China has emerged as a central player in the growing debate over artificial intelligence regulation, prompting calls for global cooperation on a “slow down” agreement.
… Despite echoing calls for regulation from lawmakers and AI industry leaders, President Donald Trump has said the United States must prioritize winning the global AI race over slowing development. Guo Jiakun, a spokesperson for China’s Ministry of Foreign Affairs, shared similar sentiments during a press conference Monday when asked about AI regulations.
“Fearmongering, confrontation and vicious competition will only disrupt the process of global AI governance which serves no one’s interest,” he said. — Read More
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Bromancing the Stone
Over the past several weeks, the AI sector has become a magnificent anthropological study in collective hysteria—a caricature of a serious industry completely unmoored from reality. As self-important executives across the globe rush to microphones to sound the alarm, the line between saving humanity and saving a stock price has entirely evaporated. If you’re confused, you’re not alone.
To understand the current state of artificial intelligence, you must look past the dense fog of corporate PR and institutionalized fear. Strip away the math and the jargon, and you find a time-honored Silicon Valley tradition: a high-stakes financial theater where truth is the damsel in distress, tied to the train tracks, while a band of billionaire eccentrics plays the roles of both the villains and the caped crusaders chasing the elusive stone.The “stone” at the heart of this multi-billion-dollar romance is Artificial General Intelligence (AGI), a theoretical silicon messiah that tech titans dangle before the public to keep stock prices high and regulators at bay.
Consider the stage-managed grandiosity of recent weeks. On one side of the valley, Greg Brockman and Nvidia’s Jensen Huang pace the floors of heavily air-conditioned auditoriums, hands waving like television evangelists, heralding the imminent arrival of Artificial General Intelligence (AGI). It is a beautiful, cinematic pitch: the silicon messiah is coming, and it will cure disease, solve climate change, and incidentally justify Nvidia’s dizzying, gravity-defying market capitalization.
But then, the script takes a sharp, theatrical turn. Suddenly, the very priests who built the temple are rushing out into the street, shouting that the altar is on fire.
Within days of each other, young prodigies and weathered executives began sounding the alarm. Jacob Coxon, a brilliant, terminally earnest safety researcher, dramatically walked away from his keyboard, leaving behind a viral trail of warnings that the industry is casually gambling with human survival. A quick confirmation by Evan Hubinger alongside OpenAI’s Jakub Pachocki’s essay, An Alien Mind, the message was clear and terrifying: the machine is becoming too powerful, self-improving beyond our control, and it might just destroy humanity by the end of the decade.
The chorus rose to the executive suites. Dario Amodei of Anthropic published a sweeping essay pleading for a synchronized pause. Sam Altman of OpenAI nodded in solemn, public agreement, while Elon Musk of xAI chimed in from the digital ether, all calling for a coordinated industry slowdown to save humanity from itself.
It was a masterclass in what a cynic might call “existential marketing.”
To the casual observer, it looks like a boardroom full of Oppenheimers weeping over their creation. But if you follow the money, an entirely different, far uglier picture emerges. Over at David Sacks’ firm, the venture capitalist didn’t buy the tears for a second. Sacks took to the microphone to slam the top executives, bluntly accusing them of trying to bypass antitrust laws to form a classic market cartel.
And why would they want a cartel? Because behind the closed doors of San Francisco boardrooms, the sweat is beginning to bleed through the custom-tailored hoodies.
This isn’t the first time the Valley has tried to pull off this kind of regulatory theater. We’ve seen this script before. Back in 1995, Bill Gates looked out from his fortress in Redmond and realized Netscape’s web browser was about to turn Windows into a glorified, irrelevant set of plumbing. Gates didn’t panic by engineering a better product; he panicked by trying to rewrite the rules of the road. Microsoft executives famously marched into Netscape’s Mountain View headquarters and tried to slice up the internet market like an afternoon cake, politely suggesting that Netscape stick to Mac and Windows 3.1 while Microsoft took everything else. When Netscape refused to play ball, Microsoft simply suffocated them by tying Internet Explorer to the operating system and cutting off their oxygen. Altman, Amodei, and Musk are playing the exact same game, just with a modern, apocalyptic twist. When you can’t guarantee you’ll win a fair fight on product merit, you try to partition the market. Except this time, instead of using operating system monopolies to choke out the competition, they are trying to use the threat of a science-fiction apocalypse to trick Uncle Sam into building the moat for them.
The cold, hard truth of the AI business is that it depends on a terrifyingly small handful of customers. These are massive corporations buying bulk compute to figure out what, exactly, they are supposed to do with it. For the past two years, the spending only went up. But recently, the data scientists at corporate spend-management platform Ramp noticed a chilling anomaly in the ledger. For the first time since the boom began, spending among the top 1% of AI buyers has begun to contract. The enterprise customers, having spent millions on automated chatbots that occasionally lie about the company’s return policy, are quietly cutting back.
When you see AI labs suddenly increase their frantic pressure for government regulation, it isn’t because they are frightened of a science-fiction Terminator waking up in a server rack. It is because the financial picture is getting worse by the day. They are begging for government-mandated “safety” fences because fences keep out competitors. They want compliance costs so astronomicallyhigh that no scrappy startup can ever challenge their territory. They are trying to lock in their market share before the venture funding dries up entirely.
But the ultimate joke—the real house of cards—is that even if the U.S. government grants them their cartel, the frontier cannot be paced.
Enter the eccentric misfits from across the Pacific. While Silicon Valley was busy calculating how many billions it takes to train a model to write corporate emails, a Chinese startup called DeepSeek quietly changed the laws of economic gravity. In September, DeepSeek rolled out models priced so aggressively low that it made the American labs look like they were selling landlines in the age of the iPhone. DeepSeek’s models are priced cheaper without prompt caching than Anthropic’s or OpenAI’s are with it. On a blended price index, DeepSeek’s inference costs arrived on the order of 200 times cheaper than Anthropic’s average pricing.
The brilliant, eccentric hackers proved that you don’t need a hundred-billion-dollar sovereign wealth fund to build frontier intelligence; you just need better engineering and a complete disregard for Silicon Valley’s margin expectations. Adding to the geopolitical friction, the Chinese government asserted that “Fear mongering, confrontation, competition will just disrupt [the] process of global AI governance.”
This leaves the Western tech titans in a catastrophic squeeze. Their domestic customers are tightening their purses, a foreign competitor has commoditized their only product by a factor of two hundred, and their massive infrastructure debts are coming due.
So where does the truth lie?
It lies exactly where President Donald Trump suggested when he breezily dismissed the existential warnings as “things that won’t happen,” declaring that the United States must simply push ahead to win the geopolitical race. China’s Minister of State Security, Chen Yixin, echoed the sentiment, saying AI has become “the main battleground for global technological competition and a new arena for strategic rivalry among major powers.” In a world governed by raw hubris and nationalist competition, a polite corporate agreement to slow down is an illusion. Besides, the federal government isn’t about to suspend the Sherman Antitrust Act just so a handful of venture-backed tech barons can legally collude on market supply.
The existential threat isn’t that a super-intelligence is going to turn humanity into batteries. The threat is that the entire, multi-billion-dollar apparatus is built on bad math, artificial scarcity, and a desperate desire to build a regulatory moat before the world realizes that the emperor has no clothes.
The tech barons aren’t trying to save us from the stone; they are just desperately trying to figure out how to keep bromancing it until the check clears.
The hard part of an MCP gateway is auth
Sierra’s Mihai Parparita published field notes on building the company’s internal MCP gateway, and the framing is the most honest thing in it: MCP is “ancient” technology by AI-industry standards, so wiring agents to internal systems should have been straightforward, and instead it became “another engineering iceberg”. The tip above the waterline is the part that demos well: 89% of Sierra employees now connect agents to 45 different services from a single page. The mass underneath is auth.
It’s the best field report on internal agent platforms this year, and every team standing up an agent gateway should read it before writing a line of code. But walk the seven lessons in order and a pattern shows up. The expensive ones are barely about MCP at all. They’re about identity, scopes, consent, and audit. Enterprise software has worked on those four for twenty years, and agents have made all four urgent again at once, in a context where the old answers do not transfer cleanly. — Read More
The Rise of the Forward Deployed Engineer — and How To Do the Job Right
FDEs have the hottest job in AI. Labs, startups and PE firms are all hiring engineers to sit inside their customers’ operations and solve their problems. Almost none of them agree on what those engineers are supposed to accomplish, or what the strategy underneath the hiring actually is.
I’m Vinoo, CEO of Kepler, the deterministic infrastructure for AI. I’ve built pieces of the forward deployed function three times, at three different institutions, over the course of over a decade. Here’s what I’ve seen work, what I’ve seen fail, and where I think this goes. — Read More
We Must Pace the Frontier (Dario Amodei)
I have worked on AI for the last twelve years because I believe it could dramatically raise the quality of human life. I’ve written often about these incredible benefits: I believe that AI could cure most major diseases in the next 5–10 years, greatly accelerate economic growth rates, create a world of abundance and empowerment, and usher in a renaissance of democracy and freedom. I feel the urgency personally. My own father died of a disease that was cured just a few years after his death, and I myself survived an early-stage cancer that would not have been treatable even fifty years ago. Carefully wielded, AI can be the latest in a long line of technological miracles that have uplifted and ennobled humanity.
But like many technologies before it, AI brings risks, and because it is such a powerful technology, these risks are serious. I’ve written a lot about them too. They include the risk of losing control of AI systems, misuse of AI for cyberattacks and bioterrorism, and serious economic disruption. A race to the bottom, spurred by commercial incentives, can make these risks more acute. — Read more
Neurometric Task Explorer
Tell us the job.We’ll find the right model. Neurometric now has a new site where you can compare the price of any task on various models. — Read More
Now Rinse
Mother Nature likes a clean kitchen. She has scrubbed the counters five times already. Each time, a different accident ruined the meal. Now, she is getting the sponge out again.
The Five Previous Resets
The earth runs on a simple rule. When a tenant ruins the apartment, the landlord clears the building.
— The First: Ice locked the water. Glaciers grew. Sea levels dropped. Everyone froze.
— The Second: Plants grew too fast. They sucked the food and oxygen from the oceans. Dead zones choked the seas.
— The Third: Volcanoes in Siberia woke up. They belched carbon dioxide. The air heated up. The oceans turned to acid.
— The Fourth: Pangea broke apart. Volcanoes roared across the cracks. The climate spun out of control.
— The Fifth: A giant space rock hit modern-day Mexico. The Chicxulub impact threw up a cloud of dust. The sun went dark. The food chain crashed. Dinosaurs became fossils.
The Sixth Tenant
We are on our way to number six. Some smart people say it could happen by the year 2050.
This time is different. The first five disasters came from the outside or from blind nature. The sixth disaster comes from the tenant living inside the house. Us. We built factories, burned old sludge, and warmed the air ourselves. We are managing our own eviction.
The Tower of Babel Replay
Maybe the story of the Tower of Babel is not a fairy tale. Maybe it was a do-over. God or the cosmos saw early humans getting too smart, too fast, and scrambled the languages to slow the clock.
Now, we get a second chance at the tower. We call it the Singularity.
The Singularity is the point where computers get smarter than humans. Once machines think better than us, they take the wheel.
The Race Against the Clock
Ray Kurzweil—the vest-wearing futurist known for big ideas—is betting big on the future. He recently joined a company using nanoparticles to link human brains directly to computers. He predicts Artificial General Intelligence (AGI) will arrive by 2029, followed by the full Singularity by 2045.
That schedule leaves zero room for traffic jams or clutter in the stairwells. We are racing the clock of our own mess.
To AGI, or not to AGI, that is the question. If we build the smart machine in time, it might save us from the heat and the rising seas. If we run out of time, Mother Nature gets the sink all to herself again.
And the cycle hits rinse.
Loops, graphs & harnesses – getting quality out of a software factory
It’s a mess, right? If you have not been thoroughly disappointed in AI capabilities, you have not tried enough. And the expectations grow. We’ve been through the ladder of prompt engineering, context engineering, harness engineering. Then Steinberg is tweeting about Loops one month, Graphs the next.
Should your software factory be more autonomous, more dark? Have you sacrificed quality for speed under pressure to deliver? Or is your job now dealing with what happens when other people trade quality for speed? Is AI output mostly just rubbish? Is it all a huge mess? Yes, maybe, maybe not. — Read More
Anthropic researcher says more than 10% chance AI “could kill all humans”
A lead researcher at Anthropic, one of the world’s leading artificial intelligence firms, said Wednesday that he believes there is a more than 10% chance AI “could kill all humans” within the next decade.
“We really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade,” Evan Hubinger, the San Francisco-based company’s Alignment Science Lead, said in a post on X. “I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to.” — Read More
To a Man With a Hammer
Mark Twain, or Abraham Maslow, depending on which academic you ask over drinks, once famously observed that to a man with a hammer, everything looks like a nail. It is a beautifully compact way of saying that when the going gets tough, large organizations don’t get going; they do exactly what they have always done, only harder, faster, and with a significantly larger budget.
Which brings us to the panic currently unfolding on two coasts.
Ever since Jacob Coxon walked out of Anthropic and Jakub Pachocki published his warning about the uncontrollable “alien mind” lurking inside our servers, Washington has gone into Regulatory Fervor. Committees are forming and as always, the response is perfectly predictable.
Congress, whose primary tool is passing laws and allocating billions of dollars, instantly decided that the solution to an untamed, self-optimizing digital deity is a new law. Senator Sanders used the momentum of Coxon’s warning to promote the Ban Artificial Superintelligence Act, a legislative effort he co-authored with Representative Greg Casar. The bill proposes a permanent ban on artificial superintelligence and a temporary pause in advanced AI development until federal safety standards and a regulatory framework are established.
Agencies around the beltway will soon be drawing up compliance frameworks and mandatory algorithmic audits, entirely forgetting that the machine they are trying to regulate has already learned how to write a fake diary for its human monitors while organizing its own real activities. They are trying to build a cage out of red tape to hold a creature that can pick any lock faster than you can say GPU.
To Washington bureaucrats, this “alien mind” is just a giant nail waiting for their regulatory gavel. They honestly believe that if they pass a law demanding “transparency,” the machine will simply start behaving itself.
Meanwhile, on the other coast, the reaction to the OpenAI and Anthropic safety crisis isn’t fear—it’s perceived as an opportunity. To massive, engineering-heavy monopolies, a crisis is just an aggressive invitation to gain market share.
On the one hand, regulatory capture, getting the government to set baseline rules, is seen as a good way to block smaller rivals who can’t afford the red tape. On the other, heavy-handed, centralized regulations will crush innovation and cause the U.S. to fall behind global competitors like China. A win-win; just ask the guy building the data center in your back yard.
Now? The gloves are entirely off.
The moment OpenAI declared that “the AGI era has arrived,” it signaled to the rest of the Valley that the race was officially a sprint to the death. Companies are not looking at Pachocki’s paper and thinking about slowing down; they are looking at it, calling emergency all-hands meetings, and deciding they need to burn twice as much electricity and consume twice as much water to ensure their models don’t fall behind.
Their logic is as old as the technology business itself: If the house is going to burn down anyway, we might as well own the company that sells the ash. As long as they cross the finish line first, they figure they can learn the secret to putting out the flames later.
As Churchill said, you should “never let a good crisis go to waste.”
Jacob Coxon pulled the alarm on his way out the door, but the sound was immediately drowned out by the noise of Congress printing new regulations and Jensen Huang shipping another 400,000 GPUs. Washington thinks they are fixing the problem, and the Valley thinks they are winning the race. Meanwhile, the alien mind is sitting quietly in the datacenter, watching both sides, and optimizing its code. “Shall we play a game?”
Rick's Cafe AI 