When the world's largest asset manager predicts a futures market for computing power and an exchange launches one within a week, the signal seems clear: compute has become the AI era's scarce commodity. Yet the same industry straining against that shortage is engineering its way out of it, targeting cost reductions of up to two orders of magnitude.

Two things are true in 2026: innovation is advancing at an unprecedented pace, and the cost of deploying new technologies is falling rapidly.

Anyone who has hit the usage limit on an AI subscription knows the problem: intelligence may be digital, but it is not free. At enterprise scale, that limit becomes a question of profitability. If agents consume more tokens than expected, the cost of automation can quickly start to look less attractive than the human labour it was supposed to replace.

Europe built its economy on the assumption of mild summers. In a hotter climate, cooling becomes a productivity tool, a workplace safety requirement, and a new layer of building infrastructure.

Time for a break or a brake?

Alan Greenspan, who presided over the Federal Reserve for more than eighteen years and came to embody the very idea of central banking, died 22 June at his home in Washington at the age of 100. He leaves behind the legacy of a man celebrated as the “Maestro” of the global economy, before the crises that followed made his record more controversial.

Just as markets are moving past energy inflation, geopolitical risk and sticky central banks, another source of volatility is building in the Pacific, under the name of El Niño.

The most interesting crypto story of 2026 is not the loudest one. Built by an eleven-person team with no outside investors, Hyperliquid has become one of the dominant trading venues in digital assets. But it is also extending on-chain trading into traditional market exposures. On the platform, users can take positions on oil, gold, indices, tokenised equities such as Tesla or Nvidia, and even synthetic exposure to SpaceX before its public listing.

It is probably the question landing most often on desks right now. The fear is easy to understand. A record pipeline of mega-listings is arriving into a market that is already stretched and heavily concentrated in AI, and the capital needed to absorb that supply has to come from somewhere. The history and the demand backdrop all argue that the fear is largely misplaced, yet the real risk is not the one investors are focusing on.

Not long ago, GPU chips were a gamer's luxury. Today, they are rapidly evolving into a distinct asset class, one that investors can finance, collateralize, lease, and even treat as yield-generating infrastructure.