Every AI Bet Is the Same Bet - Manas Bihani

Manas Bihani

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What Becomes Scarce After Intelligence?<br>An essay on why the next decade of AI may be defined less by models than by energy, memory, chips, architecture, and data.

Manas Bihani<br>Jul 21, 2026

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Two things happened this year that look like they belong to different industries.<br>In the first, the most valuable companies on earth became nuclear utilities. Microsoft restarted Three Mile Island. Amazon locked in nuclear power through 2042. All told, hyperscalers committed around 9.8 gigawatts of nuclear to AI in about a year, and sovereign wealth funds poured roughly $120 billion into the buildout. The bet underneath all of it: whoever delivers the most power wins. Build the biggest machine. Out-electrify everyone.<br>Thanks for reading! Subscribe for free to receive new posts and support my work.

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In the second, over two weeks this July, the floor fell out of the model business. Five frontier-adjacent open models shipped in a single window — Moonshot’s Kimi K3 at 2.8 trillion parameters, an American entry under a fully open license, DeepSeek’s V4, GLM-5.2, MiniMax’s M3. Kimi K3 hit number one on a coding leaderboard within hours, past a closed frontier model, at a fifth of the price, with weights you can download and run yourself. The gap between the best open model and the best closed one is now measured in months, not years. The bet underneath this one: intelligence is about to be free, and the value drains out of the model and onto whatever hardware you happen to own.<br>These look like opposite strategies. One spends hundreds of billions making intelligence bigger. The other gives it away. They are not opposite. They are two sides of a single wager, and almost nobody placing it will name the question they’re betting on.

The question is: does intelligence have a ceiling?

The bet nobody names

Here is what that one question decides.<br>If the demand for intelligence caps if, for most of what people actually want, some model is eventually “good enough” and getting smarter stops mattering then the efficiency camp wins everything. Good-enough intelligence commoditizes, races toward free, and runs on a box you own. The value stops living in the model and moves to whoever delivers it cheapest per watt. And the half-trillion-dollar nuclear buildout becomes the most expensive stranded asset in history: power plants built for a demand that plateaued.<br>If demand is uncapped if every gain in capability just unlocks a new appetite, the way cheap steel never sated the hunger for steel but multiplied it then brute force runs for a decade. The frontier keeps pulling away, the last increment of intelligence is always worth paying for, and the downloadable models are a footnote chasing a line that never stops moving. The reactor-builders win, and the efficiency camp spent its genius optimizing a commodity nobody cared to own.

Same coin. Everyone in AI has bet their capital on one side of it. And the tell that this is a real bet, not a rhetorical one, is that the smartest money is loudly and expensively betting both sides at once which is not conviction. It’s a hedge against a question the industry hasn’t admitted it’s asking.<br>So which way does the coin land? We have exactly one prior. It ran for four billion years.

The one time this experiment was run

Biology hit a hard intelligence ceiling, and we know precisely what happened underneath it.<br>The brain runs on about 20 watts, a fixed cap, set by what blood can deliver and what a skull can shed. And under that ceiling, evolution did not build a bigger, hotter brain. It couldn’t: brute force was never on the menu, because a brain runs on foraged food with no wall to plug into, and there’s no mutation-sized step from a chemical membrane to a digital logic gate. So it was forced into architecture and every trick it found is one the AI industry is now scrambling to copy. It fires only a few percent of its neurons at once, because a single spike is so costly that firing more would burn the brain’s entire energy budget sparsity as a power bill. It fuses memory and computation in the same place, so it never pays to shuttle data across a gap. It spends most of its energy about twenty-seven to one over computation not on thinking, but on moving information down the wire.

The verdict of the only run we have is unambiguous: under a fixed ceiling, architecture beats brute force. So if intelligence has a ceiling, biology already named the winner. The efficiency camp is betting with four billion years of precedent behind it.<br>And here’s the part that turns dusty precedent into this week’s headline.<br>The brain’s tricks are shipping, with model names

Why did five near-frontier models suddenly become things you can run at home? Because they are built on the brain’s first two tricks.

They’re sparse. Kimi K3 carries 2.8 trillion parameters but activates only about 50 billion per token a “mixture of experts,”...