everyone believes intelligence has unlimited demand, not just the maxis. but what the maxis get wrong is that the intelligence anthropic and openai and frontier models are building isn’t the generic kind you’re picturing. let me explain- the two biggest uses of compute are crudely either training or inference. the “generic intelligence” everyone says has unlimited demand comes from mainly inference, and inference needs very different power and utilization than training. inference comes in bursts, so you have to by default overbuild capacity to handle the peaks until the utilization problem is solved, which means almost by definition we are going to overbuild. but training doesn’t have that problem: the workload is steady and the demand curve is knowable. so data centers end up overbuilt right now precisely because utilization isn’t optimized yet. so anthropic and the other frontier labs are building their future on training, which is why they are saying they can soak up all this excess capacity. but their “intelligence” isn’t workplace productivity. it’s the leap toward singularity-type outcomes: new drug discoveries, cyber capabilities, recursive self-improvement. these are true 1-of-1s. that’s why when anthropic talks about “existential threats to humanity,” it isn’t talking about job losses, not really. it’s saying they’re on the precipice of unbelievable discoveries, because they’re still TRAINING MORE MODELS. but distillation is real and open source is real. the half-life of any frontier model is tiny because nothing protects it the way IP protects a patent. imagine a rare disease drug company that spends billions on research, and two months after a breakthrough a generic shows up. that company can never recoup its investment, unless it can discover an infinite number of rare disease drugs. THAT is the kind of intelligence anthropic is betting on. that’s what the $800bn of compute spend is betting on. so the questions you need to ask are: 1) if intelligence is two-tiered, what does each tier cost? what’s the cost of AGI, and what’s the cost of the generic intelligence that has infinite demand? and 2) are we allocating capital with the right risk curve and decay function to find out whether the AGI payoff is real? and if it is real, could a private company ever truly own it? that’s the cognitive dissonance at the heart of this entire paradox: everyone is gaslighting each other about what intelligence is as the unit of measurement is purposely kept vague by both the users and the suppliers. generic intelligence has unlimited demand, but it’s a certain race to the bottom. "superintelligence" is the opposite: it can't have unlimited demand by definition, but if it delivers even half of what it promises, no private company will ever get to keep it, at least not without the government stepping in to guard the moat (which is why anthropic keeps playing this angle up, without having shown any demonstration they are near this level of discovery at all). and at that point you have to ask who is going to hold the bag, and whether that was in fact, very intelligent at all.