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The U.S. Might Not Be Ready for the Next Phase of AI

by FeeOnlyNews.com
2 months ago
in Markets
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The U.S. Might Not Be Ready for the Next Phase of AI
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China just made a massive bet on the future of its power grid.

But it’s not doing it by building more power plants. Instead, China is planning on sending thousands of robots out to run its energy infrastructure.

And this billion-dollar move could tell us a lot about how the next phase of the AI race will actually be won.

China’s Robot Army

China’s State Grid is planning to deploy roughly 8,500 robots across its network by 2026, at a cost of $1 billion.

Most of these robots, around 5,000, will be four-legged machines designed to patrol uneven ground and confined spaces.

Image: Caixin

Approximately 3,000 will be dual-arm wheeled units to handle equipment operation, maintenance and repairs inside facilities. China also plans to deploy 500 humanoid robots built to work on high-risk jobs like ultra-high-voltage (UHV) lines, where even a minor error can knock out part of the grid.

That means China will be sending robots into substations filled with live electrical equipment, onto transmission lines suspended hundreds of feet in the air and into remote terrain where human crews typically handle inspections and repairs.

The timing of this move makes perfect sense.

Because the power-hungry data centers that power artificial intelligence are driving a surge in electricity demand.

As we’ve discussed before, that demand is starting to impact how quickly new AI infrastructure can be built here in the United States. In parts of the country, large data center projects have run into limits on how much power they can draw from the grid. Some have been delayed because electricity simply isn’t available.

Our grid is increasingly becoming a bottleneck for the next phase of AI growth.

Meanwhile, China is making its power grid more adaptive.

Instead of relying on periodic inspections and manual checks, it’s starting to layer automation into the entire system. Sensors and software systems can continuously monitor conditions across the grid, feeding back data in real time.

And now robots can handle routine inspections, especially in places that are difficult or dangerous for human crews to reach.

Turn Your Images On

That changes how China’s grid will be maintained.

Instead of reacting to problems after they occur, operators can begin to anticipate them. Issues can be identified earlier, and repairs can happen faster with less risk to humans.

China’s infrastructure plan also represents a huge leap for robotics.

Most robots today work in controlled environments like factories and warehouses. Places where the layout doesn’t change much and tasks are predictable.

A power grid is very different.

It runs through cities, mountains and remote areas. Conditions change and weather is always a factor. Plus, the work varies from one location to the next.

If today’s more advanced robots can operate reliably in that kind of environment, it greatly increases the amount of jobs we’ll be able to use them for.

And once China deploys them at scale, they’ll start producing something just as important as the work itself.

Data.

Every inspection, every anomaly, every repair will become part of a feedback loop. And over time, that data will be used to improve how the system operates.

This data won’t just make the robots more effective. It will make the grid more efficient.

Notice how these trends are converging with each other?

Artificial intelligence is increasing the demand for power at the same time power systems are becoming more complex and more valuable. Robotics provides a way to manage that complexity at scale, while the data from those robots feeds back into improving the underlying technology.

It’s not one breakthrough driving progress forward.

It’s several systems advancing together and reinforcing one another as they do. In other words, a classic example of what George Gilder and I call “Convergence X.”

But while China is investing heavily in modernizing and automating its grid, much of the U.S. system is still dealing with aging infrastructure and rising demand.

And that concerns me.

Because the next phase of the AI buildout won’t be driven by software alone. It will depend just as much on the physical systems it runs on…

And whether they can keep up.

Power is one example, but it’s not the only one.

Ports like the Port of Los Angeles and Port of Long Beach still face congestion when demand spikes. Freight rail networks are already operating near capacity in key corridors. And much of the U.S. water system is decades old, with the American Society of Civil Engineers consistently giving it a near-failing grade.

Turn Your Images On

Image: publichealthpost.org

These are large, physical networks that are expensive to expand and slow to upgrade. And in many cases, demand is rising faster than they were built to handle.

China appears to understand that the next phase of the AI race won’t just be about building smarter models.

It will also be about modernizing the physical systems that these models depend on.

And increasingly, AI and robotics will become part of that solution.

Here’s My Take

China’s push to automate its power grid suggests the next phase of the AI race could depend just as much on the physical systems supporting it.

AI runs on power grids, transportation networks, water systems and supply chains that were largely built for a different era. And the United States has a lot of work to do to upgrade its aging infrastructure.

But if Washington and corporate America don’t start taking this problem seriously, China could end up winning the AI race by default.

Regards,

Ian King's SignatureIan KingChief Strategist, Banyan Hill Publishing

Editor’s Note: We’d love to hear from you!

If you want to share your thoughts or suggestions about the Daily Disruptor, or if there are any specific topics you’d like us to cover, just send an email to [email protected].

Don’t worry, we won’t reveal your full name in the event we publish a response. So feel free to comment away!



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