Welcome back to The Hidden Layer. I’m Ian Krietzberg.
Thanks to
the reader who found the song playing in my head that A.I. could not identify—it was “Going Home” by Ben Thornewill. The minute I saw the title, it all came back to me… I was listening to his album, Quiet at the End of the Day, and somewhere along the line, my brain meshed one of his lyrics with a different artist’s. (It’s a really good song, by the way.) My soul can now rest. That was driving me crazy.
In today’s issue, a close look at one aspect of the
A.I. revolution that’s made it so different from other historical technological breakthroughs: a relentless push from governments to get people to actually use these (corporate) systems.
Mentioned in this issue: Alphabet, Nvidia, Meta, Tesla, Jon Bateman, Asad Ramzanali, Donald Trump, Michael Kratsios, and many more…
Let’s get into it…
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Three
Things You Should Know…
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Chains of thought aren’t the holy grail: The latest significant advance made on the backs of L.L.M.s has involved the transition from language models to reasoning models—like OpenAI’s “o” series, which essentially works through the introduction of internal “chains of thought” (CoT). CoT reasoning traces its origins back to 2022, and is premised on the notion that inducing a model to verbalize its step-by-step progression of thoughts (so to speak) refines the final result.
And yet, a recent working paper by researchers at Oxford and Google DeepMind, among other institutions, found that CoTs “are frequently unfaithful,
diverging from the true hidden computations that drive a model’s predictions, and giving an incorrect picture of how models arrive at conclusions.” This doesn’t mean that CoTs are useless as a means of model interpretability, the researchers note—just that they shouldn’t be “mistaken for ground truth” or, like with all things in A.I., overly relied upon. - The bubble that keeps on bubbling: Last week, Alphabet kicked off earnings season by noting plans
to spend $10 billion more on capex than previously expected due to rising demand for cloud services. That brings Alphabet’s total capex for 2025 up to a staggering $85 billion, a number the company expects to surpass in 2026.
Now Meta, Microsoft, Apple, and Amazon are all set to report earnings, and everyone is anxious to see more data on their respective pushes into A.I.—promising more good news for Nvidia et al. Torsten Slok, the chief
economist at Apollo Global Management, wrote in a recent note that the current A.I. investment cycle is even larger than the dot-com bubble due to the massive, seemingly relentless overvaluations of the biggest tech names of the day. Nvidia is currently trading at roughly 55 times its forward earnings. And don’t even get me started on Tesla (P/E
ratio: 164). - California, here we come?: Speaking of Tesla... according to an internal memo seen by Business Insider, the company told employees last week that it was planning to launch a robotaxi service—complete with safety drivers in each car—in San Francisco as soon as last weekend. While such a move might be
tolerated in regulation-light Texas, it’s not quite the same scenario in California. A spokesperson for the California Public Utilities Commission told me that “Tesla is not allowed to test or transport the public, paid or unpaid, in an autonomous vehicle, with or without a driver. Tesla is allowed to transport the public, paid or unpaid, in a non-A.V., which, of course, would have a driver.”
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Hallucination
of the Week
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Okay, it’s not exactly a hallucination, but how about this allegation that Meta “willfully and
intentionally” pirated terabytes of “high-quality” adult entertainment to train its A.I. models? That’s the somewhat surreal claim at the center of Strike 3 Holdings v. Meta, a fascinating lawsuit that alleges the intentional infringement of nearly 2,500 adult films owned by the plaintiff, all for the express purposes of training Llama and other Meta A.I.
video models. Meta, which is disputing the claims, did not return a request for comment.
And now for the main event…
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The United States and even Europe are rapidly cutting red tape and curtailing
their own regulatory guardrails to advance the interests of the private sector… all in the name of taking on China. What could possibly go wrong?
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Over the past week, governments from around the world have been practically tripping over
themselves to unshackle the A.I. industry and unleash its ostensibly transformative powers upon their economies before someone else does it first. In some cases, they have entered into partnerships with private companies, like OpenAI, as part of an effort to inject some tech magic into federal agencies. In other cases, lawmakers are salivating over the prospect of replacing (or just cutting) some federal workers entirely.
Of course, President Trump’s
recently unveiled A.I. Action Plan rages against “onerous” regulations and calls for an acceleration of A.I. adoption across the government, the military, federal agencies, etcetera. But now, even the regulation-loving European Union is waxing poetic about cutting red tape to make things “easier” for the A.I. industry. “We want Europe to be one of the leading A.I. continents,” E.U. President
Ursula von der Leyen said in a February speech. “And this means embracing a way of life where A.I. is everywhere.” France’s plan to become a global A.I. leader points to more than €109 billion
in investments for infrastructure projects, alongside calls for universal adoption. Last week, the Brits announced a (voluntary) memorandum of understanding with OpenAI, laying out ways in which they will collaborate to “identify opportunities for
how advanced A.I. models can be deployed throughout government and the private sector.”
The FOMO gripping the developed world is unlike anything since the birth of the internet, when the I.T. revolution swept through governments. Since then, there have been
several decades’ worth of advancements in the field of A.I. And yet, the current mania seems to have manifested all at once. The push to rapidly adopt these technologies is being driven by a sense of urgency that A.I. is—or will become—a kind of general-purpose “master” technology. According to Jon Bateman, co-director of
the Technology and International Affairs Program at the Carnegie Endowment for International Peace, this anxiety is undergirded by a “winner-take-all logic, where many people now believe that whoever gets ahead in A.I. could develop some kind of unassailable military or technological advantage, which is very destabilizing.” This is the catnip of the putative A.I. cold war with China that has informed much of the tech policy being pushed by Republicans and Democrats, alike.
But as Bateman
told me, “it’s not enough to innovate—you have to apply the technology within your own organizations.” That insight has led to various second- and third-order battles, all of which explain various governments’ motivations to promote the adoption of private sector innovation. Starting with the U.S. and China, various countries have now also entered the diffusion game: a push to disseminate these technologies within their own countries, and then spread them around the world.
There
are a few reasons this push for diffusion, according to Bateman, has become so urgent. First, increased market share allows for more revenue to be reinvested into R&D. Second, winning the market confers a “certain amount of political influence. If you’re the de facto commercial choice in a given country, then you’re setting standards,” he told me. Then, perhaps your own national values get the chance to diffuse into these new markets—a logic reminiscent of the Marshall Plan.
Put another way, American lawmakers and technologists want the lingua franca of A.I. to be English, not Mandarin.
This point was echoed to me by Asad Ramzanali, the director of artificial intelligence and technology policy at the Vanderbilt Policy Accelerator. Ramzanali explained that the U.S. government wants American leadership in A.I. “because we want American values to drive the technological and societal progress that comes from a powerful technology.”
Ramzanali made clear, though, that American leadership is not the same thing as driving larger profits for American companies.
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It’s all a bit ironic, as Dr. Matthew H. Hersch, a history of science professor at
Harvard, pointed out when we exchanged notes earlier this week. Modern technology has almost always been regulated by governments, its proliferation curtailed, encouraged, or guardrailed at one time or another. It’s these efforts, Hersch said, that have spurred the existence of passenger aviation, space travel, microelectronics, and the internet itself. But with regard to A.I., he continued, “we’re seeing something new in the history of regulation—not that technologies are receiving
active support from the federal government, but that this is happening more quickly, and without sufficient expert study, public debate, or judicial scrutiny.”
As it turns out, Hersch was just warming up. “Why, then, the rush to implement A.I.? Because it’s the ultimate con: the promise of something for nothing, of work without paying workers, and of a bucketload of money for whoever is able to monopolize the technology, their investors, and the political candidates they support,” he
said. “The me-too-ism of A.I. has been disappointing to watch.”
It’s true, as Hersch went on to say, that institutions are falling over themselves to embrace technologies they don’t fully understand—including plugging A.I. into “mission-critical” tasks. In the United States, the push for less regulation and more adoption has followed the Trump administration’s calls for severe reductions to the budgets of key innovating agencies, like the N.S.F., the N.I.H., DARPA, and NASA. And yet, as
Ramzanali pointed out, “A.I. wouldn’t exist without the N.S.F., DARPA, and others having funded it for decades.”
Notably, China just released an A.I. Global Governance Action Plan that, among other things, calls for international cooperation on the development and deployment of A.I. technologies—a concept that is diametrically at odds with the American approach. (“I
like America’s odds of success,” Michael Kratsios, the director of the Office of Science and Technology Policy, recently said.) Of course, this isn’t apples-to-apples—China operates a form of state-run capitalism that conveniently mixes private and public sector interests, and no one thinks the U.S. should rely on the government to lead on A.I.
advancement.
In any case, China’s competing A.I. plan highlights the stakes of the battle, which appears to be turning into a war for spheres of influence across the globe. Viewed another way, it’s also a proxy battle between capital-C capitalism and a state-run, socialized version of it. “It’s a pretty explosive situation,” as Bateman put it. The goal, he said, seems to be the creation of multiple “distinct” technological ecosystems. The race is “to incorporate the rest of the world
into those ecosystems.”
In this emerging reality, innovation alone is not enough; incorporating A.I. into the public and private sectors is the next frontier—even as the tech remains unaccountable and unreliable. What worries skeptics, of course, is whether all this “uncritical adoption,” as Ramzanali put it, creates new risks: to our civil rights, democratic decision-making, freedom from surveillance, etcetera. “The push to integrate A.I. products everywhere grants A.I.
companies power that goes beyond financial incentives, enabling them to concentrate power in a way we’ve not seen before,” Dr. Heidy Khlaaf, chief A.I. scientist at the A.I. Now Institute, told me. “The U.S.-China A.I. arms race is now being used to drive industrial policy initiatives designed to boost the tech industry, and avert safety and security scrutiny within military applications, while also winning government favors by promising unsubstantiated technologies that,
purportedly, will strengthen defense.” What could possibly go wrong?
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Up yours, robotaxi!: “I was stopped in traffic a few weeks ago and a Waymo came pulling
into my lane. It was backing up, and came within an inch of contact with my car. Not sure whether I was in a ‘blind spot’ or if they’re programmed to get that close or what. I felt a powerless sense of dread as it crept closer. I should’ve honked just to see whether it would respond, but I was frozen. Anyway, it stopped in time. I pulled around next to it, leaned over, and flipped a very deliberate bird at the empty vehicle. Hopefully there was a witness… somewhere. Then a week later, I
saw another Waymo while driving, and thought to myself, I hope it’s not keeping score!” —A Puck subscriber
Waymo in the carpool lane: “I live in Phoenix and take Waymos all the time. It’s an amazing service that I’ve really enjoyed. I’ve never had any safety concerns or issues. They go the speed limit (I’ve never been in one that’s gone over the speed limit), and appear to be overly cautious in how they operate; they follow every rule of the road that we humans
should always be following. That said, they’re still machines, and still learning. One time, at pickup at my kid’s school, there was some construction happening that was really odd and nonsensical, and a Waymo got stuck in it and had a hard time figuring it out. However, it appeared to learn from the issue, and a few days later it navigated it perfectly fine.” —A less belligerent Waymo user
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That’s all for today. I’ll see you Thursday.
Ian
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