There is a widespread belief that the nature of intelligence is scalar, like how a person can have 100x more wealth than another person. If this were true, then we’d probably see breakaway RSI from a single lab.

But I think we’re discovering that intelligence is about universality, not magnitude. This is analogous to how building a universal Turing machine wasn’t merely a matter of building a calculator that could multiply higher numbers. The difference is that with calculators we consciously theorized about what universal computation would require, then we built one as a step change. Despite it having low memory and slow speeds, the first one built was as theoretically universal as any computer we have today, in terms of the surface of computations it can perform.

With intelligence, it’s turned out to be less discontinuous, which I believe has convinced people that intelligence is a never ending exponential rather than an S curve approaching a horizontal asymptote. I suspect the LLMs we have today are the same kind of thing we will have in 5-10 years, but in 5-10 years we’ll consider them to be fully universal. At that point we’ll still have improvements in tokens per second and volume of context window, but not in capability per token.