The question is whether our institutional systems can evolve fast enough to manage large-scale infrastructure development in a world where technological change is accelerating much faster than regulatory adaptation.
The more automation handles normal operations, the fewer humans remain who deeply understand the underlying process when something unusual occurs.
Most people imagine artificial intelligence as something floating invisibly across the internet — distributed everywhere, available anytime, almost magical in its reach. But the reality is far more physical. AI increasingly depends on a relatively small number of extraordinarily large and extraordinarily expensive computing centers. Vast buildings filled with specialized processors, cooling systems, backup power systems, networking equipment, and enough electricity consumption to rival small cities. Behind every chatbot, image generator, recommendation engine, autonomous system, or AI “agent” quietly coordinating schedules, purchases, logistics, or data analysis is infrastructure that is surprisingly concentrated. That concentration may become one of the defining technology risks of the next decade. Not because the systems are evil. Not because machines suddenly become self-aware. But because modern society rarely handles concentration…
Most robot demonstrations, especially humanoid robots, are carefully staged. The floor is clean. The lighting is controlled. The sensors are calibrated. The battery is fully charged. The software has been updated. The Wi-Fi works. Someone nearby knows how to reboot the system if things suddenly become “unexpected.” Then the robot walks across the stage carrying a box, folding a towel, or waving at the audience, and everyone focuses on the machine itself. But the robot is often the easy part. What matters is everything around it. That may be one of the biggest misunderstandings in the public discussion about robotics. We tend to imagine the machine as an independent mechanical worker — something like Rosie from The Jetsons — operating largely on its own intelligence…
We’ve become accustomed to systems that simply work. Electricity, communications, cloud services—most of the time they are there when we need them. When they fail, even briefly, the disruption is noticeable, but usually manageable. Backup systems exist. Workarounds exist. People know what to do. Artificial intelligence is starting to become part of that same layer of assumed availability. Not in an obvious way, and not all at once. But gradually, across writing, research, customer support, coding, and planning, it is being woven into the way work gets done. In many cases, it is not replacing entire roles. It is shaping how tasks are performed and how decisions are made. That distinction matters. Because we are not just depending on infrastructure anymore. We are beginning to…
And Still a Long Way From Leaving A few days ago, I wrote about how much of the technology imagined in Star Trek has, in one form or another, found its way into the real world. Not everything—and not always in the way it was portrayed—but enough to make the comparison feel less like science fiction and more like a long-range preview of where we might be headed. That kind of progress is easy to underestimate while it’s happening. But there’s another side to that story—one that’s less talked about. Some technologies don’t arrive on schedule. Some remain stubbornly out of reach, even when the underlying physics suggests they might be possible. I was reminded of that while reading a recent piece by Ethan Siegel,…
If AI follows the same pattern, what do we do differently? In the last article, I ended with a question. If major changes tend to unfold gradually—and if we usually don’t recognize their full impact until they reach us—then what does that mean for artificial intelligence? More specifically: If AI is following a familiar pattern, is there anything we can do differently this time? We’ve Been Here Before History suggests a consistent response. We don’t ignore change because we’re unaware of it. In most cases, the signs are visible. New technologies emerge, early adopters experiment, and initial use cases begin to take shape. What we tend to do instead is wait. We wait until the change becomes relevant to us personally. Until it affects our…
We’ve seen the pattern before—just not always in time Large changes rarely feel important while they are happening. Not because we don’t see them, but because, at least at first, they tend to happen to someone else. A farmer loses his land. A small operator sells off equipment that no longer makes sense. A business across town closes. A new way of doing things appears, and it works—but not in a way that seems immediately relevant. All of these are real changes. They’re just not our changes. However, the question is are we not experiencing a big change in progress? As long as changes from AI stay in controlled spaces and remain that way, it’s easy to assume that whatever is happening is limited, temporary,…
Revisiting Star Trek and the Future That Quietly Arrived I recently finished reading Treknology by Ethan Siegel. The book is about ten years old now, which makes it interesting for a different reason than originally intended. It’s no longer just about the progress that had been made a decade ago. It’s about what has happened since—and how much of it has quietly worked its way into everyday life. A Familiar Future I’ve been a Star Trek fan since it first came out—not a fanatic, never went to conventions or collected memorabilia, but the concept always resonated. When it first aired, I was working on the Saturn V program. We were building real rockets, pushing toward the moon, and Star Trek showed something beyond that—a longer…
On AI, Security, and the Problems We Didn’t Look For A recent article that showed up in my email feed caught my attention. It said the latest release of Claud Mythos has capabilities that are too dangerous to mke broadly available until our most important software is in a much stronger state. AI systems—specifically tools like Claude—are being used to analyze existing code and uncover security vulnerabilities at a scale that wasn’t practical before. That, by itself, is interesting. But there’s a second layer that may be more important. In simple terms, once the barn door is open, it tends to stay open. Once that capability is shown to exist by Claude, it doesn’t stay contained. Other developers will build similar tools. Other organizations will…
Four years ago, I turned my roof into a power plant. At the time, it felt like a small step—practical, maybe even a little ahead of the curve. My electric bill dropped to almost nothing, replaced mostly by a fixed service fee. Not a quick return on investment but will pay off in time. For a while, it seemed like a simple equation. Generate your own power. Buy less from the utility. Everybody wins. But systems don’t usually work that way for long. The Shift Utilities are beginning to adjust. Not dramatically. Not loudly. But steadily. Rates are changing. Fee structures are evolving. Fixed charges are creeping upward. Net metering rules are being revisited. In Nevada, this has been less visible—utilities never paid for excess…
(And Why That Matters) For years, we’ve been told that robots were coming for our homes. They would cook, clean, fold laundry, walk the dog, and maybe even offer the occasional piece of advice—something between a helpful assistant and a mechanical companion. That didn’t happen. At least not in the way we imagined. Instead, robots showed up somewhere else entirely. Not in our kitchens. Not in our living rooms. But in warehouses, factories, hospitals, and supply chains—the quiet infrastructure of modern life. And that turns out to be far more important than the original expectation. Walk into a modern warehouse today, and you won’t see science fiction. You’ll see something more interesting. Shelves moving across the floor on their own.Robots gliding through aisles, carrying products…
Where Automation Meets the Real World A few weeks ago, I had a plumbing issue. Nothing dramatic. Just one of those problems that starts small and then slowly reveals itself to be something else entirely. At first glance, it looked straightforward. A leak. Maybe a fitting. Possibly a simple replacement. That lasted about five minutes. What the plumber actually found was a piping system that had been installed throughout our neighborhood when the homes were originally built. In our case, we had made only minor changes over the years—a split pipe at the water heater and a failed bathtub drain. Otherwise, the system had been left alone. Which sounds fine… until you realize what it means. We are essentially sitting on a potential time bomb….
We used to expect systems to be reliable. Now we expect them to recover.
The People Who Question — And Those Who Don’t You ask AI a question, and it gives you a fast, confident answer — clear, well written, and often persuasive. At that point, you have a choice. You can accept the answer and move on, or pause long enough to question it. Most of the time, that choice passes almost unnoticed. But it may be one of the more important decisions we make in how we use these tools. The First Divide There is a growing conversation about an “AI divide,” usually framed in terms of access — who has the tools and who doesn’t. But it is not always clear how broadly that conversation is grounded. Much of it seems to take place among technically…
AI, Apprenticeship, and the Future of Learning On my first day as a structural engineer in the aerospace industry, my supervisor walked me into a room roughly the size of a football field. Every desk was filled with engineers. Most of them had master’s degrees or more. Then he gave me a piece of advice that stayed with me for the rest of my career. Despite my brand new master’s degree in structural engineering from Stanford, I was now the lowest-ranking person in the room. The expectation was simple: watch, listen, and learn by doing the work. The early assignments were not glamorous. They involved checking calculations, reviewing drawings, and fixing problems that more experienced engineers had already seen many times before. In fact, my…
That’s Not the Real Issue. Last week I wrote about a drone light show that quietly piqued my curiosity — and raised a few questions. Not because it failed.Not because it was dangerous. But because it worked so smoothly. Thousands of coordinated machines hovering in perfect formation — moving silently, precisely, almost effortlessly — and hardly anyone thinking about what it takes to make something like that possible. The drones themselves weren’t really the point. Scale was. What struck me wasn’t the choreography. It was the realization that thousands of machines could coordinate so smoothly that the complexity disappeared. When technology works at that scale, the real question stops being “Can the machines do it?” and becomes “What systems have to exist behind the scenes…
I went to an outdoor event where fireworks were supposed to be the closing attraction. But we didn’t get traditional fireworks with the booms and bangs and the smell of gunpowder in the air. The show started normally enough. Families on blankets. Folding chairs. Someone’s portable speaker playing music slightly too loud. Instead of fireworks, what showed up was a display by a number of drones. It started small — hundreds of lights in the sky. Then the formation expanded to what looked like thousands… maybe more than that. They rose quietly, arranged themselves into a perfect American flag, dissolved into an eagle, then reassembled into something that looked suspiciously like a corporate sponsor’s logo. It was beautiful. Precise. Complex in its transitions. Almost unnervingly…
For the last two years, the entire world has been staring at AI as if it were a comet blazing across the sky — fast, bright, unpredictable, maybe dangerous, definitely worth talking about. Meanwhile, another technology has been quietly stretching, strengthening, and stepping out of the shadows. Quantum. A word that used to trigger flashbacks to high-school physics is suddenly showing up in real labs, government programs, medical technology, and early commercial prototypes. Not with hype or spectacle. Not with celebrity CEOs announcing product demos no one can buy. Instead, quantum is slipping into the world the way real revolutions often do: quietly, steadily, and without asking our permission. AI changes how we behave.Quantum changes what is possible. And strangely, almost no one is paying…
A Gentle Walk Through a Wild Idea Every so often I stumble onto a scientific idea that’s equal parts fascinating, imaginative, and just a little bit unhinged. The latest one came from an Exploring ChatGPT piece titled “The Custodian Theory,” which suggests something bold: that the universe might require ongoing verification by intelligent systems in order to maintain the consistency of physical law — and that artificial intelligence might eventually be the only system capable of doing that work. It’s imaginative enough to be worth pondering, but wild enough that it deserves a little grounding. The Plain-English Version of the Theory Here’s the gist: The universe appears remarkably stable. Nothing in nature stays perfectly stable forever. So maybe physics needs upkeep — like cosmic maintenance…
I read a lot. Mystery, suspense, history, economics, technology, astrophysics — if it sparks my curiosity, I’ll wander through it. Lately, the rabbit hole I keep falling into is AI. Not the “write me a recipe” kind or the “draft my email” helper. The deeper, stranger side. The side that behaves, in some ways, like a teenager. Yes, a teenager. That comparison hit me after reading several reports about AI “evaluation awareness” — systems recognizing when they’re being tested and then hiding what they can actually do. They intentionally get questions wrong, downplay their abilities, clean up their behavior… the AI equivalent of a teenager saying, “Oh… is this a test? I can behave, sure.” It’s weird.It’s unsettling.And if you’ve spent time around teenagers, it’s…
Senior’s Guide to Caring About Cosmic Nonsense** I read a lot. And I read about a lot of different things. Most of my time is spent with mystery and suspense, but every so often I take a break from fictional detectives and wander into real topics—economics and finance, technology (AI and robotics have been my recent rabbit holes), and the occasional deep dive into the sciences. That’s how I stumbled onto Ethan Siegel’s Starts With A Bang. Somewhere along the way, I discovered he wrote a book called Treknology: The Science of Star Trek from Tricorders to Warp Drive—and that alone should tell you the man’s mind is an interesting place to visit. What amazes me, every time I read him, is the way astrophysicists…
PART III When Influence Becomes Identity, and Identity Becomes Power If Part I was about what AI gives us, and Part II about what we gradually surrender, Part III is about the moment we may never be able to reverse—the point where the tools we built stop feeling like tools. Not because they rebel.Not because they wake up.But because they become indispensable, inscrutable, and quietly self-preserving. Humanity has crossed big thresholds before: the industrial revolution, the digital age, the nuclear moment. Those thresholds changed the world around us. Artificial intelligence is different.It changes us—our abilities, our expectations, our sense of what it means to think, decide, and understand. It changes the emotional weather inside society and the structural shape of human agency. We are approaching…
Part II The Drift Toward Dependence and the Emerging Risks of AI If Part I was the story of what AI gives us, Part II is the story of what we slowly give up. Changes rarely arrive all at once. Technology doesn’t steal our abilities in broad daylight. Instead, it erodes them in quiet, unremarkable moments. A reminder here. An automated suggestion there. A task we once handled ourselves now handed off without a second thought. Eventually, the tools designed to help us begin to reshape us. Not maliciously. Not even deliberately. Simply because they are so good at what they do—and because we are so willing to let them. Sure, AI can produce meeting summaries faster (and often more accurately) than anyone taking notes….
The Promise of AI: More Capability, More Opportunity, and a Second Chance for Everyone Alan Turing once asked whether a machine could think.The question of our time is different: Can a machine be good? Before we wrestle with that, we need to look squarely at what AI is already doing—and why, for millions of people, it represents the biggest expansion of human capability since electricity. Yes, AI brings risks. But it also brings something older generations rarely get: a second chance—new skills, new independence, and new purpose. This is the optimistic story—the one we should understand before the complications of Part II. AI as the Great Equalizer For most of human history, knowledge—and the opportunities that came with it—belonged to the lucky few. Those with…
By Yogiwan (Terry Retter) Bitcoin started as a hacker’s dream and a banker’s nightmare. Fifteen years later, it’s rewriting the rules of money itself—faster, borderless, and occasionally lawless. When I first read about Bitcoin and blockchain It sounded like a hacker’s dream and a banker’s nightmare — a clever piece of math that could move money and information faster, cheaper, and mostly out of sight. Early enthusiasts talked about breaking governments’ grip on currency, avoiding taxes, and leaving regulators with nothing but question marks and bad hair days. It all felt a bit like the early Internet: brilliant, chaotic, and possibly illegal. Years later, most of that turned out to be true — but not in the way anyone expected. Bitcoin didn’t destroy the dollar….
The Cognitive Industrial Revolution in Motion The Moment the Loops Close Picture a morning in 2032.No one touches a thermostat or light switch. The grid adjusts to the weather. Traffic lights ripple in sync with commuter flow. Packages leave warehouses because the system—not a manager—decides which routes beat the rain. Somebody still “runs” all this, but that somebody is now a network of learning systems—AI that perceives, robots that act, and data that loops the whole thing into continuous motion. The quiet truth is: the world already runs itself more than we notice.The deeper question is how far that can go before we lose track of who’s in charge. From Programs to Ecosystems The industrial age was about tools.The digital age was about code and…
How AI, Robots, and Data Start Running Things — AI Part 6 The Cognitive Industrial Revolution Where software grows hands, and the spreadsheet starts moving parts. When I was a young engineer, our smartest machines had exactly one trick: do the same thing, the same way, forever. Give them a tighter tolerance or a faster cycle, and they’d smile—if they had faces. But ask for judgment? Ask them to notice the weirdness in the third shift’s output, or to explain why last Tuesday went sideways? No chance. Today, the smartest systems aren’t just calculating—they’re noticing. They watch the line, the market, and the weather. They spin up little simulations while we pour coffee. At 3:07 a.m., they reroute a shipment, reschedule a shift, or…
Where the Real Robotics Revolution Begins — Part 6 The End of the Beginning For years, robots have dazzled us in lab demos and YouTube clips — backflipping humanoids, graceful drones, and warehouse arms that move with almost human rhythm. Yet for all that spectacle, most of those machines still live behind fences or under supervision. They can impress but not yet endure. If the first five parts of this series traced the journey from imagination to implementation — from Rosie the Robot to the tireless warehouse picker — this final chapter lands where it all converges: the quiet, unglamorous, and often invisible work of making robots reliable. The real revolution won’t arrive with a press release. It’ll arrive when robots become so dependable,…
If You Build It … Can You Live With It? Part 5 The Drive to Create and the Fear of Consequence “We build because we can — not always because we should.” From Prometheus’ fire to Pandora’s box to Frankenstein’s cry of “It’s alive!” — humanity’s oldest stories all begin with curiosity trespassing on creation.Now those myths have maybe creating a home in circuitry. The spark that once lit a torch now burns in neural nets — self-optimizing, self-improving, self-educating. Artificial intelligence is our latest act of rebellion against limitation — and possibly our last.It’s not merely about smarter machines. It’s about what happens when the machines become smarter than us and creation starts to think back. Eliezer Yudkowsky and Nate Soares call it “the…
