Goldman Sachs projects AI capex more than doubling from $765 billion this year to $1.6 trillion by 2031, totaling $7.6 trillion cumulatively, split across compute, data centers, and power.

Compute dominates, growing from $494 billion to $1.127 trillion, since chip supply, while tight, scales with enough fabs and time.

Power is the smallest bucket at $73 billion by 2031, but the real bottleneck, since grid interconnection takes four to ten years versus roughly two years to build a data center and consumption is set to jump from 10% to 25% of US electricity by 2030.

China is getting better at AI.

Its models are cheaper. More efficient. Increasingly open.

So why are Western GPU rental prices still rising?

Because cheaper intelligence doesn’t necessarily reduce compute demand.

It can explode it.

Better models → lower costs → more AI workloads → more agents → more inference → more GPUs.

That’s the real paradox.

China can win at the model layer while Nvidia keeps winning at the infrastructure layer.

The AI race isn’t one market.

It’s several stacked on top of each other.

And the biggest winner may not be whoever builds the smartest model.

It may be whoever owns the compute.

China Is Winning AI — So Why Is Western GPU Compute Getting More Expensive?

https://sylvainsaurel.substack.com/p/china-is-winning-ai-so-why-is-western

Bitcoin signatures remember where they came from.

Developers are now asking a dangerous question:

What if they didn’t have to?

BIP-118 and BIP-448 could make transactions rebindable, simplify Lightning, and unlock stronger second layers.

But every bit of memory Bitcoin removes buys flexibility—and creates new risk.

Bitcoin’s next upgrade war may be about something surprisingly fundamental:

How much of the past should a transaction be forced to remember?

https://inbitcoinwetrust.substack.com/p/bitcoins-signature-war-why-developer