you to frame the story around questions like: Are climate scientists trying to put their thumb on the scale to achieve a predetermined, politically motivated result? Are climate scientists improperly letting their politics invade the science of the IPCC? That frame is a trap. Instead, you need to view this through the historical lens of the Merchants of Doubt. How does the ecosystem of doubt operate? Who funds it? What methods do they use to misrepresent science and slime researchers? What scientific results are they trying to keep people from understanding are legitimate? Ultimately, you instead need to focus your article on the generation of doubt as a way to maintain the fossil fuel industry’s social and legal license to keep burning oil, gas, and coal. If you treat the misinformers’ frame as a legitimate, good-faith scientific critique, you are helping them produce doubt. Don’t do it. Don’t be a Merchant of Doubt. Thanks for reading The Climate Brink! Subscribe for free to receive new posts and support our work. Subscribe other stuff The Staying Curious Substack has an interesting post about the different flavors of climate sensitivity. This is crucial information if you want to understand how scientists think about how much warming the Earth will experience. I’d be grateful if you could hit the like button ❤️ below! It helps more people discover these ideas and lets me know what’s connecting with readers.
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President Trump seeks control of science funding
The White House Office of Management and Budget is moving to take more control of billions of dollars in federal grants. Critics say the proposed change would jeopardize the integrity of U.S. science.
President Trump seeks control of science funding
The White House Office of Management and Budget is moving to take more control of billions of dollars in federal grants. Critics say the proposed change would jeopardize the integrity of U.S. science.
President Trump seeks control of science funding
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