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“It’s shoot first, ask questions later,”

Each one of these incidents resulted from unique events. But activists and researchers say they stem from a convergence of bigger factors — increased fear of crime and an attendant surge in gun ownership, increasingly extreme political messaging on firearms, fearmongering in the media and marketing campaigns by the gun industry that portray the suburban front door as a fortified barrier against a violent world.

“The gun lobby markets firearms as something you need to defend yourself — hammers in search of nails,”

The perception that crime, especially violent gun crime, has increased is not a manufactured myth. National murder rates have climbed by about a third since 2019, according to government data, even accounting for modest declines in fatal shootings over the past 18 months.

Gun purchases rose during the pandemic and the unrest and racial-justice protests after the murder of George Floyd. Nearly 20 percent of American households bought a gun from March 2020 to March 2022, and about 5 percent of Americans bought a gun for the first time,

More than 30 states also have “stand your ground” laws. Some have recently strengthened their “castle doctrine” laws, making it more difficult to prosecute homeowners who claim self-defense in a shooting.

“People become paranoid and over-worried — and then comes an unannounced knock on their door,”

But several large-scale studies have suggested that the laws have few benefits, increase the likelihood of gun violence and might discriminate against minority groups, especially Black people.

The effect of self-defense laws protecting homeowners and gun owners is fiercely debated, with proponents arguing that their mere presence deters criminal behavior or civil disorder

shootings in which white people shot Black people were nearly three times as likely to be found “justified” compared with cases where white people shot other white people.

A 2023 analysis of recent academic research by the nonpartisan RAND Corporation found no evidence that such laws had the deterrent effect that their sponsors claimed, and there was some indication, while not conclusive, that the laws might account for some increases in gun violence.

weapons were actually more likely to be used in suicides, discharged accidentally, stolen or brandished in domestic disputes, than used to fend off an external attack.

The National Rifle Association and other gun-rights groups have long disputed such assessments, citing surveys that show far greater use of weapons for legitimate self-defense.

About a third of the roughly 16,700 gun owners surveyed in a study led by William English, a Georgetown University business school professor, said they had used their guns for self-defense, prompting Mr. English to estimate that as many as 1.6 million people in the country had defended themselves with a weapon that year.

But only a handful of cancers—of the breast, lung, colon and cervix—have screening tests recommended by the U.S. Preventive Services Task Force

Many companies are developing blood tests that can detect cancer signals before symptoms occur, and Grail’s is the most advanced. A study found it can identify more than 50 types of cancer 52% of the time and the 12 deadliest cancers in Stages I through III 68% of the time.

There’s a hitch. The test costs $949 and isn’t covered by Medicare or most private insurance.

The trouble is that this cancer is almost never caught early. There’s no routine screening for it, and symptoms don’t develop until it is advanced. Mr. Royse, 64, had no idea he was sick until he took a blood test called Galleri, produced by the Menlo Park, Calif., startup Grail. He had surgery and chemotherapy and is now cancer-free.

Mr. Royse visited Grail’s website, which referred him to a telemedicine provider who ordered a test. Another telemedicine doctor walked him through his results, which showed a cancer signal likely emanating from the pancreas, gallbladder, stomach or esophagus.

An MRI revealed a suspicious mass on his pancreas, which a biopsy confirmed was cancerous. Mr. Royse had three months of chemotherapy, surgery and another three months of chemotherapy, which ended last February. Because pancreatic cancer often recurs, he gets CT and MRI scans every three months. In addition, he has signed up for startup Natera’s Signatera customized blood test, which checks DNA specific to the patient’s cancer and can signal its return before signs are visible on the scans

Grail’s test likewise looks for DNA shed by cancer cells, which is tagged by molecules called methyl groups that are specific to a cancer’s origin. Grail uses genetic sequencing and machine learning to recognize links between DNA methyl groups and particular cancers

The test “is based on how much DNA is being shed by tumor,” Grail’s president, Josh Ofman, says. “Some tumors shed a lot of DNA. Some shed almost none.

ut slow-growing tumors typically aren’t shedding a lot of DNA.” That reduces the probability that Grail’s test will identify indolent cancers that pose no immediate danger.

Grail’s test has a roughly 0.5% false-positive rate, meaning 1 in 200 patients who don’t have cancer will get a positive signal

Its positive predictive value is 43%, so that of every 100 patients with a positive signal, 43 actually have cancer

the legislation’s price tag could reduce political support. According to one private company’s estimate, the test could cost the government $39 billion to $145 billion over a decade. Mr. Goldman counters that analysts usually overestimate the costs and underestimate the benefits of medical interventions.

Because Grail uses machine learning to detect DNA-methylation cancer linkages, the Grail test’s accuracy should improve as more tests and patient data are collected

regulators may balk at approving the test, and insurers at covering it, until it becomes cheaper and more reliable.

How would the FDA weigh the risk that a false positive on a test like Grail’s could require invasive follow-up testing against the dire but hard-to-quantify risk that a deadly cancer wouldn’t be caught until it’s much harder to treat? It’s unclear.

some experts urge the FDA to require large randomized controlled trials before approving blood cancer tests. “Multicancer screening would entail tremendous costs and potentially substantial harms,” H. Gilbert Welch and Tanujit Dey of Brigham and Women’s Hospital wrote

Dr. Welch and Mr. Dey also suggested that companies should be required to prove their tests reduce overall mortality, even though the FDA doesn’t require drugmakers to prove their products reduce deaths or extend life. Clinical trials for the mRNA Covid vaccines didn’t show they reduced deaths.

One alternative is to rely on real-world studies, which Grail is already doing. One study of patients 50 and older without signs of cancer showed that the test doubled the number of cancers detected.

One recurring problem he has seen: “Epidemiologists are always getting cancer wrong,” he says. “Epidemiologists a decade ago said U.S. overtreats cancers. Well, no, the EU undertreats cancer.”

A 2012 study that he co-authored found that the higher U.S. spending on cancer care relative to Europe between 1983 and 1999 resulted in significantly higher survival rates for American patients than for those in Europe

By his study’s calculation, U.S. spending on cancer treatments during that period resulted in $556 billion in net benefits owing to reduced mortality.

He expects Galleri and other multicancer early-detection tests to reduce deaths and produce public-health and economic benefits that exceed their monetary costs

Expanding access to multicancer early-detection tests could also help solve the chicken-and-egg problem of drug development. Because few patients are diagnosed at early stages of some cancers, it’s hard to develop treatments for them

the positive predictive value for some recommended cancer screenings is far lower. Fewer than 1 in 10 women with an abnormal finding on a mammogram are diagnosed with breast cancer.

Mr. Royse makes the same point with personal force. “I would be dead right now if not for multicancer early-detection testing,” Mr. Royse told an FDA advisory committee last fall. “The longer the FDA waits, the more people are going to die. It’s that simple.”

Postolnikov has been under increasing scrutiny in the criminal investigation into the Trump Media merger. Most recently, he has been listed on search warrant affidavits alongside several associates – one of whom was indicted last month for money laundering on top of earlier insider-trading charges.

Trump Media then received the loans from ES Family Trust: $2m on 23 December 2021, and $6m on 17 February 2022.

Part of the problem was that Trump Media struggled to get financing because traditional banks were reluctant to lend millions to Trump’s social media company in the wake of the January 6 Capitol attack, Wilkerson said.Trump Media eventually found some lenders, including ES Family Trust, but the sequence of events was curious.

S Family Trust was established on 18 May 2021, its creation papers show. Postolnikov’s “user” access to the account was “verified” on 30 November 2021 by a Paxum Bank manager in Dominica. The trust was funded for the first time on 2 December 2021

In late 2021, Trump Media was facing financial trouble after the original planned merger with Digital World was delayed indefinitely when the Securities and Exchange Commission opened an investigation into the merger, Trump Media’s since-ousted co-founder-turned-whistleblower Will Wilkerson recounted in an interview.

Oddly, the notes were never signed. But the investment in Trump Media proved to be huge: while precise figures can only be known by Trump Media, ES Family Trust’s stake in Trump Media is worth between $20m and $40m even after the sharp decline of the company’s share price in the wake of a poor earnings report

The loans came in the form of convertible promissory notes, meaning ES Family Trust would gain a major stake in Trump Media because it was offering the money in exchange for Trump Media agreeing to convert the loan principal into “shares of Company Stock”.

The ES Family Trust account also appears to have benefited Postolnikov personally. As the criminal investigation into the Trump Media deal intensified towards the end of last year, the trust recorded several transfers to Postolnikov with the subject line “Partial Loan Return”.In total, the documents showed that the trust transferred $4.8m to Postolnikov’s account, although $3m was inexplicably “reversed”.

The reason for the trust’s creation remains unknown. Aside from the money that went to Trump Media, the trust’s statements show the trust has directly invested money with only two other companies: $10.8m to Eleven Ventures LLC, a venture capital firm, and $1m to Wedbush Securities, a wealth management firm.

The creation papers also contained something notable: a declaration that, if the original trustee – a Paxum employee named Angel Pacheco – stepped down from the role, his successor would be a certain individual named Michael Shvartsman.

Last month, federal prosecutors charged Michael Shvartsman, a close associate of Postolnikov, with money laundering in a superseding indictment after previously charging him and two others in July with insider-trading Digital World shares. Shvartsman and his co-defendants pleaded not guilty.

nformant for the DHS, court filings show: in one March 2023 meeting with the informant and an associate, Shvartsman mentioned a friend who owned a bank in Dominica and made bridge loans to Trump Media.

“[Shvartsman’s associate] told the [confidential informant] that he does not think the SEC would be able to go after [Shvartsman] for his part in the investment but mentioned that [Shvartsman] essentially provided ‘bridge financing’ for the firm behind the Truth Social media platform,” it said.

The investigation into potential money laundering appears to have started after Wilkerson’s lawyers Phil Brewster, Stephen Bell and Patrick Mincey alerted the US attorney’s office in the southern district of New York to the ES Family Trust loans in October 2022.

Months later, in June 2023, the FBI expanded its investigation to work jointly with the Department of Homeland Security’s El Dorado taskforce, which specializes in money laundering, and its Illicit Proceeds and Foreign Corruption group, which targets corrupt foreign officials who use US entities to launder illicit funds.

Their reasoning is straightforward: These companies have decided that the best way to make generative AI better is to build bigger AI models. And that is really, really expensive, requiring resources on the scale of moon missions and the interstate-highway system to fund the data centers and related infrastructure that generative AI depends on

“If we’re going to justify a trillion or more dollars of investment, [AI] needs to solve complex problems and enable us to do things we haven’t been able to do before.” Today’s flagship AI models, he said, largely cannot.

Now a number of voices in the finance world are beginning to ask whether all of this investment can pay off. OpenAI, for its part, may lose up to $5 billion this year, almost 10 times more than what the company lost in 2022,

Over the past few weeks, analysts and investors at some of the world’s most influential financial institutions—including Goldman Sachs, Sequoia Capital, Moody’s, and Barclays—have issued reports that raise doubts about whether the enormous investments in generative AI will be profitable.

Dario Amodei, the CEO of the rival start-up Anthropic, has predicted that a single AI model (such as, say, GPT-6) could cost $100 billion to train by 2027. The global data-center buildup over the next few years could require trillions of dollars from tech companies, utilities, and other industries, according to a July report from Moody’s Ratings.

generative AI has already done extraordinary things, of course—advancing drug development, solving challenging math problems, generating stunning video clips. But exactly what uses of the technology can actually make money remains unclear

At present, AI is generally good at doing existing tasks—writing blog posts, coding, translating—faster and cheaper than humans can. But efficiency gains can provide only so much value, boosting the current economy but not creating a new one.

Right now, Silicon Valley might just functionally be replacing some jobs, such as customer service and form-processing work, with historically expensive software, which is not a recipe for widespread economic transformation.

McKinsey has estimated that generative AI could eventually add almost $8 trillion to the global economy every year

“Here, we can manufacture intelligence.”

Tony Kim, the head of technology investment at BlackRock, the world’s largest money manager, told me he believes that AI will trigger one of the most significant technological upheavals ever. “Prior industrial revolutions were never about intelligence,”

this future is not guaranteed. Many of the productivity gains expected from AI could be both greatly overestimated and very premature, Daron Acemoglu, an economist at MIT, has found

AI products’ key flaws, such as a tendency to invent false information, could make them unusable, or deployable only under strict human oversight, in certain settings—courts, hospitals, government agencies, schools

AI as a truly epoch-shifting technology, it may well be more akin to blockchain, a very expensive tool destined to fall short of promises to fundamentally transform society and the economy.

Researchers at Barclays recently calculated that tech companies are collectively paying for enough AI-computing infrastructure to eventually power 12,000 different ChatGPTs. Silicon Valley could very well produce a whole host of hit generative-AI products like ChatGPT, “but probably not 12,000 of them,

even if it did, there would be nowhere enough demand to use all those apps and actually turn a profit.

Some of the largest tech companies’ current spending on AI data centers will require roughly $600 billion of annual revenue to break even, of which they are currently about $500 billion short.

Tech proponents have responded to the criticism that the industry is spending too much, too fast, with something like religious dogma. “I don’t care” how much we spend, Altman has said. “I genuinely don’t.

the industry is asking the world to engage in something like a trillion-dollar tautology: AI’s world-transformative potential justifies spending any amount of resources, because its evangelists will spend any amount to make AI transform the world.

in the AI era in particular, a lack of clear evidence for a healthy return on investment may not even matter. Unlike the companies that went bust in the dot-com bubble in the early 2000s, Big Tech can spend exorbitant sums of money and be largely fine

perhaps even more important in Silicon Valley than a messianic belief in AI is a terrible fear of missing out. “In the tech industry, what drives part of this is nobody wants to be left behind. Nobody wants to be seen as lagging,

Go all in on AI, the thinking goes, or someone else will. Their actions evince “a sense of desperation,” Cahn writes. “If you do not move now, you will never get another chance.” Enormous sums of money are likely to continue flowing into AI for the foreseeable future, driven by a mix of unshakable confidence and all-consuming fear.