I agree with Dwarkesh even if it’s a contrarian take. The standard way of thinking is that AI gets cheaper every year. Better chips, better algorithms, more competition. Intelligence becomes abundant, so the price of compute should keep falling (aka intelligence too cheap to meter) His argument is almost the opposite, at least for the next few years. If frontier models become dramatically more economically useful faster than we can manufacture GPUs, then the value of each GPU rises faster than supply. Compute stops being priced by its cost to produce and starts being priced by what it can earn. How much would you pay to to hire geniuses in a data center? Or if one GPU can generate the output of a great software engineer, why would anyone rent it for today’s prices? The really interesting implication is that the frontier labs end up competing on who can afford the most compute. The labs making the most revenue can bid up GPU prices, making it even harder for everyone else to catch up. Basically it’s a super steep power law with only top labs surviving and the rest fighting to create small cheap models with no pricing power. Long term I still expect compute to get cheap. But during this transition, intelligence could become cheaper while the hardware that produces it becomes dramatically more expensive. That’s a pretty counterintuitive idea but a good idea imo.