Tag Archives: Artificial Intelligence

The Innovation Paradox: Will Automation Be China’s Demise?

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What has China invented since paper and gunpowder? Well? Through communism, the state has shifted from invention to perfection.

China’s modern economic rise is undeniable. They are brilliant at taking existing concepts, developed elsewhere, and scaling them at a speed and volume no other country can match. Their ability to execute this is by operating outside the boundaries of international intellectual property laws, where the state sanctions the piracy of these laws because they themselves are doing this at the state level.

Today, China’s mastery has culminated in a massive push toward A.I., aggressively leading the world in robotics and automation. Across the country, pilot programs are emerging—like hotels run entirely by automated systems—with the ultimate goal of expanding machine labor to replace human workers.

But this brings us to a glaring contradiction. What happens to a nation built on labor when you take the labor away?

The Automation Divide: Capitalism vs. State Control

The pivot to robotics and automation driven by A.I., hinges entirely on the economic system implementing it. The core difference lies in how society handles freed human potential:

  • In a Capitalist Society: Introducing automation ideally frees citizens from physical labor, allowing them to shift focus toward new ideas, creative ventures, entrepreneurship, and original inventions. The system is designed to reward that organic creativity.
  • Under Communist Rule: Citizens have long been funneled into replication and structured labor rather than open, independent invention. When state-enforced automation strips away the need for that labor, it doesn’t free people to create—it simply leaves a massive population with nothing to do.

A Familiar Echo of History

When a state-controlled economy eliminates the primary purpose of its massive labor force without an outlet for organic growth, the social and economic friction becomes dangerous.

To quote the great Yogi Berra: “It’s déjà vu all over again.”

By systematically replacing its people with machines while maintaining rigid control over independent thought, the state risks repeating the structural breakdowns, economic stagnation, and severe human crises seen during the state-run farming years that led to mass starvation of the late 1950s.

China’s greatest modern strength—its ability to rapidly replicate and scale technology—might just build the very machines that displace its own workforce, leaving the world to watch what happens when a labor-centric superpower runs out of work for its people.

What’s your take? Can a state-driven economy successfully transition a displaced workforce, or is massive social instability inevitable?

If you don’t want data centers in your back yard, stop taking pictures!

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Humanity captures approximately 5 billion to 5.3 billion photos every single day. But this number increases to 14 billion images a day through sharing and reposting across messaging and social media. In data terms, this is 50 petabytes of photos, every, single, day!

Adding video to the equation completely blows the doors off the numbers. Video accounts for roughly 82% of all global internet data traffic. the world now creates, captures, or copies roughly 400,000 petabytes (400 exabytes) of data every single day.

To handle this volume, we need to build, finish, and fully pack 2 to 3 brand-new, massive hyperscale data center buildings every 24 hours.

That is the Sci-Fi apocalyptic view–– the pouring of concrete from helicopters onto the homes in rural neighborhoods. Fortunately is doesn’t actually look like this for one simple reason… we delete things. Because we cannot build 1,000 data centers a year, the industry relies on a massive filter. Out of those 400,000 petabytes generated today, 98% to 98.5% is instantly dropped, compressed, or deleted within seconds or hours of creation (temporary video streaming caches, transient network packets, automated logs, and extreme social media video compression).

There are roughly 1,200 to 1,300 active hyperscale facilities running globally and the tech industry builds and activates roughly 120 to 150 brand-new hyperscale data center buildings per year worldwide. A single modern hyperscale building typically spans between 200,000 and 500,000 square feet- or roughly 8 football fields, and many of the established centers are empty in anticipation of them being used.

To handle our actual retained data, we don’t need thousands of new buildings. We need to build about 130 new buildings a year, with each building averaging about 400,000 square feet. The real trick isn’t the square footage; it’s packing those square feet with denser, high-capacity hard drives and securing the massive electrical grid connections required to power them, and fortunately for Moore’s Law, hard-drive technology is still getting faster, smaller and cheaper.

But then there is the power and infrastructure issue– more crucial than the datacenter side of things, but that will be a future post. Until then–slow down on the picture taking. Do we really need to take or share a picture of a parking lot from a train window?