Many people associate AI with coding, or helping students with their homework, or making sudden progress on the Riemann Hypothesis. It’s less well appreciated that all those capabilities map directly to physical AI. The tools that we use daily, such as Fable and GPT-5.6 Sol, can also help a robot integrate information, build a contiguous sense of its environment, break hard tasks into manageable chunks, develop a plan of action, and invent new routes from A to B. There are some obvious implications (robots are waking up and can dance) but also second-order effects. Most of those are about maps and physics.
Manufacturing everywhere for everyone
Most obviously, if machines get smarter and more nimble, it’s easier for them to make stuff. Goods get cheaper and easier to find. You don’t have to haul everything across oceans. A factory no longer has to make one product a million times — it can be reconfigured continuously. Making small custom batches finally makes economic sense. Economies of scale still apply but accrue mostly on the digital side. One AI, deployed in a million places around the world, can bake fresh croissants in all of them. And every croissant teaches it something. Sense, decide, and act until the croissants are VERY flaky but still have chew. It doesn’t so much matter where it happens to be baking. Digital intelligence is not tied to a place and learns from every deployment. Of course, the butter, wheat, and electricity are all somewhere in particular.
Physical limits overtake labor costs
What happens next? The hourly cost of labor matters less and less. If the labor in a pair of jeans drops to a dollar, suddenly the cotton and the zipper matter. Countries whose high labor costs have long priced them out of making things will gradually become competitive again. Once you take labor out of the equation, what’s left are the laws of physics and the facts of geography. How big is the country? Can a robot arm move faster than the speed of sound? (Yes, but…) What’s in the ground, and where? Is there an ocean nearby? What’s the average temperature, and is there clean water? Are the roads any good? Are there fast trains? Where’s the nearest yttrium mine? Physics, chemistry, and geography, not wages, will shape who prospers. Iceland and Quebec have cheap electricity, Mountain Pass in California has rare earths, and high-labor-cost countries like Germany and Japan suddenly have a path back.
Energy, Information, and Atoms
Why does physics matter so much? Because you can’t beat it, regardless of how smart you are. However the future plays out, energy is conserved, entropy always increases, a robot arm cannot move faster than the speed of sound in steel (or carbon fiber), and information can only propagate at the speed of light. What are the basics? Cognition, compute, and physical action convert energy, typically electricity, to useful ideas and actions. So everything involved in concentrating, converting, and storing energy, and then moving it via power transmission grids becomes a decisive factor. Energy sources such as uranium, wind, solar, and gas contribute to energy independence and unlock powerful compute. You can have all the best chips in the world, but if you can’t power them, then they are all paperweights. Oh right – now you need the pure silicon to actually make those chips. And the lasers and masks and lenses and solvents. Critical materials are critical precisely because they are needed for batteries and chips and superconductors. Getting thirsty and hungry with all this reading? Yes, let’s add the biology too. All biological life needs clean water; we need the seeds that contain the blueprints to grow our food, and that in turn requires fertilizers. And so on.
A Cambrian explosion of robot form factors
If things are easier to make and you have all the atoms, then robots are easier to make and easier to customize. The shapes are going to run wild. Humanoids make sense for only one reason: our houses, cities, and workplaces were built for creatures shaped like us. But think about what an economy actually makes, the billions of items from bicycle spokes to pencils to raspberry Pop-Tarts. What fraction of those really requires two arms and ten fingers? Today there are maybe 300 distinct robot shapes — a four-wheeled robot that carries people (a car), a two-legged robot on wheels with no arms at all, big quadrupeds the Canadian interns ride to the park. Three hundred is nothing. Expect thousands of robot forms. When making things is easy and scaling is digital, the shape gets optimized for the job for everything except the edge cases. Yes sure, I have a Swiss Army knife at home, but it’s only one of hundreds of other tools. You can see this in the war in Ukraine – just in terms of quadcopters, there are at least 6 major design patterns, based on the drone’s specific purpose in a team or swarm of drones.
Curiosity and Nimbleness
There’s one more thing that decides who benefits and it’s the most geographic fact of all. It’s whether the people in a place are willing to actively engage with a technology whose innovation cycle is measured in weeks. Countries that are nimble and let these systems get fielded, tested, deployed, and folded into a fast-changing economy stand to gain enormously over the countries where everything stalls on bad information. Take robot cars. Waymos are clearly safer than human drivers. So why isn’t there a national effort to get them to everybody, when more than 35,000 people a year are killed in traffic accidents in the US alone? I’ve asked people this and the answers range from “it’s too different” to “what about fair wages for NYC taxi drivers”. Sure, those are real concerns. But I’d like to think that most people would put kids getting to school safely ahead of “that’s how we’ve always done things here.” Our habits won’t change the facts (or the physics). Surely, a nimble and creative society can find a path forward that maximizes (and shares) the benefits.
Robots, Data, and Networks 