Categories
AI Apple Google

The Floor

I compared the frontier to a three-star chef making grilled cheese in “Context Rot” โ€” the smartest models on earth spending most of their time on work beneath them, the way a chef trained at Le Bernardin might still melt cheese between two slices of bread on a Tuesday night and call it dinner. The comfort was the point: if the sharpest tool is saved for hard problems and something merely-very-good handles the rest, nobody’s losing anything. The floor was never the interesting part.

I’ve kept turning the joke over, and I think I had the wrong worry.

Watch what companies do with their AI spend, not what they say. Coinbase moved engineers off frontier models onto open weights and cut its AI spend nearly in half while usage kept climbing. Nvidia runs a closed model as orchestrator and routes the actual volume โ€” the daily uncelebrated bulk of it โ€” to open weights it controls. The frontier is becoming a dispatcher, deciding where the request goes and rarely doing the work itself. The instinct is to worry about whose open weights end up running that volume, and right now the most capable ones at scale are Chinese โ€” GLM, Kimi โ€” which makes it tempting to read this as a contest America is quietly losing: the floor of the AI economy built somewhere else, at a price export controls can’t touch. You cannot embargo a file already downloaded. You cannot price-match free.

But that framing has a hole. Google’s own Gemma family is open-weight and good enough to handle that daily volume without anyone reaching for GLM or Kimi. “Open weights are a Chinese story” only holds if you don’t count the open models the company running Android and half the internet’s search traffic has already shipped.

And once I saw that hole, a bigger one opened behind it. I’ve been trying Apple’s new Siri โ€” arriving with iOS 27 this fall, genuinely surprisingly good in beta โ€” and it made me realize open weights, of any nationality, were never going to cook most of the world’s dinners. Apple and Google are.

Consider what actually determines where the world’s routine inference runs. Not which model benchmarks best, not which weights are downloadable โ€” what’s already installed. Apple ships to well over a billion active devices before routing a single query through Siri’s new architecture. Nobody has to be persuaded to try it, or hear about it on a podcast; it’s the thing that answers when you press the button you’ve pressed for a decade. Google owns the search bar and the Android default the same way. Between them, that’s most of the world’s phones โ€” and phones are where most of the world’s questions get asked.

The open-weight framing assumes the floor is up for grabs, that whoever ships the best free model wins the daily grind by merit. But the floor was never a bazaar. It’s a set of defaults, owned by whoever already has the device in your hand, not whoever holds the most generous license. Apple didn’t need to win the model war to win this. Its heaviest reasoning tier is built with Google, running on Nvidia chips in Google’s cloud, under a deal reported at roughly a billion dollars a year โ€” Apple doesn’t fully own the engine doing the thinking. It doesn’t need to. It owns the button.

That’s a quieter concentration than an export-controls fight, and a harder one to dislodge. An open model can be forked, distilled, undercut, or out-competed by the next release. A billion phones with an assistant built into the lock screen cannot be routed around. Whoever’s weights hum underneath barely matters, the way it barely matters to a diner which supplier delivered the flour. What matters is whose kitchen the meal came from, and whose name is on the door.

The grilled-cheese chef was never the risk. Two chefs are about to own nearly every kitchen on earth, and most of us will never notice โ€” because a kitchen you’ve been eating out of for a decade doesn’t feel like something that was won. It just feels like home.

Owning the kitchen and getting paid for what’s cooked in it, though, turn out to be two different questions. That one’s for another post.

Categories
AI

The Layers Donโ€™t Hold

Stewart Brand drew the diagram in 1999, in The Clock of the Long Now, though heโ€™d been developing the idea for years before that. Six concentric rings, each representing a layer of civilization, each moving at a different speed. Fashion at the outside, changing season to season. Commerce beneath it, slower. Infrastructure below that โ€” roads, power grids, buildings. Then governance. Then culture. At the center, moving so slowly it seems not to move at all: nature.

The diagram is elegant, but Brandโ€™s real insight is about the relationship between layers, not the layers themselves. He called the framework pace layers. The fast layers innovate. The slow layers stabilize. Fashion gets to be experimental and throwaway precisely because infrastructure doesnโ€™t. Governance can afford to be deliberate because culture provides continuity underneath it. The whole system depends on this differential. Each layer absorbs shock from the one above it and passes only the most durable changes downward. Itโ€™s not inefficiency โ€” itโ€™s architecture.

Brand also had a name for what happens when the differential breaks down. He called it โ€œlayers crashing.โ€ When a fast layer accelerates past the capacity of the layer beneath it to absorb and adapt, the system loses its self-correcting character. The fast layer doesnโ€™t just move quickly anymore โ€” it damages the slow layerโ€™s ability to function. Infrastructure overwhelmed by commerce becomes fragile. Governance overwhelmed by technology becomes irrelevant. The stability that the slow layers provide isnโ€™t guaranteed. It has to be continuously earned.

We are in a layers-crashing moment. The technology layer is moving faster than it has in any of our lifetimes, possibly faster than it ever has. And the layers below it โ€” infrastructure, governance, culture โ€” are discovering that the shock-absorption mechanisms theyโ€™ve refined over centuries werenโ€™t designed for this.


Dario Amodei published a long policy essay recently. He opens with Treebeard โ€” the ancient, slow-speaking tree from Lord of the Rings whom the Hobbits must somehow persuade to act quickly enough to matter. Itโ€™s the same intuition as Brandโ€™s pace layers, arrived at from a different direction. The problem isnโ€™t that governance is broken. The problem is that it was built for a different tempo, and the tempo has changed.

Whatโ€™s new in Amodeiโ€™s essay โ€” and it feels genuinely new โ€” is the shift in register. For several years, Anthropicโ€™s public posture on regulation has been: transparency first, binding rules later, once we understand the shape of the risks well enough to target them precisely. That posture made sense when the risks were theoretical. It makes less sense now. The pivot in the essay is Amodeiโ€™s own most advanced model, Claude Mythos Preview, which he describes as having โ€œscrambled the global cybersecurity landscape.โ€ He is using his own product as the evidence that the moment for incrementalism has passed.

The five policy areas he covers โ€” regulation, macroeconomics, scientific innovation, civil liberties, geopolitics โ€” each map onto a different pace-layer collision. The cybersecurity risk to financial infrastructure is commerce meeting governance too fast. The job displacement problem is commerce and culture in conflict, with governance lagging both. The civil liberties section is perhaps the most unsettling: the worry that AI hands governments tools of surveillance and coercion that the legal architecture of democracy โ€” built for a slower world โ€” simply cannot constrain.

The regulatory framework he proposes is modeled on the FAA: mandatory third-party testing of frontier models, government power to block deployment, four specific risk categories as scope limiters. It is more concrete than anything Anthropic has proposed publicly before. The FAA analogy is meant to reassure โ€” we have regulated powerful technologies before, we know roughly how this works โ€” and it largely does reassure. Though itโ€™s worth holding alongside it a genuine open question: whether regulatory bodies can develop the expertise and independence to govern a technology this fast-moving before the technology moves again. The history of industry regulation suggests this is hard. It doesnโ€™t suggest itโ€™s impossible.

Brandโ€™s diagram has one more feature worth noting. The arrows donโ€™t only point downward, from fast layers shaping slow ones. They also point upward: the slow layers constrain what the fast layers can become. Culture shapes what commerce builds. Governance shapes what infrastructure gets funded. Nature sets limits that no other layer can override. The relationship is bidirectional, and the bidirectionality is the point. What Amodei is calling for โ€” urgently โ€” is for the slow layers to begin exerting upward pressure again, before the differential becomes so extreme that they lose the capacity to do so.

Whether they can move quickly enough is the question Brandโ€™s diagram canโ€™t answer. Treebeard wakes up, eventually. The forest burns faster than he walks.

Categories
AI Business Investing Technology

The Scarcity Portfolio: Navigating Sovereign Debt, Wafer Bottlenecks, and Orbital Compute

Today I was watching the interview of Gavin Baker by Patrick Oโ€™Shaughnessy on his Invest Like the Best podcast. Like prior conversations this was another fascinating excursion into the mind of a sophisticated and very successful tech venture investor.

During the conversation, Patrick asked Gavin what agents he was using that were especially helpful and he mentioned one which summarizes YouTube podcasts and videos for him. Like most of us Baker just doesnโ€™t have the time to watch or listen to them himself so good summaries are really helpful.

Turns out Iโ€™ve been working on a Google Gemini Gem that does this for me. When Baker mentioned his I fired up the new Gemini 3.5 Flash model and asked it to summarize the Baker interview.

Later in the conversation Baker used the term โ€œbattlefield AIโ€ which caused me to go back to Gemini again to learn more about that. The results were so interesting that I asked Gemini to create a syllabus for a semester class on these subjects. After that I asked it to convert our whole conversation into a Markdown file so I could share it. Youโ€™ll find it below.

I found this whole experience pretty stunning. I came away very impressed with Gemini 3.5 Flash both for the quality of the responses but also the sheer speed. Wow!

Anyway I hope you enjoy the following!


Categories
Chemicals Petroleum Semiconductors

The Invisible Layer Beneath the Chip

At the edge of a semiconductor fab, nothing looks dramatic.

No flames. No smoke. No sense of weight.

Just pipes, valves, and a silence so controlled it feels artificial.

Itโ€™s easy, standing there, to believe that oilโ€”the old engine of the economyโ€”has been replaced by something cleaner, lighter, more abstract. Software, maybe. Or data. The kinds of things that donโ€™t spill.

But step a little closer, and the illusion breaks.

A modern fab is less like a factory and more like a chemistry experiment that never ends. Gases move through stainless steel arteries. Liquids are mixed, spun, deposited, stripped away. Surfaces are etched and re-etched until what remains is measured in atoms, not microns. The machinesโ€”Applied Materials, Lam Researchโ€”are precise, but they are not the story. The story is what flows through them.

Chemicals are doing the real work.

Not in bulk, the way oil once did. Not with force. But with specificity.

A barrel of oil is valuable because of its densityโ€”how much energy it contains. A liter of photoresist is valuable because of its selectivityโ€”what it allows to exist and what it removes. One powers motion. The other defines structure.

Structure is where the modern economy hides its value.

A semiconductor is not impressive because of what it consumes. Itโ€™s impressive because of what it constrains. Billions of transistors, each one placed, shaped, and insulated with a chemical discipline that borders on obsession. The difference between a working chip and a useless one is often a contaminant you cannot see.

This is a different kind of industrialism.

The 20th century scaled by adding moreโ€”more fuel, more steel, more throughput. The 21st century scales by removing everything that shouldnโ€™t be there. Purity is the limiting factor. Not how much you can move, but how precisely you can control.


From a distance, it can look like oil has become less important. The headlines have shifted. The glamour has moved on.

But the truth is more entangled.

Most of the chemicals inside a fab begin their lives as hydrocarbons. The solvents, the polymers, even some of the specialty gasesโ€”downstream of the same geological inheritance. Oil didnโ€™t disappear. It changed roles. It moved from the foreground to the substrate.

The question, then, isnโ€™t whether chemicals have replaced oil. Itโ€™s whether the economy has learned to express value differently.

Less in how much energy we can release. More in how carefully we can shape matter.


Semiconductors are the clearest example, but not the only one. Pharmaceuticals follow the same logic. Advanced materials, too. In each case, the breakthrough isnโ€™t scaleโ€”itโ€™s control. The ability to operate at the edge of whatโ€™s physically possible, and to do it repeatedly.

Which raises a quieter possibility.

That the defining resource of the next era isnโ€™t oil, or even chemicals.

Itโ€™s precision.

And chemistry is simply the language we use to achieve it.


Categories
News

Turning Out the Lights

[Note: see also The Murder of the Washington Post by Ashley Parker who writes: “Jeff Bezos, the billionaire owner ofย The Washington Post, and Will Lewis, the publisher he appointed at the end of 2023, are embarking on the latest step of their plan to kill everything that makes the paper special.”]

I was struck this morning by the brutal dismantling of the Washington Postโ€™s international reporting capabilities. The list of bureaus being shuttered by the paper reads like a roll call of the 21st centuryโ€™s geopolitical fault lines: New Delhi, Sydney, Cairo, the entire Middle East team, China, Iran, Turkey.

It is a stunning retreat.

But to view this merely as a corporate restructuring or a casualty of the dying business model of print journalism seems to miss a deeper, darker signal. This seems like an actual cultural symptom.

“The world is becoming less America-centric by the minute while the United States is becoming more America-centric than ever.”

At the exact moment technology has rendered the world indistinguishable from a single roomโ€”where a virus, a meme, or a financial crash in one corner sweeps across the floor to the other in secondsโ€”we are choosing to partition off that room.

There is a tragic symmetry to it. As the center of gravity shifts away from the us, the we respond not by engaging harder, but by closing its eyes.

When a newspaper that has shaped history decides that “reporting on the world” is no longer of valuable enough, it is doing more than saving money – although clearly thatโ€™s the primary motivation. It seems to be a surrender to the idea that what happens “over there” doesn’t matter enough to us because the people who were supposed to tell us it was coming are gone.

We seem to be turning out the lights in the rooms we find too difficult, believing that if we cannot see the world, the world cannot touch us. Feels wrong.

The moves closing these bureaus are part of broader cuts at the paper:

  • Closing the Sports section
  • Closing the Books section.
  • Restructuring and shrinking the Metro desk.
  • Suspending the Post Reports podcast.