With his approval ratings in the gutter, US president Donald Trump is cooking up another cash advance for the American people, and it’s a doozy.

At the first-ever Republican Midterm Convention in Dallas, Texas — which is really more of a MAGA pep rally than a legitimate party assembly — President Trump promised that “if the Republicans win the House of Representatives and the United States Senate, both of them, I will issue a dividend to every adult citizen in the United States of America for $5,000,” the BBC reported.

“Because we’ve done so well and because our country is making so much money, that only I can make you this promise,” Trump told supporters in a slightly garbled quote, to rapturous applause. As Al Jazeera noted, the president was scant on the details around the payments, saying only that the money would have to be spent on US goods and services.

“We don’t want you going to Canada to spend the money,” Trump admonished the crowd.

Split across the entire adult-aged population of the US, we’re talking 270 million $5,000 checks. While that would no doubt provide some relief for working class families struggling under Trump’s erratic economic regime, it would immediately cost taxpayers $1.3 trillion, before factoring in administrative costs and hits to the inflation rate, per Al Jazeera.

Such a payout would essentially land straight on the US national balance sheet, Fortune explains, which is already so far in the red that it suffers a $2 trillion annual deficit.

Though the math on this is pretty simple, the massive figure leaves more questions around the theoretical payout than answers. For example, if Republicans have control of the House and the Senate, why not issue the $5,000 check now, to demonstrate what the party can do for voters? Given that Trump’s second term has been defined by broken promises and financial misconduct, voters from across the political spectrum are quickly running out of patience for more GOP can-kicking.

Either way, we’re talking about an 80 year old man who recently started believing he was lifted from the rubble of the World Trade Center collapse — which is to say there’s a pretty good chance he won’t remember his $1.3 trillion promise come November.

More on Trump: US Military in Chaos as Trump Shares AI Video of Nonexistent Attack on Iran

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With opposition to AI continuing to grow, a top AI lab is building out a massive surveillance apparatus meant to keep a close eye on dissenters and predict when the next groundswell of protest might occur.

News of Anthropic’s system was first reported by the American Prospect, which spoke with Anthropic senior security officials and indexed job postings to get an understanding of the dragnet.

On top of keeping tabs on protests in the vicinity of Anthropic offices, the publication notes that the AI lab is taking a “pre-crime” approach to watching for potential civil unrest.

To give an example, the Prospect points out an incident shared by Anthropic security operations managers Keon Ellison and Zach Melvin, alongside James Neufeld, CEO of risk detection company Samdesk.

“Last year we had an executive travel into a major city when we received some intelligence through Samdesk about a planned protest,” Ellison said candidly. After the scheduled protest was moved up an hour due to a mix-up with police permits, the security chief said that “Samdesk gave us about 60 minutes of advanced notice that the protest organizers had moved the timeline.”

“That extra hour was critical,” Ellison continued. “Without it our executives would have departed their meetings, they would have ran right into the heart of the disruption. What could have been a high-stress situation was really mitigated through early detection through Samdesk and giving us that information.”

Outside of anticipating protests, there were also cases where Anthropic reported conversations held with its AI chatbot Claude to police. Though there have been calls to increase safety guardrails on large language models, Anthropic’s approach sounds bizarre.

As the San Francisco Standard reported in August, Anthropic reported a San Francisco man to the cops after he told Claude he was holding a rifle, and had the company’s CEO Dario Amodei “in his sights.” Yet when Anthropic reported the conversation to Bay Area police, the company refused to provide the man’s chat logs — as the Prospect observes, essentially reporting the man without sharing any tangible evidence of misconduct.

“The goal,” as Anthropic’s security manager said in the interview, “would be transforming operations from reactive information to gathering proactive and predictive and preventative threat engagement and management. That’s the kind of operational maturity that makes sense for protecting high-value targets in any industry.”

More on AI: Protesters Arrested After Storming OpenAI Lobbying Office

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Back in August, a massive leak in El Reno, Oklahoma spewed close to four million gallons of local water into the ground, forcing the city into an unofficial stand-still.

The cause was quickly traced back to a damaged water line belonging to a Bitcoin-mining data center operated by the company Athlon BT. As ABC5 reported at the time, city inspectors trawling the building’s exterior uncovered the failed water line, as well as violations around drainage, maintenance and access, and expired building permits.

Weeks later, an investigation by the local fire marshal inside the El Reno data center uncovered a further laundry list of horrifying violations.

The inspectors discovered vessels full of flammable liquid stored near combustible materials, Oklahoma station KFOR reported, in addition to fire extinguishers that weren’t properly maintained.

Electrical equipment and crucial wiring was also found in disrepair, while a lockbox meant to hold keys for emergency first responders to easily access the facility was left empty. Vegetation on the building’s exterior was in violation of the fire code.

As a result of the copious fire hazards, the city gave the data center a “failing” grade, indicative of a building with severe structural or safety failures.

When it comes to data centers, fire safety is no small matter. The structures are already highly prone to conflagration due to massive electrical loads, lithium-ion batteries, and chips that run at extremely high temperatures.

In one Ohio township, fire fighters reported being overwhelmed by the high volume of calls to two local data center campuses. In addition to tying up first responders, data center fires are costly affairs for taxpayers, as property tax abatements mean nearby residents — not data center owners — can be the ones fronting the bill whenever the fire company gets a call.

More on data centers: Data Center Caught Watering Its Lavish Lawn While Human Neighbors Are on Year-Long Water Restriction

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These days, large language models are pushing the line between schizophrenic break and reality closer than ever before.

In a wild new post that’s going viral on X-formerly-Twitter, an enterprising young biochemist named Douglas Yao showcased a new drug he’s been developing with the aid of ChatGPT. He’s not employed by any pharma company, and his drug lab is setup on a couple folding tables in his garage.

Specifically, Yao enthuses about a new drug he calls “PAC-3310,” which he says is meant to treat schizophrenia. “It was designed by ChatGPT,” Yao explains, “and I synthesized it in a chemistry lab I built in my garage.”

The result is a small vial of yellow powder — the first sample of 3310, apparently — which Yao says is modeled after the recently-authorized antipsychotic Cobenfy, “but improved.”

This vial contains a new drug called PAC-3310. It was designed by ChatGPT, and I synthesized it in a chemistry lab I built in my garage.

PAC-3310 is a new selective M4 muscarinic receptor agonist for treating schizophrenia – similar to the recent breakthrough drug Cobenfry, but… pic.twitter.com/o7z6iLR50T

— Douglas Yao (@DouglasYaoDY) September 8, 2026

On his GitHub page, Yao boasts that he’s used AI to “design several thousand new small molecule drugs” over the past year, including a “new Alzheimer’s drug,” which he’s developing in addition to the schizophrenia treatment.

“I then taught myself synthetic chemistry, built a chem lab in my garage, and synthesized a hundred of them,” he continued. “I’m now testing these compounds in cell lines and mice.”

But whatever the one-man pharma lab hopes to accomplish is difficult to say. Yao references the fact that “drug developers typically spend tens of millions of dollars generating pre-clinical efficacy evidence for a new drug,” saying that “my approach can do this at 1/1000 the cost.” This seems to suggest dreams of someday manufacturing the various drugs on a massive scale for human consumption — a process that would take years of grueling and expensive work for a well-resourced drug lab, let alone a solo entrepreneur using a box fan as a fume hood.

For instance, to even approach the Food and Drug Administration’s “New Drug Application” — itself a costly 12-month process requiring inspection of the facility where the drug will be manufactured — one first has to conduct rounds of preclinical testing followed by three phases of clinical trials. Forget “tens of millions,” as Yao mentions; this is a process that can easily cost several billion.

Even then success is far from guaranteed, as only 13.8 percent of drugs that enter clinical trials go on to obtain full approval from the FDA.

While Yao might have been right at home in the free-wheeling research landscape of the 1970s, we no longer live in a world where a mad genius can synthesize hundreds of new drugs a year from a private lab. For one thing, the regulatory environment is much more demanding, as outlined above, to say nothing of the fact that all the low-hanging fruit has been picked from the vine decades ago.

When it comes to Yao’s ChatGPT-generated Alzheimer’s treatment, the landscape is particularly fraught. As one 2019 study found, no new drug has been approved to treat Alzheimer’s since 2003, and not for a lack of trying: as the study notes, over 200 proposed substances meant to treat the disease have either failed in clinical trials or been abandoned by their creators.

The graveyard of failed Alzheimer’s treatments is so vast that the renowned organic chemist Derek Lowe has built a blog on drug discovery which routinely features after-action reports on failed substances designed to treat the neurodegenerative disease. Simply put, to think that ChatGPT alone is enough to overcome these scientific and institutional hurdles is delusional.

Replies to Yao’s post were quick to point out the irony here, of using ChatGPT — which is well-known for leading vulnerable users down dangerous breaks from reality — to synthesize drugs to treat cognitive diseases like Alzheimer’s and schizophrenia.

“Hello schizophrenic, take this medicine that chatgpt made for you,” one poster quipped on X.

Another replied that “believing you single-handedly cured schizophrenia on a commercial laundry folding table in a garage is, ironically, a classic symptom of schizophrenia.”

More on ChatGPT: Man Obliterated When Court Obtains His ChatGPT Transcripts

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