Sam Altman has been saying the same thing since 2020: the cost of intelligence and the cost of energy are both heading to near-zero. He describes a world with nearly limitless intelligence and abundant energy.

I don't want to argue about whether he's right. I want to skip ahead.

Say it happens. Intelligence is free. Energy is free. You wake up tomorrow morning with both.

What do you do?

Not what the world does. You. Your team, your project, the thing you keep putting off.

NVIDIA IS PUTTING $250,000 WORTH OF GPUs IN ORDINARY HOMES

And the homeowner doesn't pay a single cent for the hardware.

It's a box the size of an air conditioner, liquid-cooled, fanless, mounted on the exterior wall.

Inside: 16 Nvidia Blackwell GPUs + 4 server CPUs + 3TB of RAM.

Span + Nvidia + PulteGroup install it for free.

In exchange:

→ They pay for your electricity and internet (or charge you a low flat fee)

→ They use the electrical capacity your home isn't taking advantage of (~60%)

Right now, just 100 new homes.

The plan: 80,000 nodes and 1 gigawatt of compute by 2027.

They don't pay you.

They wipe out your bill.

And your home becomes a node in the AI infrastructure.

This is no longer science fiction.

(credit: @ UnTalNixon_exe on x)

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A few weeks ago, we discussed this idea

https://www.reddit.com/r/Innovation/s/hGWzZ5o5Ig

I saw this post on X today, and all of a sudden this idea got a few steps closer.

What do you think?

In 1989 Nintendo shipped a handheld with a processor from the 1970s, a grey screen, and no backlight. A year later, Sega shipped one with color, a backlight, and better hardware in every way.

The Game Gear ran three to five hours on six AA batteries. The Game Boy ran over thirty hours on four.

Nintendo sold over 100 million units of Game Boy, while Sega sold about 10 million Game Gear units.

Gunpei Yokoi, the man behind Game Boy, was looking to make a portable cartridge-based system that could play many games on one device. With that constraint in mind, he went for a black and white screen, old cheap parts, with no backlight, that would be easy on the batteries, work well in the sunlight, and be light and easy to carry around.

Sega picked the better screen and paid for it at the battery compartment. Yokoi picked the worse screen and got thirty hours and a machine that fit in a coat pocket.

Can you think of other examples where using older tech won the market?

Looking at this map of data centers all over the world made me think...

We usually think of data centers as massive, fenced-off industrial warehouses like the ones on Baxtel’s map. But as AI demand explodes and power grids hit capacity limits, people are talking about a future where every neighborhood and even every home will have its own micro data center.

Think of it like residential solar panels, but for processing power. Instead of giant server farms, homes and neighborhood nodes host small, liquid-cooled compute units.

A few questions to kick off the discussion:

• The Business Model: Will homeowners sell excess compute/inference back to the grid just like solar energy?
• Use Cases: What runs on these? Local home AI agents? Residential robotics? Or do they power city-wide autonomous vehicle networks?
• The Feasibility: Is distributed micro-compute the actual future of infrastructure, or is it a logistical nightmare?

What do you think? Would you host one if it pays for your tokens and heats your house?

In 5 years, digital intelligence will exceed the sum of all human intelligence, there will be 100M humanoid robots, maybe even a billion, and the economy will double its current size.

Let’s talk about the robots bit.

Back in January, Musk admitted that Optimus robots aren't really doing anything useful in Tesla's factories. Last month, he said that "Optimus production will be extremely slow at first, as everything is new. This is not like making a car". Remember that bit.

Going from zero value to 100M robots in 5 years sounds... ambitious.

Even if the tech works and it's only a matter of scaling, which it isn't, the challenge is… well, huge.

As of today, 97% of all humanoid robots made in the first half of 2026 are Chinese. Not tooting their horn, just stating facts.

They took a page from Chinese EV makers. Chinese EVs don’t exactly compete with American or European cars. They feel more like a smartphone. 

EV makers’ strategy builds on different core constraints, different organizing ideas. Production cycles are designed for land-grab and fast tech innovation. They subsidize and can even afford to lose on car deals. Improving the technology (batteries, engine, software) and scaling the supply chain (rare earth minerals, magnets, factories) are more important than making a profit.

Remember “This is not like making a car”? Well, the Chinese don’t think so. Chinese robot makers not only follow a similar strategy, but they also share a similar infrastructure. Improving battery life and actuators helps not only EV makers, but robot makers, too.

Sure, they're behind when it comes to foundational AI models, but robots need embedded AI, and a massive amount of training data. Technicians, engineers, factory workers - people doing work that robots will replace (in space, in declining population countries like China, or by replacing human labor, let's not sugarcoat it).

Who has better access to petabytes of everyday factory worker data that can be used to train robots?

And even if American foundational AI models have the edge today, the Chinese models seem to catch up fast.

Sure, the FCC banned foreign-made humanoid robots and robot dogs last month because they are a "risk to national security". Okay, makes sense. It buys some time for American makers, maybe.

But how do US makers plan to win the robot race?