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Hey {{first_name | there}},
If AI is the future, why are we bringing back 1960s-era dirty power plants from the past to keep it running?
Let me explain what's happening right now that most people might be missing.
The Power Plants Nobody Wanted Are Back
In Chicago's Pilsen neighborhood, there's an oil-fired power plant from the 1960s. It was supposed to stay shut down. Too old, dirty and inefficient.
But it's running again.
Why?
AI data centers need so much electricity that obsolete "peaker" power plants are being forced back into service.
These plants were designed to only run during peak demand, maybe a few hours per month. Now they're running regularly because AI data center electricity demand could double by 2030.
Here's the uncomfortable math: Peaker plants only contribute about 3% of America's power, but they have the capacity to produce 19%.
The fact that we're tapping into emergency reserves just to keep AI training tells you everything about sustainability.
So while tech companies talk about carbon neutrality and saving the planet, they're literally restarting the most polluting power infrastructure we have.
The Solution? Put Data Centers in Space
This is no longer hypothetical. It’s actually happening.
Google announced Project Suncatcher, planning to launch space data centers with test flights starting in 2027.
Elon Musk said space data centers would be "the cheapest way to train AI not more than five years from now."
Jeff Bezos, Sam Altman, and Jensen Huang are all backing this idea.
Their logic: Earth doesn't have enough land or energy for AI's growth. So why not move computing to orbit where there's unlimited solar power and no local communities to upset?
A startup called Starcloud already launched satellites equipped with Nvidia GPUs. They're betting that computation belongs in space.
Think about what this means. We're not solving AI's energy problem. We're just moving it somewhere we can't see it.
OpenAI Is Training Journalists
While infrastructure burns dirty fuel and tech giants plan orbital data centers, OpenAI quietly launched something else: The OpenAI Academy for News Organizations.
They're offering journalists financial grants, technical support, and access to their latest models to integrate AI into newsrooms.
The goal? Help journalists automate administrative tasks and enhance investigative research.
Sounds helpful, right?
But here's what I'm thinking. The same company that's contributing to an energy crisis serious enough to restart dirty power plants is now positioning itself as journalism's helpful partner.
Newsrooms are struggling financially. OpenAI is offering free tools and training. Once you build your entire workflow around their platform, what happens when they decide to charge? Or change terms? Or prioritize their own interests over yours?
I'm not saying don't use the tools. I'm saying understand the dependency you're creating.
Andrew Ng Says We're Overhyping This
Meanwhile, Andrew Ng, one of AI's pioneers, just said something that contradicts everything Silicon Valley is selling:
"AI is limited and won't replace humans anytime soon."
He doesn't think artificial general intelligence is coming in the next few years. He looks at how manual and complex AI training still is and says "there's no way this is going to take us all the way to AGI just by itself."
This matters because the entire justification for restarting dirty power plants, spending $2 billion on acquisitions, and planning space data centers rests on the belief that we're building something truly transformative.
But what if we're not? What if current AI is just really good autocomplete that requires unsustainable amounts of energy?
What This All Means
Connect the dots with me:
AI companies need so much power that we're restarting the dirtiest plants we have
The solution being proposed is moving data centers to space instead of using less energy
These same companies are offering "free" tools to cash-strapped industries to create dependency
They're spending billions on acquisitions to monetize attention and keep people on platforms longer
And one of AI's pioneers is saying the technology is fundamentally limited
Something doesn't add up.
Either AI is revolutionary enough to justify environmental damage and massive infrastructure investment, or it's not.
Right now, we're paying the environmental cost while tech companies capture the profits.
Communities near these restarted power plants deal with pollution. Your electricity bills go up as data centers strain local grids.
And the actual sustainability problem keeps getting pushed somewhere out of sight.
Where the Opportunity Is
If you're building something in AI, here's what this means:
Understand that "free" AI tools from big companies are creating dependencies. If you're relying on OpenAI, Anthropic, or Google for everything, you have vendor lock-in risk.
Look for solutions that reduce AI's footprint rather than increase it. Companies will eventually need to prove their AI usage is sustainable. Tools that optimize, compress, or reduce compute will become valuable.
And most importantly: Build for problems that actually need AI, not problems where AI is just trendy. Because if Andrew Ng is right and current approaches are limited, the companies that survive will be the ones solving real problems efficiently.
The AI boom is real. But so is its power problem.
What are your thoughts on all this? Hit reply and let me know.
- Aashish
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